diff --git a/notebooks/bulk_modulus_with_gpaw.ipynb b/notebooks/bulk_modulus_with_gpaw.ipynb index 52fe0c4a..7a35a698 100644 --- a/notebooks/bulk_modulus_with_gpaw.ipynb +++ b/notebooks/bulk_modulus_with_gpaw.ipynb @@ -1 +1,256 @@ -{"metadata":{"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":5,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# Elastic Properties\nCalculate the bulk modulus for Aluminium using the [GPAW](https://wiki.fysik.dtu.dk/gpaw/) DFT code:","metadata":{},"id":"cfa4e782-0e68-4a51-8d57-cb0eccf8e8bb"},{"cell_type":"markdown","source":"## Equation of State \nOne way to calculate the bulk modulus is using the Equation of State to calculate the equilibrium properties:","metadata":{},"id":"81c7f93c-1539-46db-8917-34a5c3b05744"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators.ase import evaluate_with_ase\nfrom atomistics.workflows.evcurve.workflow import EnergyVolumeCurveWorkflow\nfrom gpaw import GPAW, PW\n\nworkflow = EnergyVolumeCurveWorkflow(\n structure=bulk(\"Al\", a=4.05, cubic=True),\n num_points=11,\n fit_type='polynomial',\n fit_order=3,\n vol_range=0.05,\n axes=['x', 'y', 'z'],\n strains=None,\n)\ntask_dict = workflow.generate_structures()\ntask_dict","metadata":{"trusted":true},"execution_count":1,"outputs":[{"name":"stderr","text":"[jupyter-pyiron-2datomistics-2dco7ko9rv:00594] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n","output_type":"stream"},{"execution_count":1,"output_type":"execute_result","data":{"text/plain":"{'calc_energy': OrderedDict([(0.95,\n Atoms(symbols='Al4', pbc=True, cell=[3.9813426685908118, 3.9813426685908118, 3.9813426685908118])),\n (0.96,\n Atoms(symbols='Al4', pbc=True, cell=[3.9952635604153612, 3.9952635604153612, 3.9952635604153612])),\n (0.97,\n Atoms(symbols='Al4', pbc=True, cell=[4.009088111958974, 4.009088111958974, 4.009088111958974])),\n (0.98,\n Atoms(symbols='Al4', pbc=True, cell=[4.022817972936038, 4.022817972936038, 4.022817972936038])),\n (0.99,\n Atoms(symbols='Al4', pbc=True, cell=[4.036454748321015, 4.036454748321015, 4.036454748321015])),\n (1.0, Atoms(symbols='Al4', pbc=True, cell=[4.05, 4.05, 4.05])),\n (1.01,\n Atoms(symbols='Al4', pbc=True, cell=[4.063455248345461, 4.063455248345461, 4.063455248345461])),\n (1.02,\n Atoms(symbols='Al4', pbc=True, cell=[4.076821973718458, 4.076821973718458, 4.076821973718458])),\n (1.03,\n Atoms(symbols='Al4', pbc=True, cell=[4.0901016179023415, 4.0901016179023415, 4.0901016179023415])),\n (1.04,\n Atoms(symbols='Al4', pbc=True, cell=[4.1032955854717175, 4.1032955854717175, 4.1032955854717175])),\n (1.05,\n Atoms(symbols='Al4', pbc=True, cell=[4.1164052451001565, 4.1164052451001565, 4.1164052451001565]))])}"},"metadata":{}}],"id":"7e5c6f17-3774-4b3b-915c-8b0611ec0497"},{"cell_type":"markdown","source":"In the first step the `EnergyVolumeCurveWorkflow` object is initialized including all the parameters to generate\nthe strained structures and afterwards fit the resulting energy volume curve. This allows the user to see all relevant\nparameters at one place. After the initialization the function `generate_structures()` is called without any\nadditional parameters. This function returns the task dictionary `task_dict` which includes the tasks which should\nbe executed by the calculator. In this case the task is to calculate the energy `calc_energy` of the eleven generated \nstructures. Each structure is labeled by the ratio of compression or elongation. In the second step the `task_dict` \nis evaluated with the [GPAW](https://wiki.fysik.dtu.dk/gpaw/) simulation code using the `evaluate_with_ase()` function:","metadata":{},"id":"2c128729-f9b0-4b91-9995-3403f2887602"},{"cell_type":"code","source":"result_dict = evaluate_with_ase(\n task_dict=task_dict,\n ase_calculator=GPAW(\n xc=\"PBE\",\n mode=PW(300),\n kpts=(3, 3, 3)\n )\n)\nresult_dict","metadata":{"trusted":true},"execution_count":2,"outputs":[{"name":"stdout","text":"\n ___ ___ ___ _ _ _ \n | | |_ | | | | \n | | | | | . | | | | \n |__ | _|___|_____| 24.1.0\n |___|_| \n\nUser: jovyan@jupyter-pyiron-2datomistics-2dco7ko9rv\nDate: Wed May 1 22:30:09 2024\nArch: x86_64\nPid: 594\nCWD: /home/jovyan\nPython: 3.10.12\ngpaw: /srv/conda/envs/notebook/lib/python3.10/site-packages/gpaw\n_gpaw: /srv/conda/envs/notebook/lib/python3.10/site-packages/\n _gpaw.cpython-310-x86_64-linux-gnu.so\nase: /srv/conda/envs/notebook/lib/python3.10/site-packages/ase (version 3.22.1)\nnumpy: /srv/conda/envs/notebook/lib/python3.10/site-packages/numpy (version 1.26.4)\nscipy: /srv/conda/envs/notebook/lib/python3.10/site-packages/scipy (version 1.13.0)\nlibxc: 6.2.2\nunits: Angstrom and eV\ncores: 1\nOpenMP: True\nOMP_NUM_THREADS: 1\n\nInput parameters:\n kpts: [3 3 3]\n mode: {ecut: 300.0,\n name: pw}\n xc: PBE\n\nSystem changes: positions, numbers, cell, pbc, initial_charges, initial_magmoms \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 729, 748\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 16*16*16 grid\n Fine grid: 32*32*32 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 32*32*32 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 159.93 MiB\n Calculator: 3.78 MiB\n Density: 1.91 MiB\n Arrays: 0.81 MiB\n Localized functions: 0.79 MiB\n Mixer: 0.31 MiB\n Hamiltonian: 0.55 MiB\n Arrays: 0.53 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.32 MiB\n Arrays psit_nG: 0.55 MiB\n Eigensolver: 0.22 MiB\n Projections: 0.04 MiB\n Projectors: 0.32 MiB\n PW-descriptor: 0.20 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | Al | \n | .---------. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 1.990671 1.990671 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.990671 0.000000 1.990671 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.990671 1.990671 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 3.981343 0.000000 0.000000 16 0.2488\n 2. axis: yes 0.000000 3.981343 0.000000 16 0.2488\n 3. axis: yes 0.000000 0.000000 3.981343 16 0.2488\n\n Lengths: 3.981343 3.981343 3.981343\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2488\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:30:13 -14.882425\niter: 2 22:30:15 -14.888515 -2.60 -0.94\niter: 3 22:30:18 -14.900036 -2.44 -0.96\niter: 4 22:30:21 -14.894259 -3.56 -1.21\niter: 5 22:30:24 -14.894996c -5.28 -2.02\niter: 6 22:30:27 -14.895377c -4.42 -2.09\niter: 7 22:30:30 -14.895377c -6.24 -3.62\niter: 8 22:30:32 -14.895377c -8.01c -3.81\niter: 9 22:30:34 -14.895378c -8.43c -3.83\niter: 10 22:30:37 -14.895378c -10.06c -4.52c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +21.064728\nPotential: -11.809468\nExternal: +0.000000\nXC: -24.083645\nEntropy (-ST): -0.066076\nLocal: -0.033954\nSIC: +0.000000\n--------------------------\nFree energy: -14.928416\nExtrapolated: -14.895378\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.98391 2.00000\n 0 5 5.98391 2.00000\n 0 6 5.98391 2.00000\n 0 7 13.41407 0.00000\n\n 1 4 6.93763 1.99987\n 1 5 6.93763 1.99987\n 1 6 8.35072 0.02220\n 1 7 8.35072 0.02220\n\n\nFermi level: 7.90175\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 739, 767\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 16*16*16 grid\n Fine grid: 32*32*32 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 32*32*32 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 175.34 MiB\n Calculator: 3.82 MiB\n Density: 1.92 MiB\n Arrays: 0.81 MiB\n Localized functions: 0.80 MiB\n Mixer: 0.31 MiB\n Hamiltonian: 0.55 MiB\n Arrays: 0.53 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.35 MiB\n Arrays psit_nG: 0.56 MiB\n Eigensolver: 0.22 MiB\n Projections: 0.04 MiB\n Projectors: 0.32 MiB\n PW-descriptor: 0.20 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 1.997632 1.997632 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.997632 0.000000 1.997632 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.997632 1.997632 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 3.995264 0.000000 0.000000 16 0.2497\n 2. axis: yes 0.000000 3.995264 0.000000 16 0.2497\n 3. axis: yes 0.000000 0.000000 3.995264 16 0.2497\n\n Lengths: 3.995264 3.995264 3.995264\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2497\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:30:41 -14.901011\niter: 2 22:30:44 -14.906870 -2.60 -0.94\niter: 3 22:30:47 -14.916095 -2.47 -0.96\niter: 4 22:30:50 -14.909770 -3.60 -1.22\niter: 5 22:30:54 -14.910476 -5.19 -2.03\niter: 6 22:30:58 -14.910818c -4.39 -2.08\niter: 7 22:31:02 -14.910819c -6.19 -3.56\niter: 8 22:31:06 -14.910819c -7.98c -3.81\niter: 9 22:31:10 -14.910820c -8.50c -3.83\niter: 10 22:31:14 -14.910820c -10.09c -4.48c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, 0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +19.609492\nPotential: -10.740904\nExternal: +0.000000\nXC: -23.714414\nEntropy (-ST): -0.065421\nLocal: -0.032284\nSIC: +0.000000\n--------------------------\nFree energy: -14.943530\nExtrapolated: -14.910820\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.88373 2.00000\n 0 5 5.88373 2.00000\n 0 6 5.88373 2.00000\n 0 7 13.25946 0.00000\n\n 1 4 6.83715 1.99985\n 1 5 6.83715 1.99985\n 1 6 8.25115 0.01891\n 1 7 8.25115 0.01891\n\n\nFermi level: 7.78599\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 748, 767\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 176.70 MiB\n Calculator: 4.59 MiB\n Density: 2.40 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.80 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.41 MiB\n Arrays psit_nG: 0.56 MiB\n Eigensolver: 0.22 MiB\n Projections: 0.04 MiB\n Projectors: 0.32 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | Al | \n | .---------. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.004544 2.004544 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.004544 0.000000 2.004544 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.004544 2.004544 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.009088 0.000000 0.000000 18 0.2227\n 2. axis: yes 0.000000 4.009088 0.000000 18 0.2227\n 3. axis: yes 0.000000 0.000000 4.009088 18 0.2227\n\n Lengths: 4.009088 4.009088 4.009088\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2227\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:31:21 -14.915469\niter: 2 22:31:25 -14.921113 -2.61 -0.94\niter: 3 22:31:29 -14.928129 -2.49 -0.95\niter: 4 22:31:34 -14.921329 -3.65 -1.23\niter: 5 22:31:38 -14.921925 -5.12 -2.04\niter: 6 22:31:42 -14.922306c -4.38 -2.09\niter: 7 22:31:46 -14.922307c -6.21 -3.62\niter: 8 22:31:50 -14.922306c -8.03c -3.81\niter: 9 22:31:54 -14.922307c -8.51c -3.81\niter: 10 22:31:58 -14.922307c -10.13c -4.49c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +18.208265\nPotential: -9.713675\nExternal: +0.000000\nXC: -23.353256\nEntropy (-ST): -0.064736\nLocal: -0.031272\nSIC: +0.000000\n--------------------------\nFree energy: -14.954675\nExtrapolated: -14.922307\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.78499 2.00000\n 0 5 5.78499 2.00000\n 0 6 5.78499 2.00000\n 0 7 13.10778 0.00000\n\n 1 4 6.73786 1.99982\n 1 5 6.73786 1.99982\n 1 6 8.15344 0.01607\n 1 7 8.15344 0.01607\n\n\nFermi level: 7.67184\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 751, 784\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 179.96 MiB\n Calculator: 4.62 MiB\n Density: 2.41 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.81 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.44 MiB\n Arrays psit_nG: 0.57 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.33 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.011409 2.011409 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.011409 0.000000 2.011409 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.011409 2.011409 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.022818 0.000000 0.000000 18 0.2235\n 2. axis: yes 0.000000 4.022818 0.000000 18 0.2235\n 3. axis: yes 0.000000 0.000000 4.022818 18 0.2235\n\n Lengths: 4.022818 4.022818 4.022818\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2235\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:32:04 -14.926405\niter: 2 22:32:08 -14.931838 -2.61 -0.94\niter: 3 22:32:12 -14.936753 -2.52 -0.95\niter: 4 22:32:16 -14.929473 -3.69 -1.23\niter: 5 22:32:20 -14.930009 -5.05 -2.04\niter: 6 22:32:23 -14.930391c -4.35 -2.09\niter: 7 22:32:27 -14.930392c -6.26 -3.62\niter: 8 22:32:31 -14.930391c -8.07c -3.81\niter: 9 22:32:35 -14.930392c -8.53c -3.79\niter: 10 22:32:39 -14.930392c -10.13c -4.48c\n\nConverged after 10 iterations.\n\nDipole moment: (0.000000, 0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +16.855968\nPotential: -8.724549\nExternal: +0.000000\nXC: -22.999659\nEntropy (-ST): -0.064031\nLocal: -0.030137\nSIC: +0.000000\n--------------------------\nFree energy: -14.962408\nExtrapolated: -14.930392\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.68763 2.00000\n 0 5 5.68763 2.00000\n 0 6 5.68763 2.00000\n 0 7 12.95893 0.00000\n\n 1 4 6.63963 1.99980\n 1 5 6.63963 1.99980\n 1 6 8.05750 0.01363\n 1 7 8.05750 0.01363\n\n\nFermi level: 7.55929\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 751, 792\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 180.56 MiB\n Calculator: 4.64 MiB\n Density: 2.42 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.82 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.45 MiB\n Arrays psit_nG: 0.58 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.33 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.018227 2.018227 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.018227 0.000000 2.018227 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.018227 2.018227 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.036455 0.000000 0.000000 18 0.2242\n 2. axis: yes 0.000000 4.036455 0.000000 18 0.2242\n 3. axis: yes 0.000000 0.000000 4.036455 18 0.2242\n\n Lengths: 4.036455 4.036455 4.036455\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2242\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:32:46 -14.933780\niter: 2 22:32:50 -14.939007 -2.61 -0.94\niter: 3 22:32:54 -14.941916 -2.55 -0.95\niter: 4 22:32:59 -14.934186 -3.72 -1.23\niter: 5 22:33:03 -14.934636 -5.00 -2.05\niter: 6 22:33:07 -14.935049c -4.32 -2.10\niter: 7 22:33:11 -14.935048c -6.37 -3.46\niter: 8 22:33:15 -14.935048c -8.13c -3.80\niter: 9 22:33:19 -14.935049c -8.50c -3.76\niter: 10 22:33:23 -14.935049c -10.15c -4.48c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, 0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +15.551943\nPotential: -7.772560\nExternal: +0.000000\nXC: -22.653530\nEntropy (-ST): -0.063320\nLocal: -0.029241\nSIC: +0.000000\n--------------------------\nFree energy: -14.966709\nExtrapolated: -14.935049\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.59162 2.00000\n 0 5 5.59162 2.00000\n 0 6 5.59162 2.00000\n 0 7 12.81284 0.00000\n\n 1 4 6.54249 1.99977\n 1 5 6.54249 1.99977\n 1 6 7.96330 0.01153\n 1 7 7.96330 0.01153\n\n\nFermi level: 7.44830\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 751, 792\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 181.98 MiB\n Calculator: 4.66 MiB\n Density: 2.43 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.83 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.45 MiB\n Arrays psit_nG: 0.58 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.33 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.025000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.025000 0.000000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.025000 2.025000 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.050000 0.000000 0.000000 18 0.2250\n 2. axis: yes 0.000000 4.050000 0.000000 18 0.2250\n 3. axis: yes 0.000000 0.000000 4.050000 18 0.2250\n\n Lengths: 4.050000 4.050000 4.050000\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2250\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:33:29 -14.937999\niter: 2 22:33:33 -14.943025 -2.61 -0.94\niter: 3 22:33:37 -14.944013 -2.57 -0.95\niter: 4 22:33:42 -14.935856 -3.75 -1.24\niter: 5 22:33:46 -14.936188 -4.96 -2.05\niter: 6 22:33:49 -14.936670c -4.31 -2.12\niter: 7 22:33:53 -14.936666c -6.58 -3.23\niter: 8 22:33:57 -14.936665c -8.27c -3.81\niter: 9 22:34:01 -14.936666c -8.42c -3.71\niter: 10 22:34:05 -14.936666c -10.18c -4.51c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +14.292126\nPotential: -6.854900\nExternal: +0.000000\nXC: -22.314456\nEntropy (-ST): -0.062606\nLocal: -0.028133\nSIC: +0.000000\n--------------------------\nFree energy: -14.967970\nExtrapolated: -14.936666\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.49693 2.00000\n 0 5 5.49693 2.00000\n 0 6 5.49693 2.00000\n 0 7 12.66943 0.00000\n\n 1 4 6.44637 1.99973\n 1 5 6.44637 1.99973\n 1 6 7.87077 0.00975\n 1 7 7.87077 0.00975\n\n\nFermi level: 7.33890\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 751, 796\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 182.63 MiB\n Calculator: 4.66 MiB\n Density: 2.44 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.83 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.46 MiB\n Arrays psit_nG: 0.58 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.33 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.031728 2.031728 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.031728 0.000000 2.031728 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.031728 2.031728 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.063455 0.000000 0.000000 18 0.2257\n 2. axis: yes 0.000000 4.063455 0.000000 18 0.2257\n 3. axis: yes 0.000000 0.000000 4.063455 18 0.2257\n\n Lengths: 4.063455 4.063455 4.063455\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2257\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:34:11 -14.939033\niter: 2 22:34:15 -14.943862 -2.61 -0.94\niter: 3 22:34:19 -14.943014c -2.60 -0.95\niter: 4 22:34:23 -14.934451 -3.78 -1.24\niter: 5 22:34:27 -14.934640 -4.97 -2.06\niter: 6 22:34:32 -14.935221c -4.32 -2.15\niter: 7 22:34:35 -14.935212c -6.84 -3.06\niter: 8 22:34:40 -14.935212c -8.42c -3.80\niter: 9 22:34:44 -14.935213c -8.20c -3.64\niter: 10 22:34:48 -14.935213c -9.82c -4.52c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +13.077726\nPotential: -5.972581\nExternal: +0.000000\nXC: -21.982427\nEntropy (-ST): -0.061895\nLocal: -0.026983\nSIC: +0.000000\n--------------------------\nFree energy: -14.966160\nExtrapolated: -14.935213\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.40354 2.00000\n 0 5 5.40354 2.00000\n 0 6 5.40354 2.00000\n 0 7 12.52862 0.00000\n\n 1 4 6.35125 1.99970\n 1 5 6.35125 1.99970\n 1 6 7.77989 0.00823\n 1 7 7.77989 0.00823\n\n\nFermi level: 7.23099\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 796, 807\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 182.70 MiB\n Calculator: 4.69 MiB\n Density: 2.45 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.84 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.47 MiB\n Arrays psit_nG: 0.59 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.34 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n |Al| | \n | .---------. \n | / Al / \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.038411 2.038411 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.038411 0.000000 2.038411 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.038411 2.038411 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.076822 0.000000 0.000000 18 0.2265\n 2. axis: yes 0.000000 4.076822 0.000000 18 0.2265\n 3. axis: yes 0.000000 0.000000 4.076822 18 0.2265\n\n Lengths: 4.076822 4.076822 4.076822\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2265\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:34:54 -14.937251\niter: 2 22:34:59 -14.941885 -2.62 -0.94\niter: 3 22:35:03 -14.939271c -2.62 -0.95\niter: 4 22:35:07 -14.930329 -3.80 -1.24\niter: 5 22:35:11 -14.930379 -5.05 -2.06\niter: 6 22:35:15 -14.931060c -4.36 -2.16\niter: 7 22:35:19 -14.931044c -6.85 -2.92\niter: 8 22:35:23 -14.931044c -8.18c -3.78\niter: 9 22:35:27 -14.931045c -7.93c -3.57\niter: 10 22:35:31 -14.931045c -9.45c -4.64c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +11.900238\nPotential: -5.117966\nExternal: +0.000000\nXC: -21.656807\nEntropy (-ST): -0.061203\nLocal: -0.025909\nSIC: +0.000000\n--------------------------\nFree energy: -14.961646\nExtrapolated: -14.931045\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.31128 2.00000\n 0 5 5.31128 2.00000\n 0 6 5.31128 2.00000\n 0 7 12.39031 0.00000\n\n 1 4 6.25708 1.99966\n 1 5 6.25708 1.99966\n 1 6 7.69059 0.00695\n 1 7 7.69059 0.00695\n\n\nFermi level: 7.12468\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 799, 814\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 183.73 MiB\n Calculator: 4.71 MiB\n Density: 2.46 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.85 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.48 MiB\n Arrays psit_nG: 0.60 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.34 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n |Al| | \n | .---------. \n | / Al / \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.045051 2.045051 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.045051 0.000000 2.045051 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.045051 2.045051 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.090102 0.000000 0.000000 18 0.2272\n 2. axis: yes 0.000000 4.090102 0.000000 18 0.2272\n 3. axis: yes 0.000000 0.000000 4.090102 18 0.2272\n\n Lengths: 4.090102 4.090102 4.090102\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2272\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:35:38 -14.932645\niter: 2 22:35:43 -14.937089 -2.62 -0.94\niter: 3 22:35:47 -14.932789c -2.65 -0.95\niter: 4 22:35:51 -14.923493 -3.82 -1.25\niter: 5 22:35:55 -14.923447 -5.23 -2.07\niter: 6 22:35:59 -14.924190c -4.40 -2.16\niter: 7 22:36:03 -14.924165c -6.57 -2.79\niter: 8 22:36:07 -14.924165c -7.67c -3.77\niter: 9 22:36:11 -14.924165c -7.77c -3.50\niter: 10 22:36:14 -14.924165c -9.28c -4.80c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +10.761960\nPotential: -4.293213\nExternal: +0.000000\nXC: -21.337659\nEntropy (-ST): -0.060526\nLocal: -0.024991\nSIC: +0.000000\n--------------------------\nFree energy: -14.954428\nExtrapolated: -14.924165\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.22036 2.00000\n 0 5 5.22036 2.00000\n 0 6 5.22036 2.00000\n 0 7 12.25448 0.00000\n\n 1 4 6.16384 1.99962\n 1 5 6.16384 1.99962\n 1 6 7.60284 0.00585\n 1 7 7.60284 0.00585\n\n\nFermi level: 7.01977\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 799, 824\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 184.05 MiB\n Calculator: 4.73 MiB\n Density: 2.46 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.86 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.50 MiB\n Arrays psit_nG: 0.60 MiB\n Eigensolver: 0.24 MiB\n Projections: 0.04 MiB\n Projectors: 0.35 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n |Al| | \n | .---------. \n | / Al / \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.051648 2.051648 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.051648 0.000000 2.051648 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.051648 2.051648 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.103296 0.000000 0.000000 18 0.2280\n 2. axis: yes 0.000000 4.103296 0.000000 18 0.2280\n 3. axis: yes 0.000000 0.000000 4.103296 18 0.2280\n\n Lengths: 4.103296 4.103296 4.103296\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2280\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:36:21 -14.925350\niter: 2 22:36:25 -14.929610 -2.62 -0.94\niter: 3 22:36:30 -14.923699c -2.67 -0.95\niter: 4 22:36:33 -14.914071 -3.84 -1.25\niter: 5 22:36:37 -14.913995 -5.39 -2.07\niter: 6 22:36:41 -14.914744c -4.46 -2.14\niter: 7 22:36:45 -14.914703c -6.23 -2.67\niter: 8 22:36:49 -14.914703c -7.29 -3.73\niter: 9 22:36:53 -14.914704c -7.61c -3.42\niter: 10 22:36:57 -14.914704c -9.08c -4.77c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +9.664679\nPotential: -3.500677\nExternal: +0.000000\nXC: -21.025036\nEntropy (-ST): -0.059878\nLocal: -0.023731\nSIC: +0.000000\n--------------------------\nFree energy: -14.944642\nExtrapolated: -14.914704\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.13063 2.00000\n 0 5 5.13063 2.00000\n 0 6 5.13063 2.00000\n 0 7 12.12106 0.00000\n\n 1 4 6.07144 1.99957\n 1 5 6.07144 1.99957\n 1 6 7.51659 0.00494\n 1 7 7.51659 0.00494\n\n\nFermi level: 6.91650\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 799, 824\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 184.18 MiB\n Calculator: 4.75 MiB\n Density: 2.48 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.88 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.50 MiB\n Arrays psit_nG: 0.60 MiB\n Eigensolver: 0.24 MiB\n Projections: 0.04 MiB\n Projectors: 0.35 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n | Al | \n | .---------. \n | / All / \n |/ / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.058203 2.058203 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.058203 0.000000 2.058203 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.058203 2.058203 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.116405 0.000000 0.000000 18 0.2287\n 2. axis: yes 0.000000 4.116405 0.000000 18 0.2287\n 3. axis: yes 0.000000 0.000000 4.116405 18 0.2287\n\n Lengths: 4.116405 4.116405 4.116405\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2287\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:37:03 -14.915473\niter: 2 22:37:07 -14.919556 -2.62 -0.94\niter: 3 22:37:11 -14.912114 -2.70 -0.95\niter: 4 22:37:15 -14.902180 -3.86 -1.25\niter: 5 22:37:20 -14.902124 -5.50 -2.07\niter: 6 22:37:24 -14.902858c -4.47 -2.11\niter: 7 22:37:29 -14.902774c -5.84 -2.51\niter: 8 22:37:32 -14.902775c -6.88 -3.71\niter: 9 22:37:36 -14.902775c -7.36 -3.30\niter: 10 22:37:40 -14.902775c -8.69c -4.59c\n\nConverged after 10 iterations.\n\nDipole moment: (0.000000, -0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +8.611038\nPotential: -2.741920\nExternal: +0.000000\nXC: -20.719117\nEntropy (-ST): -0.059259\nLocal: -0.023145\nSIC: +0.000000\n--------------------------\nFree energy: -14.932404\nExtrapolated: -14.902775\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.04210 2.00000\n 0 5 5.04210 2.00000\n 0 6 5.04210 2.00000\n 0 7 11.98998 0.00000\n\n 1 4 5.97999 1.99953\n 1 5 5.97999 1.99953\n 1 6 7.43183 0.00417\n 1 7 7.43183 0.00417\n\n\nFermi level: 6.81475\n\nNo gap\n","output_type":"stream"},{"execution_count":2,"output_type":"execute_result","data":{"text/plain":"{'energy': {0.95: -14.895378072812221,\n 0.96: -14.910819737644692,\n 0.97: -14.922307241109358,\n 0.98: -14.93039227930928,\n 0.99: -14.935048569951459,\n 1.0: -14.93666639635226,\n 1.01: -14.935212782113831,\n 1.02: -14.931045138828088,\n 1.03: -14.924165445694268,\n 1.04: -14.914703573990083,\n 1.05: -14.902774559119468}}"},"metadata":{}}],"id":"374b84ab-1471-481a-ae2a-f04cca2bf331"},{"cell_type":"markdown","source":"In analogy to the `task_dict` which defines the tasks to be executed by the simulation code the `result_dict` summarizes \nthe results of the calculations. In this case the energies calculated for the specific strains. By ordering both the \n`task_dict` and the `result_dict` with the same labels, the `EnergyVolumeCurveWorkflow` object is able to match the \ncalculation results to the corresponding structure. Finally, in the third step the `analyse_structures()` function takes\nthe `result_dict` as an input and fits the Equation of State with the fitting parameters defined in the first step:","metadata":{},"id":"61113aa0-8b91-4867-bee2-47b5b7d72a0d"},{"cell_type":"code","source":"fit_dict = workflow.analyse_structures(output_dict=result_dict)\nfit_dict","metadata":{"trusted":true},"execution_count":3,"outputs":[{"execution_count":3,"output_type":"execute_result","data":{"text/plain":"{'b_prime_eq': 4.453836548379018,\n 'bulkmodul_eq': 72.38919826524031,\n 'volume_eq': 66.44252286130995,\n 'energy_eq': -14.936703222033056,\n 'fit_dict': {'fit_type': 'polynomial',\n 'least_square_error': 4.432974567361701e-09,\n 'poly_fit': array([-9.30297838e-05, 2.19434659e-02, -1.68388816e+00, 2.73605421e+01]),\n 'fit_order': 3},\n 'energy': [-14.895378072812221,\n -14.910819737644692,\n -14.922307241109358,\n -14.93039227930928,\n -14.935048569951459,\n -14.93666639635226,\n -14.935212782113831,\n -14.931045138828088,\n -14.924165445694268,\n -14.914703573990083,\n -14.902774559119468],\n 'volume': [63.10861874999998,\n 63.77291999999998,\n 64.43722124999998,\n 65.1015225,\n 65.76582375000004,\n 66.43012500000002,\n 67.09442624999994,\n 67.75872750000002,\n 68.42302874999999,\n 69.08732999999997,\n 69.75163125000002]}"},"metadata":{}}],"id":"54b0d2c8-f8c7-4b9a-85c9-303a04976dfc"},{"cell_type":"markdown","source":"The bulk modulus for Aluminium is calculated using the [GPAW](https://wiki.fysik.dtu.dk/gpaw/) simulation code by fitting\nthe Equation of State with a third order polynomial over a volume range of +/-5% to be 72.3GPa. ","metadata":{},"id":"4c7eeb29-2d1f-44c2-8fcb-09be2bd5f717"},{"cell_type":"markdown","source":"## Elastic Matrix\nAn alternative approach to calculate the bulk modulus is based on the relation `B = (1/3) (C11 + 2 C12 )`. The bulk\nmodulus can be calculated based on the sum of the first elastic constant `C11` and twice the second elastic constant `C12`\ndivided by there. ","metadata":{},"id":"39b116c1-65fb-4c8b-a80e-b8f331012849"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators.ase import evaluate_with_ase\nfrom atomistics.workflows.elastic.workflow import ElasticMatrixWorkflow\nfrom gpaw import GPAW, PW\n\nworkflow = ElasticMatrixWorkflow(\n structure=bulk(\"Al\", a=4.05, cubic=True),\n num_of_point=5,\n eps_range=0.05,\n sqrt_eta=True,\n fit_order=2\n)\ntask_dict = workflow.generate_structures()\ntask_dict","metadata":{"trusted":true},"execution_count":4,"outputs":[{"execution_count":4,"output_type":"execute_result","data":{"text/plain":"{'calc_energy': OrderedDict([('s_e_0',\n Atoms(symbols='Al4', pbc=True, cell=[4.05, 4.05, 4.05])),\n ('s_01_e_m0_05000',\n Atoms(symbols='Al4', pbc=True, cell=[3.8421673571095107, 3.8421673571095107, 3.8421673571095107])),\n ('s_01_e_m0_02500',\n Atoms(symbols='Al4', pbc=True, cell=[3.94745170964797, 3.94745170964797, 3.94745170964797])),\n ('s_01_e_0_02500',\n Atoms(symbols='Al4', pbc=True, cell=[4.150015060213919, 4.150015060213919, 4.150015060213919])),\n ('s_01_e_0_05000',\n Atoms(symbols='Al4', pbc=True, cell=[4.247675835085893, 4.247675835085893, 4.247675835085893])),\n ('s_08_e_m0_05000',\n Atoms(symbols='Al4', pbc=True, cell=[3.8421673571095107, 3.8421673571095107, 4.05])),\n ('s_08_e_m0_02500',\n Atoms(symbols='Al4', pbc=True, cell=[3.94745170964797, 3.94745170964797, 4.05])),\n ('s_08_e_0_02500',\n Atoms(symbols='Al4', pbc=True, cell=[4.150015060213919, 4.150015060213919, 4.05])),\n ('s_08_e_0_05000',\n Atoms(symbols='Al4', pbc=True, cell=[4.247675835085893, 4.247675835085893, 4.05])),\n ('s_23_e_m0_05000',\n Atoms(symbols='Al4', pbc=True, cell=[[4.039260597921188, -0.2084152371679185, -0.2084152371679185], [-0.2084152371679185, 4.039260597921188, -0.2084152371679185], [-0.2084152371679185, -0.2084152371679185, 4.039260597921188]])),\n ('s_23_e_m0_02500',\n Atoms(symbols='Al4', pbc=True, cell=[[4.047399159178924, -0.1026159010347065, -0.1026159010347065], [-0.1026159010347065, 4.047399159178924, -0.1026159010347065], [-0.1026159010347065, -0.1026159010347065, 4.047399159178924]])),\n ('s_23_e_0_02500',\n Atoms(symbols='Al4', pbc=True, cell=[[4.047526418127057, 0.1000747084794181, 0.1000747084794181], [0.1000747084794181, 4.047526418127057, 0.1000747084794181], [0.1000747084794181, 0.1000747084794181, 4.047526418127057]])),\n ('s_23_e_0_05000',\n Atoms(symbols='Al4', pbc=True, cell=[[4.0402958099962145, 0.19812845289162093, 0.19812845289162093], [0.19812845289162093, 4.0402958099962145, 0.19812845289162093], [0.19812845289162093, 0.19812845289162093, 4.0402958099962145]]))])}"},"metadata":{}}],"id":"19aae7eb-7fa2-4cb0-b109-d2bad7aedc39"},{"cell_type":"markdown","source":"In analogy to the example with the `EnergyVolumeCurveWorkflow` above, the `ElasticMatrixWorkflow` is initialized with all\nthe parameters required to generate the atomistic structures and afterwards fit the resulting energies. By calling the\n`generate_structures()` function the task dictionary `task_dict` is generated. The task dictionary specifies that the \nenergy should be calculated for a total of thirteen structures with different displacements. In the second step the \nstructures are again evaluated with the [GPAW](https://wiki.fysik.dtu.dk/gpaw/) simulation code: ","metadata":{},"id":"98d423dc-db2e-4b3d-a336-031d48e3098d"},{"cell_type":"code","source":"result_dict = evaluate_with_ase(\n task_dict=task_dict,\n ase_calculator=GPAW(\n xc=\"PBE\",\n mode=PW(300),\n kpts=(3, 3, 3)\n )\n)\nresult_dict","metadata":{"trusted":true},"execution_count":5,"outputs":[{"name":"stdout","text":"\n ___ ___ ___ _ _ _ \n | | |_ | | | | \n | | | | | . | | | | \n |__ | _|___|_____| 24.1.0\n |___|_| \n\nUser: jovyan@jupyter-pyiron-2datomistics-2dco7ko9rv\nDate: Wed May 1 22:37:40 2024\nArch: x86_64\nPid: 594\nCWD: /home/jovyan\nPython: 3.10.12\ngpaw: /srv/conda/envs/notebook/lib/python3.10/site-packages/gpaw\n_gpaw: /srv/conda/envs/notebook/lib/python3.10/site-packages/\n _gpaw.cpython-310-x86_64-linux-gnu.so\nase: /srv/conda/envs/notebook/lib/python3.10/site-packages/ase (version 3.22.1)\nnumpy: /srv/conda/envs/notebook/lib/python3.10/site-packages/numpy (version 1.26.4)\nscipy: /srv/conda/envs/notebook/lib/python3.10/site-packages/scipy (version 1.13.0)\nlibxc: 6.2.2\nunits: Angstrom and eV\ncores: 1\nOpenMP: True\nOMP_NUM_THREADS: 1\n\nInput parameters:\n kpts: [3 3 3]\n mode: {ecut: 300.0,\n name: pw}\n xc: PBE\n\nSystem changes: positions, numbers, cell, pbc, initial_charges, initial_magmoms \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 751, 792\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 186.33 MiB\n Calculator: 4.66 MiB\n Density: 2.43 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.83 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.45 MiB\n Arrays psit_nG: 0.58 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.33 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.025000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.025000 0.000000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.025000 2.025000 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.050000 0.000000 0.000000 18 0.2250\n 2. axis: yes 0.000000 4.050000 0.000000 18 0.2250\n 3. axis: yes 0.000000 0.000000 4.050000 18 0.2250\n\n Lengths: 4.050000 4.050000 4.050000\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2250\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:37:46 -14.937999\niter: 2 22:37:51 -14.943025 -2.61 -0.94\niter: 3 22:37:55 -14.944013 -2.57 -0.95\niter: 4 22:37:59 -14.935856 -3.75 -1.24\niter: 5 22:38:03 -14.936188 -4.96 -2.05\niter: 6 22:38:07 -14.936670c -4.31 -2.12\niter: 7 22:38:11 -14.936666c -6.58 -3.23\niter: 8 22:38:15 -14.936665c -8.27c -3.81\niter: 9 22:38:19 -14.936666c -8.42c -3.71\niter: 10 22:38:24 -14.936666c -10.18c -4.51c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +14.292126\nPotential: -6.854900\nExternal: +0.000000\nXC: -22.314456\nEntropy (-ST): -0.062606\nLocal: -0.028133\nSIC: +0.000000\n--------------------------\nFree energy: -14.967970\nExtrapolated: -14.936666\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.49693 2.00000\n 0 5 5.49693 2.00000\n 0 6 5.49693 2.00000\n 0 7 12.66943 0.00000\n\n 1 4 6.44637 1.99973\n 1 5 6.44637 1.99973\n 1 6 7.87077 0.00975\n 1 7 7.87077 0.00975\n\n\nFermi level: 7.33890\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 658, 691\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 16*16*16 grid\n Fine grid: 32*32*32 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 32*32*32 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 193.62 MiB\n Calculator: 3.61 MiB\n Density: 1.84 MiB\n Arrays: 0.81 MiB\n Localized functions: 0.71 MiB\n Mixer: 0.31 MiB\n Hamiltonian: 0.55 MiB\n Arrays: 0.53 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.01 MiB\n Wavefunctions: 1.23 MiB\n Arrays psit_nG: 0.51 MiB\n Eigensolver: 0.20 MiB\n Projections: 0.04 MiB\n Projectors: 0.29 MiB\n PW-descriptor: 0.20 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .--------. \n /| | \n * | | \n |Al | \n | | | \n | .-Al-----. \n |/ Al / \n Al-------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 1.921084 1.921084 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.921084 0.000000 1.921084 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.921084 1.921084 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 3.842167 0.000000 0.000000 16 0.2401\n 2. axis: yes 0.000000 3.842167 0.000000 16 0.2401\n 3. axis: yes 0.000000 0.000000 3.842167 16 0.2401\n\n Lengths: 3.842167 3.842167 3.842167\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2401\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:38:29 -14.458328\niter: 2 22:38:33 -14.467077 -2.57 -0.94\niter: 3 22:38:36 -14.505006 -2.15 -0.96\niter: 4 22:38:40 -14.507040 -3.05 -1.16\niter: 5 22:38:44 -14.508034c -5.81 -1.94\niter: 6 22:38:47 -14.509159c -4.57 -2.12\niter: 7 22:38:51 -14.509154c -6.78 -2.83\niter: 8 22:38:55 -14.509155c -8.99c -3.51\niter: 9 22:38:59 -14.509158c -7.43c -3.62\niter: 10 22:39:02 -14.509158c -9.08c -4.97c\n\nConverged after 10 iterations.\n\nDipole moment: (0.000000, 0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +38.117828\nPotential: -24.459808\nExternal: +0.000000\nXC: -28.083947\nEntropy (-ST): -0.069078\nLocal: -0.048692\nSIC: +0.000000\n--------------------------\nFree energy: -14.543697\nExtrapolated: -14.509158\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 7.02831 2.00000\n 0 5 7.02831 2.00000\n 0 6 7.02831 2.00000\n 0 7 15.06935 0.00000\n\n 1 4 7.97110 1.99998\n 1 5 7.97110 1.99998\n 1 6 9.41360 0.08491\n 1 7 9.41360 0.08491\n\n\nFermi level: 9.10201\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 717, 739\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 16*16*16 grid\n Fine grid: 32*32*32 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 32*32*32 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 193.62 MiB\n Calculator: 3.74 MiB\n Density: 1.89 MiB\n Arrays: 0.81 MiB\n Localized functions: 0.77 MiB\n Mixer: 0.31 MiB\n Hamiltonian: 0.55 MiB\n Arrays: 0.53 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.31 MiB\n Arrays psit_nG: 0.54 MiB\n Eigensolver: 0.21 MiB\n Projections: 0.04 MiB\n Projectors: 0.31 MiB\n PW-descriptor: 0.20 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | Al | \n | .---------. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 1.973726 1.973726 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.973726 0.000000 1.973726 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.973726 1.973726 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 3.947452 0.000000 0.000000 16 0.2467\n 2. axis: yes 0.000000 3.947452 0.000000 16 0.2467\n 3. axis: yes 0.000000 0.000000 3.947452 16 0.2467\n\n Lengths: 3.947452 3.947452 3.947452\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2467\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:39:08 -14.820923\niter: 2 22:39:13 -14.827577 -2.60 -0.94\niter: 3 22:39:16 -14.844992 -2.37 -0.96\niter: 4 22:39:20 -14.840675 -3.45 -1.20\niter: 5 22:39:26 -14.841471c -5.48 -2.00\niter: 6 22:39:31 -14.841983c -4.48 -2.09\niter: 7 22:39:35 -14.841981c -6.53 -3.59\niter: 8 22:39:39 -14.841981c -8.15c -3.79\niter: 9 22:39:44 -14.841982c -8.25c -3.82\niter: 10 22:39:48 -14.841982c -9.93c -4.59c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, 0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +24.783564\nPotential: -14.549751\nExternal: +0.000000\nXC: -25.004962\nEntropy (-ST): -0.067471\nLocal: -0.037099\nSIC: +0.000000\n--------------------------\nFree energy: -14.875718\nExtrapolated: -14.841982\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 6.23092 2.00000\n 0 5 6.23092 2.00000\n 0 6 6.23092 2.00000\n 0 7 13.79846 0.00000\n\n 1 4 7.18413 1.99991\n 1 5 7.18413 1.99991\n 1 6 8.59802 0.03225\n 1 7 8.59802 0.03225\n\n\nFermi level: 8.18692\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 836, 856\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 195.04 MiB\n Calculator: 4.81 MiB\n Density: 2.49 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.89 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.55 MiB\n Arrays psit_nG: 0.63 MiB\n Eigensolver: 0.24 MiB\n Projections: 0.04 MiB\n Projectors: 0.36 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n | Al | \n | .-Al------. \n | / Al / \n |/ / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.075008 2.075008 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.075008 0.000000 2.075008 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.075008 2.075008 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.150015 0.000000 0.000000 18 0.2306\n 2. axis: yes 0.000000 4.150015 0.000000 18 0.2306\n 3. axis: yes 0.000000 0.000000 4.150015 18 0.2306\n\n Lengths: 4.150015 4.150015 4.150015\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2306\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:39:55 -14.879464\niter: 2 22:39:59 -14.883109 -2.62 -0.94\niter: 3 22:40:03 -14.871975 -2.76 -0.96\niter: 4 22:40:08 -14.861344 -3.91 -1.26\niter: 5 22:40:13 -14.861380 -5.65 -2.08\niter: 6 22:40:18 -14.861874c -4.97 -2.07\niter: 7 22:40:21 -14.861850c -5.36 -2.63\niter: 8 22:40:25 -14.861849c -7.28 -3.56\niter: 9 22:40:30 -14.861852c -6.79 -3.44\niter: 10 22:40:35 -14.861852c -7.30 -3.41\niter: 11 22:40:40 -14.861852c -9.44c -3.85\niter: 12 22:40:45 -14.861851c -8.74c -4.03c\n\nConverged after 12 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +6.024647\nPotential: -0.884511\nExternal: +0.000000\nXC: -19.951921\nEntropy (-ST): -0.057798\nLocal: -0.021168\nSIC: +0.000000\n--------------------------\nFree energy: -14.890750\nExtrapolated: -14.861851\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 4.81760 2.00000\n 0 5 4.81760 2.00000\n 0 6 4.81760 2.00000\n 0 7 11.66042 0.00000\n\n 1 4 5.74673 1.99940\n 1 5 5.74673 1.99940\n 1 6 7.21857 0.00269\n 1 7 7.21857 0.00269\n\n\nFermi level: 6.55769\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 884, 922\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 195.85 MiB\n Calculator: 4.97 MiB\n Density: 2.55 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.95 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.78 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.64 MiB\n Arrays psit_nG: 0.68 MiB\n Eigensolver: 0.26 MiB\n Projections: 0.04 MiB\n Projectors: 0.38 MiB\n PW-descriptor: 0.28 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n | Al | \n | .---------. \n | / All / \n |/ / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.123838 2.123838 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.123838 0.000000 2.123838 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.123838 2.123838 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.247676 0.000000 0.000000 18 0.2360\n 2. axis: yes 0.000000 4.247676 0.000000 18 0.2360\n 3. axis: yes 0.000000 0.000000 4.247676 18 0.2360\n\n Lengths: 4.247676 4.247676 4.247676\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2360\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:40:52 -14.696924\niter: 2 22:40:57 -14.699422 -2.64 -0.94\niter: 3 22:41:02 -14.679770 -2.91 -0.96\niter: 4 22:41:06 -14.667487 -4.04 -1.28\niter: 5 22:41:10 -14.667584 -5.99 -2.08\niter: 6 22:41:15 -14.667794c -4.99 -2.08\niter: 7 22:41:19 -14.667795c -6.56 -3.69\niter: 8 22:41:24 -14.667794c -7.75c -3.59\niter: 9 22:41:28 -14.667795c -8.79c -3.81\niter: 10 22:41:33 -14.667795c -9.67c -4.06c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, 0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: -0.441729\nPotential: +3.686595\nExternal: +0.000000\nXC: -17.870816\nEntropy (-ST): -0.054761\nLocal: -0.014463\nSIC: +0.000000\n--------------------------\nFree energy: -14.695175\nExtrapolated: -14.667795\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 4.18694 2.00000\n 0 5 4.18694 2.00000\n 0 6 4.18694 2.00000\n 0 7 10.75420 0.00000\n\n 1 4 5.07835 1.99906\n 1 5 5.07835 1.99906\n 1 6 6.63071 0.00077\n 1 7 6.63071 0.00077\n\n\nFermi level: 5.84459\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 16\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.00000000 0.00000000 0.33333333 2/27\n 2: 0.33333333 0.00000000 0.00000000 4/27\n 3: 0.33333333 0.00000000 0.33333333 8/27\n 4: 0.33333333 0.33333333 0.00000000 4/27\n 5: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 694, 708\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 16*16*18 grid\n Fine grid: 32*32*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 32*32*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 196.86 MiB\n Calculator: 4.36 MiB\n Density: 2.01 MiB\n Arrays: 0.91 MiB\n Localized functions: 0.75 MiB\n Mixer: 0.35 MiB\n Hamiltonian: 0.61 MiB\n Arrays: 0.60 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.73 MiB\n Arrays psit_nG: 0.78 MiB\n Eigensolver: 0.21 MiB\n Projections: 0.06 MiB\n Projectors: 0.45 MiB\n PW-descriptor: 0.24 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .--------. \n /| | \n * | | \n |Al | \n | | | \n | .-Al-----. \n |/ Al / \n Al-------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 1.921084 2.025000 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.921084 0.000000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.921084 1.921084 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 3.842167 0.000000 0.000000 16 0.2401\n 2. axis: yes 0.000000 3.842167 0.000000 16 0.2401\n 3. axis: yes 0.000000 0.000000 4.050000 18 0.2250\n\n Lengths: 3.842167 3.842167 4.050000\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2350\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:41:40 -14.732895\niter: 2 22:41:45 -14.740004 -2.60 -0.94\niter: 3 22:41:51 -14.762942 -2.29 -0.96\niter: 4 22:41:56 -14.760523 -3.30 -1.19\niter: 5 22:42:01 -14.760822c -5.55 -2.01\niter: 6 22:42:06 -14.761985c -4.57 -2.13\niter: 7 22:42:12 -14.761976c -6.98 -3.27\niter: 8 22:42:17 -14.761980c -7.54c -3.32\niter: 9 22:42:22 -14.761985c -7.48c -3.59\niter: 10 22:42:27 -14.761985c -9.23c -4.68c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +29.946922\nPotential: -18.554760\nExternal: +0.000000\nXC: -26.098780\nEntropy (-ST): -0.028997\nLocal: -0.040868\nSIC: +0.000000\n--------------------------\nFree energy: -14.776483\nExtrapolated: -14.761985\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.78601 2.00000\n 0 5 6.87607 2.00000\n 0 6 6.87607 2.00000\n 0 7 13.73921 0.00000\n\n 1 4 7.74692 1.97199\n 1 5 7.74692 1.97198\n 1 6 8.89364 0.00147\n 1 7 8.89364 0.00147\n\n\nFermi level: 8.17232\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 16\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.00000000 0.00000000 0.33333333 2/27\n 2: 0.33333333 0.00000000 0.00000000 4/27\n 3: 0.33333333 0.00000000 0.33333333 8/27\n 4: 0.33333333 0.33333333 0.00000000 4/27\n 5: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 737, 756\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 16*16*18 grid\n Fine grid: 32*32*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 32*32*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 196.86 MiB\n Calculator: 4.50 MiB\n Density: 2.05 MiB\n Arrays: 0.91 MiB\n Localized functions: 0.79 MiB\n Mixer: 0.35 MiB\n Hamiltonian: 0.61 MiB\n Arrays: 0.60 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.83 MiB\n Arrays psit_nG: 0.83 MiB\n Eigensolver: 0.22 MiB\n Projections: 0.06 MiB\n Projectors: 0.48 MiB\n PW-descriptor: 0.24 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 1.973726 2.025000 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.973726 0.000000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.973726 1.973726 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 3.947452 0.000000 0.000000 16 0.2467\n 2. axis: yes 0.000000 3.947452 0.000000 16 0.2467\n 3. axis: yes 0.000000 0.000000 4.050000 18 0.2250\n\n Lengths: 3.947452 3.947452 4.050000\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2393\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:42:34 -14.903323\niter: 2 22:42:39 -14.909242 -2.61 -0.94\niter: 3 22:42:43 -14.919947 -2.44 -0.95\niter: 4 22:42:48 -14.914320 -3.57 -1.22\niter: 5 22:42:53 -14.914598c -5.26 -2.03\niter: 6 22:42:58 -14.915408c -4.55 -2.15\niter: 7 22:43:03 -14.915408c -6.67 -3.36\niter: 8 22:43:08 -14.915408c -7.91c -3.62\niter: 9 22:43:13 -14.915410c -7.98c -3.72\niter: 10 22:43:18 -14.915410c -9.88c -4.70c\n\nConverged after 10 iterations.\n\nDipole moment: (0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +21.332754\nPotential: -12.094956\nExternal: +0.000000\nXC: -24.099721\nEntropy (-ST): -0.039257\nLocal: -0.033858\nSIC: +0.000000\n--------------------------\nFree energy: -14.935039\nExtrapolated: -14.915410\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.63543 2.00000\n 0 5 6.16057 2.00000\n 0 6 6.16057 2.00000\n 0 7 13.17416 0.00000\n\n 1 4 7.07724 1.99853\n 1 5 7.07724 1.99853\n 1 6 8.35185 0.00789\n 1 7 8.35185 0.00789\n\n\nFermi level: 7.79870\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 16\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.00000000 0.00000000 0.33333333 2/27\n 2: 0.33333333 0.00000000 0.00000000 4/27\n 3: 0.33333333 0.00000000 0.33333333 8/27\n 4: 0.33333333 0.33333333 0.00000000 4/27\n 5: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 807, 832\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 196.86 MiB\n Calculator: 5.28 MiB\n Density: 2.47 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.87 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 2.03 MiB\n Arrays psit_nG: 0.91 MiB\n Eigensolver: 0.24 MiB\n Projections: 0.06 MiB\n Projectors: 0.53 MiB\n PW-descriptor: 0.30 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n | Al | \n | .---------. \n | / AlAl / \n |/ / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.075008 2.025000 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.075008 0.000000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.075008 2.075008 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.150015 0.000000 0.000000 18 0.2306\n 2. axis: yes 0.000000 4.150015 0.000000 18 0.2306\n 3. axis: yes 0.000000 0.000000 4.050000 18 0.2250\n\n Lengths: 4.150015 4.150015 4.050000\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2287\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:43:26 -14.919077\niter: 2 22:43:31 -14.923047 -2.62 -0.94\niter: 3 22:43:37 -14.915401 -2.70 -0.95\niter: 4 22:43:42 -14.905669 -3.88 -1.26\niter: 5 22:43:48 -14.905607 -5.49 -2.08\niter: 6 22:43:54 -14.906325c -4.49 -2.12\niter: 7 22:44:00 -14.906256c -5.95 -2.57\niter: 8 22:44:06 -14.906257c -6.95 -3.71\niter: 9 22:44:12 -14.906257c -7.39 -3.31\niter: 10 22:44:19 -14.906257c -8.75c -4.59c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, 0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +8.698013\nPotential: -2.831815\nExternal: +0.000000\nXC: -20.724898\nEntropy (-ST): -0.048849\nLocal: -0.023133\nSIC: +0.000000\n--------------------------\nFree energy: -14.930681\nExtrapolated: -14.906257\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 4.87930 2.00000\n 0 5 4.87930 2.00000\n 0 6 5.37182 2.00000\n 0 7 11.70552 0.00000\n\n 1 4 5.84939 1.99972\n 1 5 5.84939 1.99972\n 1 6 7.44240 0.00171\n 1 7 7.44240 0.00171\n\n\nFermi level: 6.73590\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 16\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.00000000 0.00000000 0.33333333 2/27\n 2: 0.33333333 0.00000000 0.00000000 4/27\n 3: 0.33333333 0.00000000 0.33333333 8/27\n 4: 0.33333333 0.33333333 0.00000000 4/27\n 5: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 848, 872\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 198.45 MiB\n Calculator: 5.40 MiB\n Density: 2.51 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.91 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.78 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 2.12 MiB\n Arrays psit_nG: 0.96 MiB\n Eigensolver: 0.25 MiB\n Projections: 0.06 MiB\n Projectors: 0.55 MiB\n PW-descriptor: 0.30 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n | Al | \n | .---------. \n | / All / \n |/ / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.123838 2.025000 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.123838 0.000000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.123838 2.123838 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.247676 0.000000 0.000000 18 0.2360\n 2. axis: yes 0.000000 4.247676 0.000000 18 0.2360\n 3. axis: yes 0.000000 0.000000 4.050000 18 0.2250\n\n Lengths: 4.247676 4.247676 4.050000\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2323\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:44:29 -14.812413\niter: 2 22:44:36 -14.815910 -2.62 -0.94\niter: 3 22:44:42 -14.803239 -2.79 -0.96\niter: 4 22:44:48 -14.791922 -3.92 -1.26\niter: 5 22:44:55 -14.792019 -5.77 -2.10\niter: 6 22:45:01 -14.792358c -4.93 -2.07\niter: 7 22:45:06 -14.792358c -6.44 -3.28\niter: 8 22:45:12 -14.792357c -8.08c -3.65\niter: 9 22:45:18 -14.792358c -7.22 -3.66\niter: 10 22:45:24 -14.792358c -8.01c -3.64\niter: 11 22:45:30 -14.792358c -9.38c -4.32c\n\nConverged after 11 iterations.\n\nDipole moment: (-0.000000, 0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +4.244555\nPotential: +0.324641\nExternal: +0.000000\nXC: -19.309666\nEntropy (-ST): -0.064765\nLocal: -0.019506\nSIC: +0.000000\n--------------------------\nFree energy: -14.824741\nExtrapolated: -14.792358\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 4.30602 2.00000\n 0 5 4.30602 2.00000\n 0 6 5.25459 1.99983\n 0 7 10.83679 0.00000\n\n 1 4 5.28608 1.99977\n 1 5 5.28608 1.99977\n 1 6 7.05846 0.00035\n 1 7 7.05846 0.00035\n\n\nFermi level: 6.19264\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 12\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 0 1) ( 1 0 0) ( 0 1 0)\n ( 0 0 1) ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 1 0) ( 1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 -1 0) (-1 0 0) ( 0 0 -1) (-1 0 0) ( 0 0 -1) ( 0 -1 0)\n (-1 0 0) ( 0 -1 0) (-1 0 0) ( 0 0 -1) ( 0 -1 0) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 -0.33333333 6/27\n 2: 0.33333333 0.00000000 0.00000000 6/27\n 3: 0.33333333 0.33333333 -0.33333333 6/27\n 4: 0.33333333 0.33333333 0.00000000 6/27\n 5: 0.33333333 0.33333333 0.33333333 2/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 762, 774\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 198.71 MiB\n Calculator: 5.10 MiB\n Density: 2.41 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.81 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.92 MiB\n Arrays psit_nG: 0.85 MiB\n Eigensolver: 0.22 MiB\n Projections: 0.06 MiB\n Projectors: 0.49 MiB\n PW-descriptor: 0.29 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n \n \n \n \n Al \n Al \n \n Al \n Al \n \n \n \n \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al -0.208415 1.915423 1.915423 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.915423 -0.208415 1.915423 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.915423 1.915423 -0.208415 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.039261 -0.208415 -0.208415 18 0.2225\n 2. axis: yes -0.208415 4.039261 -0.208415 18 0.2225\n 3. axis: yes -0.208415 -0.208415 4.039261 18 0.2225\n\n Lengths: 4.050000 4.050000 4.050000\n Angles: 95.739170 95.739170 95.739170\n\nEffective grid spacing dv^(1/3) = 0.2238\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:45:39 -14.253273\niter: 2 22:45:44 -14.261390 -2.56 -0.94\niter: 3 22:45:49 -14.277583 -2.52 -0.96\niter: 4 22:45:56 -14.275510 -3.84 -1.28\niter: 5 22:46:02 -14.275479c -5.56 -2.24\niter: 6 22:46:07 -14.276006c -4.67 -2.26\niter: 7 22:46:14 -14.276016c -7.21 -2.90\niter: 8 22:46:19 -14.276022c -6.81 -3.39\niter: 9 22:46:25 -14.276021c -8.57c -3.60\niter: 10 22:46:31 -14.276021c -10.57c -4.52c\n\nConverged after 10 iterations.\n\nDipole moment: (0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +22.369503\nPotential: -13.123187\nExternal: +0.000000\nXC: -23.447226\nEntropy (-ST): -0.086104\nLocal: -0.032058\nSIC: +0.000000\n--------------------------\nFree energy: -14.319073\nExtrapolated: -14.276021\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.74742 2.00000\n 0 5 5.74742 2.00000\n 0 6 5.74742 2.00000\n 0 7 11.05858 0.00000\n\n 1 4 6.01298 1.99996\n 1 5 7.51707 0.02779\n 1 6 8.20211 0.00003\n 1 7 8.20211 0.00003\n\n\nFermi level: 7.09085\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 12\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 0 1) ( 1 0 0) ( 0 1 0)\n ( 0 0 1) ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 1 0) ( 1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 -1 0) (-1 0 0) ( 0 0 -1) (-1 0 0) ( 0 0 -1) ( 0 -1 0)\n (-1 0 0) ( 0 -1 0) (-1 0 0) ( 0 0 -1) ( 0 -1 0) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 -0.33333333 6/27\n 2: 0.33333333 0.00000000 0.00000000 6/27\n 3: 0.33333333 0.33333333 -0.33333333 6/27\n 4: 0.33333333 0.33333333 0.00000000 6/27\n 5: 0.33333333 0.33333333 0.33333333 2/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 776, 786\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 198.74 MiB\n Calculator: 5.14 MiB\n Density: 2.43 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.83 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.94 MiB\n Arrays psit_nG: 0.86 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.06 MiB\n Projectors: 0.50 MiB\n PW-descriptor: 0.29 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n \n \n \n \n Al \n Al \n Al \n Al \n \n \n \n \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al -0.102616 1.972392 1.972392 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.972392 -0.102616 1.972392 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.972392 1.972392 -0.102616 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.047399 -0.102616 -0.102616 18 0.2244\n 2. axis: yes -0.102616 4.047399 -0.102616 18 0.2244\n 3. axis: yes -0.102616 -0.102616 4.047399 18 0.2244\n\n Lengths: 4.050000 4.050000 4.050000\n Angles: 92.865984 92.865984 92.865984\n\nEffective grid spacing dv^(1/3) = 0.2247\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:46:40 -14.825070\niter: 2 22:46:46 -14.830281 -2.61 -0.94\niter: 3 22:46:51 -14.834036 -2.59 -0.95\niter: 4 22:46:56 -14.827853 -3.93 -1.28\niter: 5 22:47:01 -14.827824 -5.51 -2.13\niter: 6 22:47:06 -14.828567c -4.62 -2.20\niter: 7 22:47:11 -14.828567c -7.14 -3.39\niter: 8 22:47:16 -14.828567c -7.99c -3.75\niter: 9 22:47:21 -14.828566c -8.51c -3.64\niter: 10 22:47:27 -14.828566c -10.22c -4.33c\n\nConverged after 10 iterations.\n\nDipole moment: (0.000000, 0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +15.802906\nPotential: -8.007940\nExternal: +0.000000\nXC: -22.569922\nEntropy (-ST): -0.048849\nLocal: -0.029186\nSIC: +0.000000\n--------------------------\nFree energy: -14.852991\nExtrapolated: -14.828566\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.55442 2.00000\n 0 5 5.55442 2.00000\n 0 6 5.55442 2.00000\n 0 7 11.81924 0.00000\n\n 1 4 5.97050 1.99999\n 1 5 7.42040 0.20799\n 1 6 8.63723 0.00000\n 1 7 8.63723 0.00000\n\n\nFermi level: 7.20504\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 12\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 0 1) ( 1 0 0) ( 0 1 0)\n ( 0 0 1) ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 1 0) ( 1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 -1 0) (-1 0 0) ( 0 0 -1) (-1 0 0) ( 0 0 -1) ( 0 -1 0)\n (-1 0 0) ( 0 -1 0) (-1 0 0) ( 0 0 -1) ( 0 -1 0) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 -0.33333333 6/27\n 2: 0.33333333 0.00000000 0.00000000 6/27\n 3: 0.33333333 0.33333333 -0.33333333 6/27\n 4: 0.33333333 0.33333333 0.00000000 6/27\n 5: 0.33333333 0.33333333 0.33333333 2/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 769, 788\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 199.47 MiB\n Calculator: 5.15 MiB\n Density: 2.43 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.83 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.94 MiB\n Arrays psit_nG: 0.87 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.06 MiB\n Projectors: 0.50 MiB\n PW-descriptor: 0.29 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n \n \n \n \n Al \n Al \n Al \n Al \n \n \n \n \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.100075 2.073801 2.073801 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.073801 0.100075 2.073801 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.073801 2.073801 0.100075 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.047526 0.100075 0.100075 18 0.2245\n 2. axis: yes 0.100075 4.047526 0.100075 18 0.2245\n 3. axis: yes 0.100075 0.100075 4.047526 18 0.2245\n\n Lengths: 4.050000 4.050000 4.050000\n Angles: 87.134016 87.134016 87.134016\n\nEffective grid spacing dv^(1/3) = 0.2247\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:47:35 -14.919271\niter: 2 22:47:40 -14.924183 -2.61 -0.93\niter: 3 22:47:45 -14.925894 -2.58 -0.95\niter: 4 22:47:51 -14.918258 -3.85 -1.27\niter: 5 22:47:56 -14.918454 -5.54 -2.06\niter: 6 22:48:01 -14.919068c -4.75 -2.00\niter: 7 22:48:06 -14.919062c -6.59 -3.08\niter: 8 22:48:12 -14.919072c -6.40 -3.13\niter: 9 22:48:18 -14.919070c -7.92c -3.40\niter: 10 22:48:23 -14.919070c -9.67c -3.80\niter: 11 22:48:30 -14.919071c -7.85c -3.79\niter: 12 22:48:36 -14.919070c -9.42c -4.39c\n\nConverged after 12 iterations.\n\nDipole moment: (-0.000000, -0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +15.399146\nPotential: -7.723286\nExternal: +0.000000\nXC: -22.549734\nEntropy (-ST): -0.030010\nLocal: -0.030192\nSIC: +0.000000\n--------------------------\nFree energy: -14.934075\nExtrapolated: -14.919070\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.54788 2.00000\n 0 5 5.54788 2.00000\n 0 6 5.54788 2.00000\n 0 7 11.92279 0.00000\n\n 1 4 6.14720 1.99999\n 1 5 7.68339 0.08558\n 1 6 8.32283 0.00015\n 1 7 8.32283 0.00015\n\n\nFermi level: 7.37261\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 12\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 0 1) ( 1 0 0) ( 0 1 0)\n ( 0 0 1) ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 1 0) ( 1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 -1 0) (-1 0 0) ( 0 0 -1) (-1 0 0) ( 0 0 -1) ( 0 -1 0)\n (-1 0 0) ( 0 -1 0) (-1 0 0) ( 0 0 -1) ( 0 -1 0) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 -0.33333333 6/27\n 2: 0.33333333 0.00000000 0.00000000 6/27\n 3: 0.33333333 0.33333333 -0.33333333 6/27\n 4: 0.33333333 0.33333333 0.00000000 6/27\n 5: 0.33333333 0.33333333 0.33333333 2/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 760, 787\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 200.70 MiB\n Calculator: 5.13 MiB\n Density: 2.42 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.81 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.94 MiB\n Arrays psit_nG: 0.86 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.06 MiB\n Projectors: 0.50 MiB\n PW-descriptor: 0.29 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n \n \n \n \n Al \n Al \n Al \n \n Al \n \n \n \n \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.198128 2.119212 2.119212 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.119212 0.198128 2.119212 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.119212 2.119212 0.198128 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.040296 0.198128 0.198128 18 0.2229\n 2. axis: yes 0.198128 4.040296 0.198128 18 0.2229\n 3. axis: yes 0.198128 0.198128 4.040296 18 0.2229\n\n Lengths: 4.050000 4.050000 4.050000\n Angles: 84.260830 84.260830 84.260830\n\nEffective grid spacing dv^(1/3) = 0.2239\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:48:45 -14.617275\niter: 2 22:48:51 -14.621858 -2.58 -0.92\niter: 3 22:48:56 -14.622996c -2.48 -0.93\niter: 4 22:49:02 -14.611982 -3.79 -1.34\niter: 5 22:49:07 -14.612650 -5.20 -1.90\niter: 6 22:49:13 -14.613003c -4.86 -2.02\niter: 7 22:49:18 -14.613004c -6.47 -3.00\niter: 8 22:49:24 -14.613019c -6.42 -3.07\niter: 9 22:49:30 -14.613019c -8.00c -3.70\niter: 10 22:49:36 -14.613019c -9.07c -3.97\niter: 11 22:49:42 -14.613019c -8.48c -4.06c\n\nConverged after 11 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +20.022062\nPotential: -11.287530\nExternal: +0.000000\nXC: -23.298354\nEntropy (-ST): -0.033644\nLocal: -0.032376\nSIC: +0.000000\n--------------------------\nFree energy: -14.629841\nExtrapolated: -14.613019\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.69327 2.00000\n 0 5 5.69327 2.00000\n 0 6 5.69327 2.00000\n 0 7 11.44751 0.00000\n\n 1 4 6.31998 1.99994\n 1 5 7.72451 0.05504\n 1 6 7.72451 0.05504\n 1 7 8.02631 0.00276\n\n\nFermi level: 7.36802\n\nNo gap\n","output_type":"stream"},{"execution_count":5,"output_type":"execute_result","data":{"text/plain":"{'energy': {'s_e_0': -14.93666639635226,\n 's_01_e_m0_05000': -14.509157650657773,\n 's_01_e_m0_02500': -14.841982287128575,\n 's_01_e_0_02500': -14.86185138418095,\n 's_01_e_0_05000': -14.667794842757818,\n 's_08_e_m0_05000': -14.761984598633523,\n 's_08_e_m0_02500': -14.915410384618987,\n 's_08_e_0_02500': -14.906256779085401,\n 's_08_e_0_05000': -14.792358225770455,\n 's_23_e_m0_05000': -14.276020694675015,\n 's_23_e_m0_02500': -14.82856618062893,\n 's_23_e_0_02500': -14.919070455416568,\n 's_23_e_0_05000': -14.613019415010102}}"},"metadata":{}}],"id":"6f603915-171c-4458-b67f-81670f64686c"},{"cell_type":"markdown","source":"The atomistic structures are evaluated with the `evaluate_with_ase()` function, which returns the `result_dict`. This \n`result_dict` in analogy to the `task_dict` contains the same keys as well as the energies calculated with the \n[GPAW](https://wiki.fysik.dtu.dk/gpaw/) simulation code. Finally, the `result_dict` is provided as an input to the \n`analyse_structures()` function to calculate the corresponding elastic constants: ","metadata":{},"id":"064c0b0c-c69d-4457-b32d-1179036a6ac9"},{"cell_type":"code","source":"elastic_dict = workflow.analyse_structures(output_dict=result_dict)\nelastic_dict","metadata":{"trusted":true},"execution_count":6,"outputs":[{"execution_count":6,"output_type":"execute_result","data":{"text/plain":"{'elastic_matrix': array([[98.43569593, 63.17413032, 63.17413032, 0. , 0. ,\n 0. ],\n [63.17413032, 98.43569593, 63.17413032, 0. , 0. ,\n 0. ],\n [63.17413032, 63.17413032, 98.43569593, 0. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 84.66136139, 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 84.66136139,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0. ,\n 84.66136139]]),\n 'elastic_matrix_inverse': array([[ 0.02038923, -0.00797026, -0.00797026, 0. , 0. ,\n 0. ],\n [-0.00797026, 0.02038923, -0.00797026, 0. , 0. ,\n 0. ],\n [-0.00797026, -0.00797026, 0.02038923, 0. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0.01181176, 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0.01181176,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0. ,\n 0.01181176]]),\n 'bulkmodul_voigt': 74.92798552184198,\n 'bulkmodul_reuss': 74.92798552184202,\n 'bulkmodul_hill': 74.927985521842,\n 'shearmodul_voigt': 57.84912995743317,\n 'shearmodul_reuss': 33.58561744891993,\n 'shearmodul_hill': 45.71737370317655,\n 'youngsmodul_voigt': 138.02583917911684,\n 'youngsmodul_reuss': 87.65940807073069,\n 'youngsmodul_hill': 113.97206957810407,\n 'poissonsratio_voigt': 0.19298111553864067,\n 'poissonsratio_reuss': 0.3050140912855198,\n 'poissonsratio_hill': 0.24648531123065173,\n 'AVR': 26.536424277175126,\n 'elastic_matrix_eigval': EigResult(eigenvalues=array([ 35.26156561, 224.78395657, 35.26156561, 84.66136139,\n 84.66136139, 84.66136139]), eigenvectors=array([[-0.81649658, 0.57735027, 0.40373959, 0. , 0. ,\n 0. ],\n [ 0.40824829, 0.57735027, -0.81648004, 0. , 0. ,\n 0. ],\n [ 0.40824829, 0.57735027, 0.41274045, 0. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 1. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 1. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0. ,\n 1. ]]))}"},"metadata":{}}],"id":"245a78c5-8895-4f4f-b813-58fc0b9ea186"},{"cell_type":"markdown","source":"The bulk modulus calculated from the elastic constants `C11` and `C12` based on a strain of +/- 5% is calculated with \nthe [GPAW](https://wiki.fysik.dtu.dk/gpaw/) simulation code to be 74.9GPa. This differs from the bulk modulus calculated\nfrom the Equation of State above by 2.6GPa. In comparison to the experimental bulk modulus for Aluminium which is\n[reported to be 76GPa](https://periodictable.com/Elements/013/data.html) the calculation based on the elastic constants\nseem to be more precise, still this is more likely related to error cancellation. In general elastic properties calculated\nfrom density functional theory are expected to have errors of about 5-10% unless carefully converged.","metadata":{},"id":"43fe5df0-4142-464b-ab13-99e52868e57f"}]} \ No newline at end of file +{ + "cells": [ + { + "cell_type": "markdown", + "id": "cfa4e782-0e68-4a51-8d57-cb0eccf8e8bb", + "metadata": {}, + "source": "# Elastic Properties\nCalculate the bulk modulus for Aluminium using the [GPAW](https://wiki.fysik.dtu.dk/gpaw/) DFT code:" + }, + { + "cell_type": "markdown", + "id": "81c7f93c-1539-46db-8917-34a5c3b05744", + "metadata": {}, + "source": "## Equation of State \nOne way to calculate the bulk modulus is using the Equation of State to calculate the equilibrium properties:" + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "7e5c6f17-3774-4b3b-915c-8b0611ec0497", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pyiron-2datomistics-2dco7ko9rv:00594] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + }, + { + "data": { + "text/plain": "{'calc_energy': OrderedDict([(0.95,\n Atoms(symbols='Al4', pbc=True, cell=[3.9813426685908118, 3.9813426685908118, 3.9813426685908118])),\n (0.96,\n Atoms(symbols='Al4', pbc=True, cell=[3.9952635604153612, 3.9952635604153612, 3.9952635604153612])),\n (0.97,\n Atoms(symbols='Al4', pbc=True, cell=[4.009088111958974, 4.009088111958974, 4.009088111958974])),\n (0.98,\n Atoms(symbols='Al4', pbc=True, cell=[4.022817972936038, 4.022817972936038, 4.022817972936038])),\n (0.99,\n Atoms(symbols='Al4', pbc=True, cell=[4.036454748321015, 4.036454748321015, 4.036454748321015])),\n (1.0, Atoms(symbols='Al4', pbc=True, cell=[4.05, 4.05, 4.05])),\n (1.01,\n Atoms(symbols='Al4', pbc=True, cell=[4.063455248345461, 4.063455248345461, 4.063455248345461])),\n (1.02,\n Atoms(symbols='Al4', pbc=True, cell=[4.076821973718458, 4.076821973718458, 4.076821973718458])),\n (1.03,\n Atoms(symbols='Al4', pbc=True, cell=[4.0901016179023415, 4.0901016179023415, 4.0901016179023415])),\n (1.04,\n Atoms(symbols='Al4', pbc=True, cell=[4.1032955854717175, 4.1032955854717175, 4.1032955854717175])),\n (1.05,\n Atoms(symbols='Al4', pbc=True, cell=[4.1164052451001565, 4.1164052451001565, 4.1164052451001565]))])}" + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators.ase import evaluate_with_ase\n", + "from atomistics.workflows.evcurve.workflow import EnergyVolumeCurveWorkflow\n", + "from gpaw import GPAW, PW\n", + "\n", + "workflow = EnergyVolumeCurveWorkflow(\n", + " structure=bulk(\"Al\", a=4.05, cubic=True),\n", + " num_points=11,\n", + " fit_type=\"polynomial\",\n", + " fit_order=3,\n", + " vol_range=0.05,\n", + " axes=[\"x\", \"y\", \"z\"],\n", + " strains=None,\n", + ")\n", + "task_dict = workflow.generate_structures()\n", + "task_dict" + ] + }, + { + "cell_type": "markdown", + "id": "2c128729-f9b0-4b91-9995-3403f2887602", + "metadata": {}, + "source": "In the first step the `EnergyVolumeCurveWorkflow` object is initialized including all the parameters to generate\nthe strained structures and afterwards fit the resulting energy volume curve. This allows the user to see all relevant\nparameters at one place. After the initialization the function `generate_structures()` is called without any\nadditional parameters. This function returns the task dictionary `task_dict` which includes the tasks which should\nbe executed by the calculator. In this case the task is to calculate the energy `calc_energy` of the eleven generated \nstructures. Each structure is labeled by the ratio of compression or elongation. In the second step the `task_dict` \nis evaluated with the [GPAW](https://wiki.fysik.dtu.dk/gpaw/) simulation code using the `evaluate_with_ase()` function:" + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "374b84ab-1471-481a-ae2a-f04cca2bf331", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "\n ___ ___ ___ _ _ _ \n | | |_ | | | | \n | | | | | . | | | | \n |__ | _|___|_____| 24.1.0\n |___|_| \n\nUser: jovyan@jupyter-pyiron-2datomistics-2dco7ko9rv\nDate: Wed May 1 22:30:09 2024\nArch: x86_64\nPid: 594\nCWD: /home/jovyan\nPython: 3.10.12\ngpaw: /srv/conda/envs/notebook/lib/python3.10/site-packages/gpaw\n_gpaw: /srv/conda/envs/notebook/lib/python3.10/site-packages/\n _gpaw.cpython-310-x86_64-linux-gnu.so\nase: /srv/conda/envs/notebook/lib/python3.10/site-packages/ase (version 3.22.1)\nnumpy: /srv/conda/envs/notebook/lib/python3.10/site-packages/numpy (version 1.26.4)\nscipy: /srv/conda/envs/notebook/lib/python3.10/site-packages/scipy (version 1.13.0)\nlibxc: 6.2.2\nunits: Angstrom and eV\ncores: 1\nOpenMP: True\nOMP_NUM_THREADS: 1\n\nInput parameters:\n kpts: [3 3 3]\n mode: {ecut: 300.0,\n name: pw}\n xc: PBE\n\nSystem changes: positions, numbers, cell, pbc, initial_charges, initial_magmoms \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 729, 748\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 16*16*16 grid\n Fine grid: 32*32*32 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 32*32*32 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 159.93 MiB\n Calculator: 3.78 MiB\n Density: 1.91 MiB\n Arrays: 0.81 MiB\n Localized functions: 0.79 MiB\n Mixer: 0.31 MiB\n Hamiltonian: 0.55 MiB\n Arrays: 0.53 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.32 MiB\n Arrays psit_nG: 0.55 MiB\n Eigensolver: 0.22 MiB\n Projections: 0.04 MiB\n Projectors: 0.32 MiB\n PW-descriptor: 0.20 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | Al | \n | .---------. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 1.990671 1.990671 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.990671 0.000000 1.990671 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.990671 1.990671 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 3.981343 0.000000 0.000000 16 0.2488\n 2. axis: yes 0.000000 3.981343 0.000000 16 0.2488\n 3. axis: yes 0.000000 0.000000 3.981343 16 0.2488\n\n Lengths: 3.981343 3.981343 3.981343\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2488\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:30:13 -14.882425\niter: 2 22:30:15 -14.888515 -2.60 -0.94\niter: 3 22:30:18 -14.900036 -2.44 -0.96\niter: 4 22:30:21 -14.894259 -3.56 -1.21\niter: 5 22:30:24 -14.894996c -5.28 -2.02\niter: 6 22:30:27 -14.895377c -4.42 -2.09\niter: 7 22:30:30 -14.895377c -6.24 -3.62\niter: 8 22:30:32 -14.895377c -8.01c -3.81\niter: 9 22:30:34 -14.895378c -8.43c -3.83\niter: 10 22:30:37 -14.895378c -10.06c -4.52c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +21.064728\nPotential: -11.809468\nExternal: +0.000000\nXC: -24.083645\nEntropy (-ST): -0.066076\nLocal: -0.033954\nSIC: +0.000000\n--------------------------\nFree energy: -14.928416\nExtrapolated: -14.895378\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.98391 2.00000\n 0 5 5.98391 2.00000\n 0 6 5.98391 2.00000\n 0 7 13.41407 0.00000\n\n 1 4 6.93763 1.99987\n 1 5 6.93763 1.99987\n 1 6 8.35072 0.02220\n 1 7 8.35072 0.02220\n\n\nFermi level: 7.90175\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 739, 767\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 16*16*16 grid\n Fine grid: 32*32*32 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 32*32*32 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 175.34 MiB\n Calculator: 3.82 MiB\n Density: 1.92 MiB\n Arrays: 0.81 MiB\n Localized functions: 0.80 MiB\n Mixer: 0.31 MiB\n Hamiltonian: 0.55 MiB\n Arrays: 0.53 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.35 MiB\n Arrays psit_nG: 0.56 MiB\n Eigensolver: 0.22 MiB\n Projections: 0.04 MiB\n Projectors: 0.32 MiB\n PW-descriptor: 0.20 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 1.997632 1.997632 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.997632 0.000000 1.997632 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.997632 1.997632 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 3.995264 0.000000 0.000000 16 0.2497\n 2. axis: yes 0.000000 3.995264 0.000000 16 0.2497\n 3. axis: yes 0.000000 0.000000 3.995264 16 0.2497\n\n Lengths: 3.995264 3.995264 3.995264\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2497\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:30:41 -14.901011\niter: 2 22:30:44 -14.906870 -2.60 -0.94\niter: 3 22:30:47 -14.916095 -2.47 -0.96\niter: 4 22:30:50 -14.909770 -3.60 -1.22\niter: 5 22:30:54 -14.910476 -5.19 -2.03\niter: 6 22:30:58 -14.910818c -4.39 -2.08\niter: 7 22:31:02 -14.910819c -6.19 -3.56\niter: 8 22:31:06 -14.910819c -7.98c -3.81\niter: 9 22:31:10 -14.910820c -8.50c -3.83\niter: 10 22:31:14 -14.910820c -10.09c -4.48c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, 0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +19.609492\nPotential: -10.740904\nExternal: +0.000000\nXC: -23.714414\nEntropy (-ST): -0.065421\nLocal: -0.032284\nSIC: +0.000000\n--------------------------\nFree energy: -14.943530\nExtrapolated: -14.910820\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.88373 2.00000\n 0 5 5.88373 2.00000\n 0 6 5.88373 2.00000\n 0 7 13.25946 0.00000\n\n 1 4 6.83715 1.99985\n 1 5 6.83715 1.99985\n 1 6 8.25115 0.01891\n 1 7 8.25115 0.01891\n\n\nFermi level: 7.78599\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 748, 767\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 176.70 MiB\n Calculator: 4.59 MiB\n Density: 2.40 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.80 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.41 MiB\n Arrays psit_nG: 0.56 MiB\n Eigensolver: 0.22 MiB\n Projections: 0.04 MiB\n Projectors: 0.32 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | Al | \n | .---------. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.004544 2.004544 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.004544 0.000000 2.004544 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.004544 2.004544 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.009088 0.000000 0.000000 18 0.2227\n 2. axis: yes 0.000000 4.009088 0.000000 18 0.2227\n 3. axis: yes 0.000000 0.000000 4.009088 18 0.2227\n\n Lengths: 4.009088 4.009088 4.009088\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2227\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:31:21 -14.915469\niter: 2 22:31:25 -14.921113 -2.61 -0.94\niter: 3 22:31:29 -14.928129 -2.49 -0.95\niter: 4 22:31:34 -14.921329 -3.65 -1.23\niter: 5 22:31:38 -14.921925 -5.12 -2.04\niter: 6 22:31:42 -14.922306c -4.38 -2.09\niter: 7 22:31:46 -14.922307c -6.21 -3.62\niter: 8 22:31:50 -14.922306c -8.03c -3.81\niter: 9 22:31:54 -14.922307c -8.51c -3.81\niter: 10 22:31:58 -14.922307c -10.13c -4.49c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +18.208265\nPotential: -9.713675\nExternal: +0.000000\nXC: -23.353256\nEntropy (-ST): -0.064736\nLocal: -0.031272\nSIC: +0.000000\n--------------------------\nFree energy: -14.954675\nExtrapolated: -14.922307\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.78499 2.00000\n 0 5 5.78499 2.00000\n 0 6 5.78499 2.00000\n 0 7 13.10778 0.00000\n\n 1 4 6.73786 1.99982\n 1 5 6.73786 1.99982\n 1 6 8.15344 0.01607\n 1 7 8.15344 0.01607\n\n\nFermi level: 7.67184\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 751, 784\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 179.96 MiB\n Calculator: 4.62 MiB\n Density: 2.41 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.81 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.44 MiB\n Arrays psit_nG: 0.57 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.33 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.011409 2.011409 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.011409 0.000000 2.011409 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.011409 2.011409 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.022818 0.000000 0.000000 18 0.2235\n 2. axis: yes 0.000000 4.022818 0.000000 18 0.2235\n 3. axis: yes 0.000000 0.000000 4.022818 18 0.2235\n\n Lengths: 4.022818 4.022818 4.022818\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2235\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:32:04 -14.926405\niter: 2 22:32:08 -14.931838 -2.61 -0.94\niter: 3 22:32:12 -14.936753 -2.52 -0.95\niter: 4 22:32:16 -14.929473 -3.69 -1.23\niter: 5 22:32:20 -14.930009 -5.05 -2.04\niter: 6 22:32:23 -14.930391c -4.35 -2.09\niter: 7 22:32:27 -14.930392c -6.26 -3.62\niter: 8 22:32:31 -14.930391c -8.07c -3.81\niter: 9 22:32:35 -14.930392c -8.53c -3.79\niter: 10 22:32:39 -14.930392c -10.13c -4.48c\n\nConverged after 10 iterations.\n\nDipole moment: (0.000000, 0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +16.855968\nPotential: -8.724549\nExternal: +0.000000\nXC: -22.999659\nEntropy (-ST): -0.064031\nLocal: -0.030137\nSIC: +0.000000\n--------------------------\nFree energy: -14.962408\nExtrapolated: -14.930392\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.68763 2.00000\n 0 5 5.68763 2.00000\n 0 6 5.68763 2.00000\n 0 7 12.95893 0.00000\n\n 1 4 6.63963 1.99980\n 1 5 6.63963 1.99980\n 1 6 8.05750 0.01363\n 1 7 8.05750 0.01363\n\n\nFermi level: 7.55929\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 751, 792\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 180.56 MiB\n Calculator: 4.64 MiB\n Density: 2.42 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.82 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.45 MiB\n Arrays psit_nG: 0.58 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.33 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.018227 2.018227 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.018227 0.000000 2.018227 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.018227 2.018227 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.036455 0.000000 0.000000 18 0.2242\n 2. axis: yes 0.000000 4.036455 0.000000 18 0.2242\n 3. axis: yes 0.000000 0.000000 4.036455 18 0.2242\n\n Lengths: 4.036455 4.036455 4.036455\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2242\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:32:46 -14.933780\niter: 2 22:32:50 -14.939007 -2.61 -0.94\niter: 3 22:32:54 -14.941916 -2.55 -0.95\niter: 4 22:32:59 -14.934186 -3.72 -1.23\niter: 5 22:33:03 -14.934636 -5.00 -2.05\niter: 6 22:33:07 -14.935049c -4.32 -2.10\niter: 7 22:33:11 -14.935048c -6.37 -3.46\niter: 8 22:33:15 -14.935048c -8.13c -3.80\niter: 9 22:33:19 -14.935049c -8.50c -3.76\niter: 10 22:33:23 -14.935049c -10.15c -4.48c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, 0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +15.551943\nPotential: -7.772560\nExternal: +0.000000\nXC: -22.653530\nEntropy (-ST): -0.063320\nLocal: -0.029241\nSIC: +0.000000\n--------------------------\nFree energy: -14.966709\nExtrapolated: -14.935049\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.59162 2.00000\n 0 5 5.59162 2.00000\n 0 6 5.59162 2.00000\n 0 7 12.81284 0.00000\n\n 1 4 6.54249 1.99977\n 1 5 6.54249 1.99977\n 1 6 7.96330 0.01153\n 1 7 7.96330 0.01153\n\n\nFermi level: 7.44830\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 751, 792\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 181.98 MiB\n Calculator: 4.66 MiB\n Density: 2.43 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.83 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.45 MiB\n Arrays psit_nG: 0.58 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.33 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.025000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.025000 0.000000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.025000 2.025000 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.050000 0.000000 0.000000 18 0.2250\n 2. axis: yes 0.000000 4.050000 0.000000 18 0.2250\n 3. axis: yes 0.000000 0.000000 4.050000 18 0.2250\n\n Lengths: 4.050000 4.050000 4.050000\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2250\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:33:29 -14.937999\niter: 2 22:33:33 -14.943025 -2.61 -0.94\niter: 3 22:33:37 -14.944013 -2.57 -0.95\niter: 4 22:33:42 -14.935856 -3.75 -1.24\niter: 5 22:33:46 -14.936188 -4.96 -2.05\niter: 6 22:33:49 -14.936670c -4.31 -2.12\niter: 7 22:33:53 -14.936666c -6.58 -3.23\niter: 8 22:33:57 -14.936665c -8.27c -3.81\niter: 9 22:34:01 -14.936666c -8.42c -3.71\niter: 10 22:34:05 -14.936666c -10.18c -4.51c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +14.292126\nPotential: -6.854900\nExternal: +0.000000\nXC: -22.314456\nEntropy (-ST): -0.062606\nLocal: -0.028133\nSIC: +0.000000\n--------------------------\nFree energy: -14.967970\nExtrapolated: -14.936666\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.49693 2.00000\n 0 5 5.49693 2.00000\n 0 6 5.49693 2.00000\n 0 7 12.66943 0.00000\n\n 1 4 6.44637 1.99973\n 1 5 6.44637 1.99973\n 1 6 7.87077 0.00975\n 1 7 7.87077 0.00975\n\n\nFermi level: 7.33890\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 751, 796\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 182.63 MiB\n Calculator: 4.66 MiB\n Density: 2.44 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.83 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.46 MiB\n Arrays psit_nG: 0.58 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.33 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.031728 2.031728 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.031728 0.000000 2.031728 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.031728 2.031728 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.063455 0.000000 0.000000 18 0.2257\n 2. axis: yes 0.000000 4.063455 0.000000 18 0.2257\n 3. axis: yes 0.000000 0.000000 4.063455 18 0.2257\n\n Lengths: 4.063455 4.063455 4.063455\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2257\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:34:11 -14.939033\niter: 2 22:34:15 -14.943862 -2.61 -0.94\niter: 3 22:34:19 -14.943014c -2.60 -0.95\niter: 4 22:34:23 -14.934451 -3.78 -1.24\niter: 5 22:34:27 -14.934640 -4.97 -2.06\niter: 6 22:34:32 -14.935221c -4.32 -2.15\niter: 7 22:34:35 -14.935212c -6.84 -3.06\niter: 8 22:34:40 -14.935212c -8.42c -3.80\niter: 9 22:34:44 -14.935213c -8.20c -3.64\niter: 10 22:34:48 -14.935213c -9.82c -4.52c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +13.077726\nPotential: -5.972581\nExternal: +0.000000\nXC: -21.982427\nEntropy (-ST): -0.061895\nLocal: -0.026983\nSIC: +0.000000\n--------------------------\nFree energy: -14.966160\nExtrapolated: -14.935213\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.40354 2.00000\n 0 5 5.40354 2.00000\n 0 6 5.40354 2.00000\n 0 7 12.52862 0.00000\n\n 1 4 6.35125 1.99970\n 1 5 6.35125 1.99970\n 1 6 7.77989 0.00823\n 1 7 7.77989 0.00823\n\n\nFermi level: 7.23099\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 796, 807\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 182.70 MiB\n Calculator: 4.69 MiB\n Density: 2.45 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.84 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.47 MiB\n Arrays psit_nG: 0.59 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.34 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n |Al| | \n | .---------. \n | / Al / \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.038411 2.038411 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.038411 0.000000 2.038411 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.038411 2.038411 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.076822 0.000000 0.000000 18 0.2265\n 2. axis: yes 0.000000 4.076822 0.000000 18 0.2265\n 3. axis: yes 0.000000 0.000000 4.076822 18 0.2265\n\n Lengths: 4.076822 4.076822 4.076822\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2265\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:34:54 -14.937251\niter: 2 22:34:59 -14.941885 -2.62 -0.94\niter: 3 22:35:03 -14.939271c -2.62 -0.95\niter: 4 22:35:07 -14.930329 -3.80 -1.24\niter: 5 22:35:11 -14.930379 -5.05 -2.06\niter: 6 22:35:15 -14.931060c -4.36 -2.16\niter: 7 22:35:19 -14.931044c -6.85 -2.92\niter: 8 22:35:23 -14.931044c -8.18c -3.78\niter: 9 22:35:27 -14.931045c -7.93c -3.57\niter: 10 22:35:31 -14.931045c -9.45c -4.64c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +11.900238\nPotential: -5.117966\nExternal: +0.000000\nXC: -21.656807\nEntropy (-ST): -0.061203\nLocal: -0.025909\nSIC: +0.000000\n--------------------------\nFree energy: -14.961646\nExtrapolated: -14.931045\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.31128 2.00000\n 0 5 5.31128 2.00000\n 0 6 5.31128 2.00000\n 0 7 12.39031 0.00000\n\n 1 4 6.25708 1.99966\n 1 5 6.25708 1.99966\n 1 6 7.69059 0.00695\n 1 7 7.69059 0.00695\n\n\nFermi level: 7.12468\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 799, 814\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 183.73 MiB\n Calculator: 4.71 MiB\n Density: 2.46 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.85 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.48 MiB\n Arrays psit_nG: 0.60 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.34 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n |Al| | \n | .---------. \n | / Al / \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.045051 2.045051 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.045051 0.000000 2.045051 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.045051 2.045051 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.090102 0.000000 0.000000 18 0.2272\n 2. axis: yes 0.000000 4.090102 0.000000 18 0.2272\n 3. axis: yes 0.000000 0.000000 4.090102 18 0.2272\n\n Lengths: 4.090102 4.090102 4.090102\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2272\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:35:38 -14.932645\niter: 2 22:35:43 -14.937089 -2.62 -0.94\niter: 3 22:35:47 -14.932789c -2.65 -0.95\niter: 4 22:35:51 -14.923493 -3.82 -1.25\niter: 5 22:35:55 -14.923447 -5.23 -2.07\niter: 6 22:35:59 -14.924190c -4.40 -2.16\niter: 7 22:36:03 -14.924165c -6.57 -2.79\niter: 8 22:36:07 -14.924165c -7.67c -3.77\niter: 9 22:36:11 -14.924165c -7.77c -3.50\niter: 10 22:36:14 -14.924165c -9.28c -4.80c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +10.761960\nPotential: -4.293213\nExternal: +0.000000\nXC: -21.337659\nEntropy (-ST): -0.060526\nLocal: -0.024991\nSIC: +0.000000\n--------------------------\nFree energy: -14.954428\nExtrapolated: -14.924165\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.22036 2.00000\n 0 5 5.22036 2.00000\n 0 6 5.22036 2.00000\n 0 7 12.25448 0.00000\n\n 1 4 6.16384 1.99962\n 1 5 6.16384 1.99962\n 1 6 7.60284 0.00585\n 1 7 7.60284 0.00585\n\n\nFermi level: 7.01977\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 799, 824\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 184.05 MiB\n Calculator: 4.73 MiB\n Density: 2.46 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.86 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.50 MiB\n Arrays psit_nG: 0.60 MiB\n Eigensolver: 0.24 MiB\n Projections: 0.04 MiB\n Projectors: 0.35 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n |Al| | \n | .---------. \n | / Al / \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.051648 2.051648 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.051648 0.000000 2.051648 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.051648 2.051648 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.103296 0.000000 0.000000 18 0.2280\n 2. axis: yes 0.000000 4.103296 0.000000 18 0.2280\n 3. axis: yes 0.000000 0.000000 4.103296 18 0.2280\n\n Lengths: 4.103296 4.103296 4.103296\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2280\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:36:21 -14.925350\niter: 2 22:36:25 -14.929610 -2.62 -0.94\niter: 3 22:36:30 -14.923699c -2.67 -0.95\niter: 4 22:36:33 -14.914071 -3.84 -1.25\niter: 5 22:36:37 -14.913995 -5.39 -2.07\niter: 6 22:36:41 -14.914744c -4.46 -2.14\niter: 7 22:36:45 -14.914703c -6.23 -2.67\niter: 8 22:36:49 -14.914703c -7.29 -3.73\niter: 9 22:36:53 -14.914704c -7.61c -3.42\niter: 10 22:36:57 -14.914704c -9.08c -4.77c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +9.664679\nPotential: -3.500677\nExternal: +0.000000\nXC: -21.025036\nEntropy (-ST): -0.059878\nLocal: -0.023731\nSIC: +0.000000\n--------------------------\nFree energy: -14.944642\nExtrapolated: -14.914704\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.13063 2.00000\n 0 5 5.13063 2.00000\n 0 6 5.13063 2.00000\n 0 7 12.12106 0.00000\n\n 1 4 6.07144 1.99957\n 1 5 6.07144 1.99957\n 1 6 7.51659 0.00494\n 1 7 7.51659 0.00494\n\n\nFermi level: 6.91650\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 799, 824\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 184.18 MiB\n Calculator: 4.75 MiB\n Density: 2.48 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.88 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.50 MiB\n Arrays psit_nG: 0.60 MiB\n Eigensolver: 0.24 MiB\n Projections: 0.04 MiB\n Projectors: 0.35 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n | Al | \n | .---------. \n | / All / \n |/ / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.058203 2.058203 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.058203 0.000000 2.058203 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.058203 2.058203 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.116405 0.000000 0.000000 18 0.2287\n 2. axis: yes 0.000000 4.116405 0.000000 18 0.2287\n 3. axis: yes 0.000000 0.000000 4.116405 18 0.2287\n\n Lengths: 4.116405 4.116405 4.116405\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2287\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:37:03 -14.915473\niter: 2 22:37:07 -14.919556 -2.62 -0.94\niter: 3 22:37:11 -14.912114 -2.70 -0.95\niter: 4 22:37:15 -14.902180 -3.86 -1.25\niter: 5 22:37:20 -14.902124 -5.50 -2.07\niter: 6 22:37:24 -14.902858c -4.47 -2.11\niter: 7 22:37:29 -14.902774c -5.84 -2.51\niter: 8 22:37:32 -14.902775c -6.88 -3.71\niter: 9 22:37:36 -14.902775c -7.36 -3.30\niter: 10 22:37:40 -14.902775c -8.69c -4.59c\n\nConverged after 10 iterations.\n\nDipole moment: (0.000000, -0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +8.611038\nPotential: -2.741920\nExternal: +0.000000\nXC: -20.719117\nEntropy (-ST): -0.059259\nLocal: -0.023145\nSIC: +0.000000\n--------------------------\nFree energy: -14.932404\nExtrapolated: -14.902775\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.04210 2.00000\n 0 5 5.04210 2.00000\n 0 6 5.04210 2.00000\n 0 7 11.98998 0.00000\n\n 1 4 5.97999 1.99953\n 1 5 5.97999 1.99953\n 1 6 7.43183 0.00417\n 1 7 7.43183 0.00417\n\n\nFermi level: 6.81475\n\nNo gap\n" + }, + { + "data": { + "text/plain": "{'energy': {0.95: -14.895378072812221,\n 0.96: -14.910819737644692,\n 0.97: -14.922307241109358,\n 0.98: -14.93039227930928,\n 0.99: -14.935048569951459,\n 1.0: -14.93666639635226,\n 1.01: -14.935212782113831,\n 1.02: -14.931045138828088,\n 1.03: -14.924165445694268,\n 1.04: -14.914703573990083,\n 1.05: -14.902774559119468}}" + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result_dict = evaluate_with_ase(\n", + " task_dict=task_dict, ase_calculator=GPAW(xc=\"PBE\", mode=PW(300), kpts=(3, 3, 3))\n", + ")\n", + "result_dict" + ] + }, + { + "cell_type": "markdown", + "id": "61113aa0-8b91-4867-bee2-47b5b7d72a0d", + "metadata": {}, + "source": "In analogy to the `task_dict` which defines the tasks to be executed by the simulation code the `result_dict` summarizes \nthe results of the calculations. In this case the energies calculated for the specific strains. By ordering both the \n`task_dict` and the `result_dict` with the same labels, the `EnergyVolumeCurveWorkflow` object is able to match the \ncalculation results to the corresponding structure. Finally, in the third step the `analyse_structures()` function takes\nthe `result_dict` as an input and fits the Equation of State with the fitting parameters defined in the first step:" + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "54b0d2c8-f8c7-4b9a-85c9-303a04976dfc", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "{'b_prime_eq': 4.453836548379018,\n 'bulkmodul_eq': 72.38919826524031,\n 'volume_eq': 66.44252286130995,\n 'energy_eq': -14.936703222033056,\n 'fit_dict': {'fit_type': 'polynomial',\n 'least_square_error': 4.432974567361701e-09,\n 'poly_fit': array([-9.30297838e-05, 2.19434659e-02, -1.68388816e+00, 2.73605421e+01]),\n 'fit_order': 3},\n 'energy': [-14.895378072812221,\n -14.910819737644692,\n -14.922307241109358,\n -14.93039227930928,\n -14.935048569951459,\n -14.93666639635226,\n -14.935212782113831,\n -14.931045138828088,\n -14.924165445694268,\n -14.914703573990083,\n -14.902774559119468],\n 'volume': [63.10861874999998,\n 63.77291999999998,\n 64.43722124999998,\n 65.1015225,\n 65.76582375000004,\n 66.43012500000002,\n 67.09442624999994,\n 67.75872750000002,\n 68.42302874999999,\n 69.08732999999997,\n 69.75163125000002]}" + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fit_dict = workflow.analyse_structures(output_dict=result_dict)\n", + "fit_dict" + ] + }, + { + "cell_type": "markdown", + "id": "4c7eeb29-2d1f-44c2-8fcb-09be2bd5f717", + "metadata": {}, + "source": "The bulk modulus for Aluminium is calculated using the [GPAW](https://wiki.fysik.dtu.dk/gpaw/) simulation code by fitting\nthe Equation of State with a third order polynomial over a volume range of +/-5% to be 72.3GPa. " + }, + { + "cell_type": "markdown", + "id": "39b116c1-65fb-4c8b-a80e-b8f331012849", + "metadata": {}, + "source": "## Elastic Matrix\nAn alternative approach to calculate the bulk modulus is based on the relation `B = (1/3) (C11 + 2 C12 )`. The bulk\nmodulus can be calculated based on the sum of the first elastic constant `C11` and twice the second elastic constant `C12`\ndivided by there. " + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "19aae7eb-7fa2-4cb0-b109-d2bad7aedc39", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "{'calc_energy': OrderedDict([('s_e_0',\n Atoms(symbols='Al4', pbc=True, cell=[4.05, 4.05, 4.05])),\n ('s_01_e_m0_05000',\n Atoms(symbols='Al4', pbc=True, cell=[3.8421673571095107, 3.8421673571095107, 3.8421673571095107])),\n ('s_01_e_m0_02500',\n Atoms(symbols='Al4', pbc=True, cell=[3.94745170964797, 3.94745170964797, 3.94745170964797])),\n ('s_01_e_0_02500',\n Atoms(symbols='Al4', pbc=True, cell=[4.150015060213919, 4.150015060213919, 4.150015060213919])),\n ('s_01_e_0_05000',\n Atoms(symbols='Al4', pbc=True, cell=[4.247675835085893, 4.247675835085893, 4.247675835085893])),\n ('s_08_e_m0_05000',\n Atoms(symbols='Al4', pbc=True, cell=[3.8421673571095107, 3.8421673571095107, 4.05])),\n ('s_08_e_m0_02500',\n Atoms(symbols='Al4', pbc=True, cell=[3.94745170964797, 3.94745170964797, 4.05])),\n ('s_08_e_0_02500',\n Atoms(symbols='Al4', pbc=True, cell=[4.150015060213919, 4.150015060213919, 4.05])),\n ('s_08_e_0_05000',\n Atoms(symbols='Al4', pbc=True, cell=[4.247675835085893, 4.247675835085893, 4.05])),\n ('s_23_e_m0_05000',\n Atoms(symbols='Al4', pbc=True, cell=[[4.039260597921188, -0.2084152371679185, -0.2084152371679185], [-0.2084152371679185, 4.039260597921188, -0.2084152371679185], [-0.2084152371679185, -0.2084152371679185, 4.039260597921188]])),\n ('s_23_e_m0_02500',\n Atoms(symbols='Al4', pbc=True, cell=[[4.047399159178924, -0.1026159010347065, -0.1026159010347065], [-0.1026159010347065, 4.047399159178924, -0.1026159010347065], [-0.1026159010347065, -0.1026159010347065, 4.047399159178924]])),\n ('s_23_e_0_02500',\n Atoms(symbols='Al4', pbc=True, cell=[[4.047526418127057, 0.1000747084794181, 0.1000747084794181], [0.1000747084794181, 4.047526418127057, 0.1000747084794181], [0.1000747084794181, 0.1000747084794181, 4.047526418127057]])),\n ('s_23_e_0_05000',\n Atoms(symbols='Al4', pbc=True, cell=[[4.0402958099962145, 0.19812845289162093, 0.19812845289162093], [0.19812845289162093, 4.0402958099962145, 0.19812845289162093], [0.19812845289162093, 0.19812845289162093, 4.0402958099962145]]))])}" + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators.ase import evaluate_with_ase\n", + "from atomistics.workflows.elastic.workflow import ElasticMatrixWorkflow\n", + "from gpaw import GPAW, PW\n", + "\n", + "workflow = ElasticMatrixWorkflow(\n", + " structure=bulk(\"Al\", a=4.05, cubic=True),\n", + " num_of_point=5,\n", + " eps_range=0.05,\n", + " sqrt_eta=True,\n", + " fit_order=2,\n", + ")\n", + "task_dict = workflow.generate_structures()\n", + "task_dict" + ] + }, + { + "cell_type": "markdown", + "id": "98d423dc-db2e-4b3d-a336-031d48e3098d", + "metadata": {}, + "source": "In analogy to the example with the `EnergyVolumeCurveWorkflow` above, the `ElasticMatrixWorkflow` is initialized with all\nthe parameters required to generate the atomistic structures and afterwards fit the resulting energies. By calling the\n`generate_structures()` function the task dictionary `task_dict` is generated. The task dictionary specifies that the \nenergy should be calculated for a total of thirteen structures with different displacements. In the second step the \nstructures are again evaluated with the [GPAW](https://wiki.fysik.dtu.dk/gpaw/) simulation code: " + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "6f603915-171c-4458-b67f-81670f64686c", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "\n ___ ___ ___ _ _ _ \n | | |_ | | | | \n | | | | | . | | | | \n |__ | _|___|_____| 24.1.0\n |___|_| \n\nUser: jovyan@jupyter-pyiron-2datomistics-2dco7ko9rv\nDate: Wed May 1 22:37:40 2024\nArch: x86_64\nPid: 594\nCWD: /home/jovyan\nPython: 3.10.12\ngpaw: /srv/conda/envs/notebook/lib/python3.10/site-packages/gpaw\n_gpaw: /srv/conda/envs/notebook/lib/python3.10/site-packages/\n _gpaw.cpython-310-x86_64-linux-gnu.so\nase: /srv/conda/envs/notebook/lib/python3.10/site-packages/ase (version 3.22.1)\nnumpy: /srv/conda/envs/notebook/lib/python3.10/site-packages/numpy (version 1.26.4)\nscipy: /srv/conda/envs/notebook/lib/python3.10/site-packages/scipy (version 1.13.0)\nlibxc: 6.2.2\nunits: Angstrom and eV\ncores: 1\nOpenMP: True\nOMP_NUM_THREADS: 1\n\nInput parameters:\n kpts: [3 3 3]\n mode: {ecut: 300.0,\n name: pw}\n xc: PBE\n\nSystem changes: positions, numbers, cell, pbc, initial_charges, initial_magmoms \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 751, 792\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 186.33 MiB\n Calculator: 4.66 MiB\n Density: 2.43 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.83 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.45 MiB\n Arrays psit_nG: 0.58 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.04 MiB\n Projectors: 0.33 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.025000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.025000 0.000000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.025000 2.025000 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.050000 0.000000 0.000000 18 0.2250\n 2. axis: yes 0.000000 4.050000 0.000000 18 0.2250\n 3. axis: yes 0.000000 0.000000 4.050000 18 0.2250\n\n Lengths: 4.050000 4.050000 4.050000\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2250\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:37:46 -14.937999\niter: 2 22:37:51 -14.943025 -2.61 -0.94\niter: 3 22:37:55 -14.944013 -2.57 -0.95\niter: 4 22:37:59 -14.935856 -3.75 -1.24\niter: 5 22:38:03 -14.936188 -4.96 -2.05\niter: 6 22:38:07 -14.936670c -4.31 -2.12\niter: 7 22:38:11 -14.936666c -6.58 -3.23\niter: 8 22:38:15 -14.936665c -8.27c -3.81\niter: 9 22:38:19 -14.936666c -8.42c -3.71\niter: 10 22:38:24 -14.936666c -10.18c -4.51c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +14.292126\nPotential: -6.854900\nExternal: +0.000000\nXC: -22.314456\nEntropy (-ST): -0.062606\nLocal: -0.028133\nSIC: +0.000000\n--------------------------\nFree energy: -14.967970\nExtrapolated: -14.936666\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.49693 2.00000\n 0 5 5.49693 2.00000\n 0 6 5.49693 2.00000\n 0 7 12.66943 0.00000\n\n 1 4 6.44637 1.99973\n 1 5 6.44637 1.99973\n 1 6 7.87077 0.00975\n 1 7 7.87077 0.00975\n\n\nFermi level: 7.33890\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 658, 691\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 16*16*16 grid\n Fine grid: 32*32*32 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 32*32*32 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 193.62 MiB\n Calculator: 3.61 MiB\n Density: 1.84 MiB\n Arrays: 0.81 MiB\n Localized functions: 0.71 MiB\n Mixer: 0.31 MiB\n Hamiltonian: 0.55 MiB\n Arrays: 0.53 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.01 MiB\n Wavefunctions: 1.23 MiB\n Arrays psit_nG: 0.51 MiB\n Eigensolver: 0.20 MiB\n Projections: 0.04 MiB\n Projectors: 0.29 MiB\n PW-descriptor: 0.20 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .--------. \n /| | \n * | | \n |Al | \n | | | \n | .-Al-----. \n |/ Al / \n Al-------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 1.921084 1.921084 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.921084 0.000000 1.921084 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.921084 1.921084 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 3.842167 0.000000 0.000000 16 0.2401\n 2. axis: yes 0.000000 3.842167 0.000000 16 0.2401\n 3. axis: yes 0.000000 0.000000 3.842167 16 0.2401\n\n Lengths: 3.842167 3.842167 3.842167\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2401\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:38:29 -14.458328\niter: 2 22:38:33 -14.467077 -2.57 -0.94\niter: 3 22:38:36 -14.505006 -2.15 -0.96\niter: 4 22:38:40 -14.507040 -3.05 -1.16\niter: 5 22:38:44 -14.508034c -5.81 -1.94\niter: 6 22:38:47 -14.509159c -4.57 -2.12\niter: 7 22:38:51 -14.509154c -6.78 -2.83\niter: 8 22:38:55 -14.509155c -8.99c -3.51\niter: 9 22:38:59 -14.509158c -7.43c -3.62\niter: 10 22:39:02 -14.509158c -9.08c -4.97c\n\nConverged after 10 iterations.\n\nDipole moment: (0.000000, 0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +38.117828\nPotential: -24.459808\nExternal: +0.000000\nXC: -28.083947\nEntropy (-ST): -0.069078\nLocal: -0.048692\nSIC: +0.000000\n--------------------------\nFree energy: -14.543697\nExtrapolated: -14.509158\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 7.02831 2.00000\n 0 5 7.02831 2.00000\n 0 6 7.02831 2.00000\n 0 7 15.06935 0.00000\n\n 1 4 7.97110 1.99998\n 1 5 7.97110 1.99998\n 1 6 9.41360 0.08491\n 1 7 9.41360 0.08491\n\n\nFermi level: 9.10201\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 717, 739\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 16*16*16 grid\n Fine grid: 32*32*32 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 32*32*32 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 193.62 MiB\n Calculator: 3.74 MiB\n Density: 1.89 MiB\n Arrays: 0.81 MiB\n Localized functions: 0.77 MiB\n Mixer: 0.31 MiB\n Hamiltonian: 0.55 MiB\n Arrays: 0.53 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.31 MiB\n Arrays psit_nG: 0.54 MiB\n Eigensolver: 0.21 MiB\n Projections: 0.04 MiB\n Projectors: 0.31 MiB\n PW-descriptor: 0.20 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | Al | \n | .---------. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 1.973726 1.973726 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.973726 0.000000 1.973726 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.973726 1.973726 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 3.947452 0.000000 0.000000 16 0.2467\n 2. axis: yes 0.000000 3.947452 0.000000 16 0.2467\n 3. axis: yes 0.000000 0.000000 3.947452 16 0.2467\n\n Lengths: 3.947452 3.947452 3.947452\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2467\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:39:08 -14.820923\niter: 2 22:39:13 -14.827577 -2.60 -0.94\niter: 3 22:39:16 -14.844992 -2.37 -0.96\niter: 4 22:39:20 -14.840675 -3.45 -1.20\niter: 5 22:39:26 -14.841471c -5.48 -2.00\niter: 6 22:39:31 -14.841983c -4.48 -2.09\niter: 7 22:39:35 -14.841981c -6.53 -3.59\niter: 8 22:39:39 -14.841981c -8.15c -3.79\niter: 9 22:39:44 -14.841982c -8.25c -3.82\niter: 10 22:39:48 -14.841982c -9.93c -4.59c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, 0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +24.783564\nPotential: -14.549751\nExternal: +0.000000\nXC: -25.004962\nEntropy (-ST): -0.067471\nLocal: -0.037099\nSIC: +0.000000\n--------------------------\nFree energy: -14.875718\nExtrapolated: -14.841982\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 6.23092 2.00000\n 0 5 6.23092 2.00000\n 0 6 6.23092 2.00000\n 0 7 13.79846 0.00000\n\n 1 4 7.18413 1.99991\n 1 5 7.18413 1.99991\n 1 6 8.59802 0.03225\n 1 7 8.59802 0.03225\n\n\nFermi level: 8.18692\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 836, 856\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 195.04 MiB\n Calculator: 4.81 MiB\n Density: 2.49 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.89 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.55 MiB\n Arrays psit_nG: 0.63 MiB\n Eigensolver: 0.24 MiB\n Projections: 0.04 MiB\n Projectors: 0.36 MiB\n PW-descriptor: 0.27 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n | Al | \n | .-Al------. \n | / Al / \n |/ / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.075008 2.075008 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.075008 0.000000 2.075008 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.075008 2.075008 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.150015 0.000000 0.000000 18 0.2306\n 2. axis: yes 0.000000 4.150015 0.000000 18 0.2306\n 3. axis: yes 0.000000 0.000000 4.150015 18 0.2306\n\n Lengths: 4.150015 4.150015 4.150015\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2306\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:39:55 -14.879464\niter: 2 22:39:59 -14.883109 -2.62 -0.94\niter: 3 22:40:03 -14.871975 -2.76 -0.96\niter: 4 22:40:08 -14.861344 -3.91 -1.26\niter: 5 22:40:13 -14.861380 -5.65 -2.08\niter: 6 22:40:18 -14.861874c -4.97 -2.07\niter: 7 22:40:21 -14.861850c -5.36 -2.63\niter: 8 22:40:25 -14.861849c -7.28 -3.56\niter: 9 22:40:30 -14.861852c -6.79 -3.44\niter: 10 22:40:35 -14.861852c -7.30 -3.41\niter: 11 22:40:40 -14.861852c -9.44c -3.85\niter: 12 22:40:45 -14.861851c -8.74c -4.03c\n\nConverged after 12 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +6.024647\nPotential: -0.884511\nExternal: +0.000000\nXC: -19.951921\nEntropy (-ST): -0.057798\nLocal: -0.021168\nSIC: +0.000000\n--------------------------\nFree energy: -14.890750\nExtrapolated: -14.861851\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 4.81760 2.00000\n 0 5 4.81760 2.00000\n 0 6 4.81760 2.00000\n 0 7 11.66042 0.00000\n\n 1 4 5.74673 1.99940\n 1 5 5.74673 1.99940\n 1 6 7.21857 0.00269\n 1 7 7.21857 0.00269\n\n\nFermi level: 6.55769\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 48\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1)\n ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0)\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0)\n ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0) ( 0 1 0) ( 0 -1 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1) ( 0 0 -1)\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 1 0 0) (-1 0 0) ( 1 0 0) (-1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1) ( 1 0 0) (-1 0 0)\n\n ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 0 -1) ( 0 0 -1) (-1 0 0) (-1 0 0) ( 0 1 0) ( 0 1 0)\n ( 1 0 0) (-1 0 0) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 1) ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0)\n ( 0 1 0) ( 0 -1 0) ( 0 1 0) ( 0 -1 0) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n4 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 0.00000000 6/27\n 2: 0.33333333 0.33333333 0.00000000 12/27\n 3: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 884, 922\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 195.85 MiB\n Calculator: 4.97 MiB\n Density: 2.55 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.95 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.78 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.64 MiB\n Arrays psit_nG: 0.68 MiB\n Eigensolver: 0.26 MiB\n Projections: 0.04 MiB\n Projectors: 0.38 MiB\n PW-descriptor: 0.28 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n | Al | \n | .---------. \n | / All / \n |/ / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.123838 2.123838 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.123838 0.000000 2.123838 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.123838 2.123838 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.247676 0.000000 0.000000 18 0.2360\n 2. axis: yes 0.000000 4.247676 0.000000 18 0.2360\n 3. axis: yes 0.000000 0.000000 4.247676 18 0.2360\n\n Lengths: 4.247676 4.247676 4.247676\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2360\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:40:52 -14.696924\niter: 2 22:40:57 -14.699422 -2.64 -0.94\niter: 3 22:41:02 -14.679770 -2.91 -0.96\niter: 4 22:41:06 -14.667487 -4.04 -1.28\niter: 5 22:41:10 -14.667584 -5.99 -2.08\niter: 6 22:41:15 -14.667794c -4.99 -2.08\niter: 7 22:41:19 -14.667795c -6.56 -3.69\niter: 8 22:41:24 -14.667794c -7.75c -3.59\niter: 9 22:41:28 -14.667795c -8.79c -3.81\niter: 10 22:41:33 -14.667795c -9.67c -4.06c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, 0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: -0.441729\nPotential: +3.686595\nExternal: +0.000000\nXC: -17.870816\nEntropy (-ST): -0.054761\nLocal: -0.014463\nSIC: +0.000000\n--------------------------\nFree energy: -14.695175\nExtrapolated: -14.667795\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 4.18694 2.00000\n 0 5 4.18694 2.00000\n 0 6 4.18694 2.00000\n 0 7 10.75420 0.00000\n\n 1 4 5.07835 1.99906\n 1 5 5.07835 1.99906\n 1 6 6.63071 0.00077\n 1 7 6.63071 0.00077\n\n\nFermi level: 5.84459\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 16\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.00000000 0.00000000 0.33333333 2/27\n 2: 0.33333333 0.00000000 0.00000000 4/27\n 3: 0.33333333 0.00000000 0.33333333 8/27\n 4: 0.33333333 0.33333333 0.00000000 4/27\n 5: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 694, 708\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 16*16*18 grid\n Fine grid: 32*32*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 32*32*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 196.86 MiB\n Calculator: 4.36 MiB\n Density: 2.01 MiB\n Arrays: 0.91 MiB\n Localized functions: 0.75 MiB\n Mixer: 0.35 MiB\n Hamiltonian: 0.61 MiB\n Arrays: 0.60 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.73 MiB\n Arrays psit_nG: 0.78 MiB\n Eigensolver: 0.21 MiB\n Projections: 0.06 MiB\n Projectors: 0.45 MiB\n PW-descriptor: 0.24 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .--------. \n /| | \n * | | \n |Al | \n | | | \n | .-Al-----. \n |/ Al / \n Al-------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 1.921084 2.025000 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.921084 0.000000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.921084 1.921084 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 3.842167 0.000000 0.000000 16 0.2401\n 2. axis: yes 0.000000 3.842167 0.000000 16 0.2401\n 3. axis: yes 0.000000 0.000000 4.050000 18 0.2250\n\n Lengths: 3.842167 3.842167 4.050000\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2350\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:41:40 -14.732895\niter: 2 22:41:45 -14.740004 -2.60 -0.94\niter: 3 22:41:51 -14.762942 -2.29 -0.96\niter: 4 22:41:56 -14.760523 -3.30 -1.19\niter: 5 22:42:01 -14.760822c -5.55 -2.01\niter: 6 22:42:06 -14.761985c -4.57 -2.13\niter: 7 22:42:12 -14.761976c -6.98 -3.27\niter: 8 22:42:17 -14.761980c -7.54c -3.32\niter: 9 22:42:22 -14.761985c -7.48c -3.59\niter: 10 22:42:27 -14.761985c -9.23c -4.68c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +29.946922\nPotential: -18.554760\nExternal: +0.000000\nXC: -26.098780\nEntropy (-ST): -0.028997\nLocal: -0.040868\nSIC: +0.000000\n--------------------------\nFree energy: -14.776483\nExtrapolated: -14.761985\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.78601 2.00000\n 0 5 6.87607 2.00000\n 0 6 6.87607 2.00000\n 0 7 13.73921 0.00000\n\n 1 4 7.74692 1.97199\n 1 5 7.74692 1.97198\n 1 6 8.89364 0.00147\n 1 7 8.89364 0.00147\n\n\nFermi level: 8.17232\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 16\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.00000000 0.00000000 0.33333333 2/27\n 2: 0.33333333 0.00000000 0.00000000 4/27\n 3: 0.33333333 0.00000000 0.33333333 8/27\n 4: 0.33333333 0.33333333 0.00000000 4/27\n 5: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 737, 756\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 16*16*18 grid\n Fine grid: 32*32*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 32*32*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 196.86 MiB\n Calculator: 4.50 MiB\n Density: 2.05 MiB\n Arrays: 0.91 MiB\n Localized functions: 0.79 MiB\n Mixer: 0.35 MiB\n Hamiltonian: 0.61 MiB\n Arrays: 0.60 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.83 MiB\n Arrays psit_nG: 0.83 MiB\n Eigensolver: 0.22 MiB\n Projections: 0.06 MiB\n Projectors: 0.48 MiB\n PW-descriptor: 0.24 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n * | | \n |Al | \n | | | \n | .--Al-----. \n |/ Al / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 1.973726 2.025000 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.973726 0.000000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.973726 1.973726 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 3.947452 0.000000 0.000000 16 0.2467\n 2. axis: yes 0.000000 3.947452 0.000000 16 0.2467\n 3. axis: yes 0.000000 0.000000 4.050000 18 0.2250\n\n Lengths: 3.947452 3.947452 4.050000\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2393\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:42:34 -14.903323\niter: 2 22:42:39 -14.909242 -2.61 -0.94\niter: 3 22:42:43 -14.919947 -2.44 -0.95\niter: 4 22:42:48 -14.914320 -3.57 -1.22\niter: 5 22:42:53 -14.914598c -5.26 -2.03\niter: 6 22:42:58 -14.915408c -4.55 -2.15\niter: 7 22:43:03 -14.915408c -6.67 -3.36\niter: 8 22:43:08 -14.915408c -7.91c -3.62\niter: 9 22:43:13 -14.915410c -7.98c -3.72\niter: 10 22:43:18 -14.915410c -9.88c -4.70c\n\nConverged after 10 iterations.\n\nDipole moment: (0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +21.332754\nPotential: -12.094956\nExternal: +0.000000\nXC: -24.099721\nEntropy (-ST): -0.039257\nLocal: -0.033858\nSIC: +0.000000\n--------------------------\nFree energy: -14.935039\nExtrapolated: -14.915410\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.63543 2.00000\n 0 5 6.16057 2.00000\n 0 6 6.16057 2.00000\n 0 7 13.17416 0.00000\n\n 1 4 7.07724 1.99853\n 1 5 7.07724 1.99853\n 1 6 8.35185 0.00789\n 1 7 8.35185 0.00789\n\n\nFermi level: 7.79870\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 16\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.00000000 0.00000000 0.33333333 2/27\n 2: 0.33333333 0.00000000 0.00000000 4/27\n 3: 0.33333333 0.00000000 0.33333333 8/27\n 4: 0.33333333 0.33333333 0.00000000 4/27\n 5: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 807, 832\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 196.86 MiB\n Calculator: 5.28 MiB\n Density: 2.47 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.87 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 2.03 MiB\n Arrays psit_nG: 0.91 MiB\n Eigensolver: 0.24 MiB\n Projections: 0.06 MiB\n Projectors: 0.53 MiB\n PW-descriptor: 0.30 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n | Al | \n | .---------. \n | / AlAl / \n |/ / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.075008 2.025000 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.075008 0.000000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.075008 2.075008 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.150015 0.000000 0.000000 18 0.2306\n 2. axis: yes 0.000000 4.150015 0.000000 18 0.2306\n 3. axis: yes 0.000000 0.000000 4.050000 18 0.2250\n\n Lengths: 4.150015 4.150015 4.050000\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2287\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:43:26 -14.919077\niter: 2 22:43:31 -14.923047 -2.62 -0.94\niter: 3 22:43:37 -14.915401 -2.70 -0.95\niter: 4 22:43:42 -14.905669 -3.88 -1.26\niter: 5 22:43:48 -14.905607 -5.49 -2.08\niter: 6 22:43:54 -14.906325c -4.49 -2.12\niter: 7 22:44:00 -14.906256c -5.95 -2.57\niter: 8 22:44:06 -14.906257c -6.95 -3.71\niter: 9 22:44:12 -14.906257c -7.39 -3.31\niter: 10 22:44:19 -14.906257c -8.75c -4.59c\n\nConverged after 10 iterations.\n\nDipole moment: (-0.000000, 0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +8.698013\nPotential: -2.831815\nExternal: +0.000000\nXC: -20.724898\nEntropy (-ST): -0.048849\nLocal: -0.023133\nSIC: +0.000000\n--------------------------\nFree energy: -14.930681\nExtrapolated: -14.906257\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 4.87930 2.00000\n 0 5 4.87930 2.00000\n 0 6 5.37182 2.00000\n 0 7 11.70552 0.00000\n\n 1 4 5.84939 1.99972\n 1 5 5.84939 1.99972\n 1 6 7.44240 0.00171\n 1 7 7.44240 0.00171\n\n\nFermi level: 6.73590\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 16\n\n ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 1 0 0) ( 1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0) ( 0 -1 0)\n (-1 0 0) (-1 0 0) ( 1 0 0) ( 1 0 0) (-1 0 0) (-1 0 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n (-1 0 0) (-1 0 0) (-1 0 0) (-1 0 0)\n ( 0 1 0) ( 0 1 0) ( 0 -1 0) ( 0 -1 0)\n ( 0 0 1) ( 0 0 -1) ( 0 0 1) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.00000000 0.00000000 0.33333333 2/27\n 2: 0.33333333 0.00000000 0.00000000 4/27\n 3: 0.33333333 0.00000000 0.33333333 8/27\n 4: 0.33333333 0.33333333 0.00000000 4/27\n 5: 0.33333333 0.33333333 0.33333333 8/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 848, 872\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 198.45 MiB\n Calculator: 5.40 MiB\n Density: 2.51 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.91 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.78 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 2.12 MiB\n Arrays psit_nG: 0.96 MiB\n Eigensolver: 0.25 MiB\n Projections: 0.06 MiB\n Projectors: 0.55 MiB\n PW-descriptor: 0.30 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n .---------. \n /| | \n / | | \n * | | \n | Al | \n | .---------. \n | / All / \n |/ / \n Al--------* \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.000000 2.123838 2.025000 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.123838 0.000000 2.025000 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.123838 2.123838 0.000000 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.247676 0.000000 0.000000 18 0.2360\n 2. axis: yes 0.000000 4.247676 0.000000 18 0.2360\n 3. axis: yes 0.000000 0.000000 4.050000 18 0.2250\n\n Lengths: 4.247676 4.247676 4.050000\n Angles: 90.000000 90.000000 90.000000\n\nEffective grid spacing dv^(1/3) = 0.2323\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:44:29 -14.812413\niter: 2 22:44:36 -14.815910 -2.62 -0.94\niter: 3 22:44:42 -14.803239 -2.79 -0.96\niter: 4 22:44:48 -14.791922 -3.92 -1.26\niter: 5 22:44:55 -14.792019 -5.77 -2.10\niter: 6 22:45:01 -14.792358c -4.93 -2.07\niter: 7 22:45:06 -14.792358c -6.44 -3.28\niter: 8 22:45:12 -14.792357c -8.08c -3.65\niter: 9 22:45:18 -14.792358c -7.22 -3.66\niter: 10 22:45:24 -14.792358c -8.01c -3.64\niter: 11 22:45:30 -14.792358c -9.38c -4.32c\n\nConverged after 11 iterations.\n\nDipole moment: (-0.000000, 0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +4.244555\nPotential: +0.324641\nExternal: +0.000000\nXC: -19.309666\nEntropy (-ST): -0.064765\nLocal: -0.019506\nSIC: +0.000000\n--------------------------\nFree energy: -14.824741\nExtrapolated: -14.792358\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 4.30602 2.00000\n 0 5 4.30602 2.00000\n 0 6 5.25459 1.99983\n 0 7 10.83679 0.00000\n\n 1 4 5.28608 1.99977\n 1 5 5.28608 1.99977\n 1 6 7.05846 0.00035\n 1 7 7.05846 0.00035\n\n\nFermi level: 6.19264\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 12\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 0 1) ( 1 0 0) ( 0 1 0)\n ( 0 0 1) ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 1 0) ( 1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 -1 0) (-1 0 0) ( 0 0 -1) (-1 0 0) ( 0 0 -1) ( 0 -1 0)\n (-1 0 0) ( 0 -1 0) (-1 0 0) ( 0 0 -1) ( 0 -1 0) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 -0.33333333 6/27\n 2: 0.33333333 0.00000000 0.00000000 6/27\n 3: 0.33333333 0.33333333 -0.33333333 6/27\n 4: 0.33333333 0.33333333 0.00000000 6/27\n 5: 0.33333333 0.33333333 0.33333333 2/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 762, 774\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 198.71 MiB\n Calculator: 5.10 MiB\n Density: 2.41 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.81 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.92 MiB\n Arrays psit_nG: 0.85 MiB\n Eigensolver: 0.22 MiB\n Projections: 0.06 MiB\n Projectors: 0.49 MiB\n PW-descriptor: 0.29 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n \n \n \n \n Al \n Al \n \n Al \n Al \n \n \n \n \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al -0.208415 1.915423 1.915423 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.915423 -0.208415 1.915423 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.915423 1.915423 -0.208415 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.039261 -0.208415 -0.208415 18 0.2225\n 2. axis: yes -0.208415 4.039261 -0.208415 18 0.2225\n 3. axis: yes -0.208415 -0.208415 4.039261 18 0.2225\n\n Lengths: 4.050000 4.050000 4.050000\n Angles: 95.739170 95.739170 95.739170\n\nEffective grid spacing dv^(1/3) = 0.2238\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:45:39 -14.253273\niter: 2 22:45:44 -14.261390 -2.56 -0.94\niter: 3 22:45:49 -14.277583 -2.52 -0.96\niter: 4 22:45:56 -14.275510 -3.84 -1.28\niter: 5 22:46:02 -14.275479c -5.56 -2.24\niter: 6 22:46:07 -14.276006c -4.67 -2.26\niter: 7 22:46:14 -14.276016c -7.21 -2.90\niter: 8 22:46:19 -14.276022c -6.81 -3.39\niter: 9 22:46:25 -14.276021c -8.57c -3.60\niter: 10 22:46:31 -14.276021c -10.57c -4.52c\n\nConverged after 10 iterations.\n\nDipole moment: (0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +22.369503\nPotential: -13.123187\nExternal: +0.000000\nXC: -23.447226\nEntropy (-ST): -0.086104\nLocal: -0.032058\nSIC: +0.000000\n--------------------------\nFree energy: -14.319073\nExtrapolated: -14.276021\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.74742 2.00000\n 0 5 5.74742 2.00000\n 0 6 5.74742 2.00000\n 0 7 11.05858 0.00000\n\n 1 4 6.01298 1.99996\n 1 5 7.51707 0.02779\n 1 6 8.20211 0.00003\n 1 7 8.20211 0.00003\n\n\nFermi level: 7.09085\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 12\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 0 1) ( 1 0 0) ( 0 1 0)\n ( 0 0 1) ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 1 0) ( 1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 -1 0) (-1 0 0) ( 0 0 -1) (-1 0 0) ( 0 0 -1) ( 0 -1 0)\n (-1 0 0) ( 0 -1 0) (-1 0 0) ( 0 0 -1) ( 0 -1 0) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 -0.33333333 6/27\n 2: 0.33333333 0.00000000 0.00000000 6/27\n 3: 0.33333333 0.33333333 -0.33333333 6/27\n 4: 0.33333333 0.33333333 0.00000000 6/27\n 5: 0.33333333 0.33333333 0.33333333 2/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 776, 786\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 198.74 MiB\n Calculator: 5.14 MiB\n Density: 2.43 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.83 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.94 MiB\n Arrays psit_nG: 0.86 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.06 MiB\n Projectors: 0.50 MiB\n PW-descriptor: 0.29 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n \n \n \n \n Al \n Al \n Al \n Al \n \n \n \n \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al -0.102616 1.972392 1.972392 ( 0.0000, 0.0000, 0.0000)\n 2 Al 1.972392 -0.102616 1.972392 ( 0.0000, 0.0000, 0.0000)\n 3 Al 1.972392 1.972392 -0.102616 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.047399 -0.102616 -0.102616 18 0.2244\n 2. axis: yes -0.102616 4.047399 -0.102616 18 0.2244\n 3. axis: yes -0.102616 -0.102616 4.047399 18 0.2244\n\n Lengths: 4.050000 4.050000 4.050000\n Angles: 92.865984 92.865984 92.865984\n\nEffective grid spacing dv^(1/3) = 0.2247\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:46:40 -14.825070\niter: 2 22:46:46 -14.830281 -2.61 -0.94\niter: 3 22:46:51 -14.834036 -2.59 -0.95\niter: 4 22:46:56 -14.827853 -3.93 -1.28\niter: 5 22:47:01 -14.827824 -5.51 -2.13\niter: 6 22:47:06 -14.828567c -4.62 -2.20\niter: 7 22:47:11 -14.828567c -7.14 -3.39\niter: 8 22:47:16 -14.828567c -7.99c -3.75\niter: 9 22:47:21 -14.828566c -8.51c -3.64\niter: 10 22:47:27 -14.828566c -10.22c -4.33c\n\nConverged after 10 iterations.\n\nDipole moment: (0.000000, 0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +15.802906\nPotential: -8.007940\nExternal: +0.000000\nXC: -22.569922\nEntropy (-ST): -0.048849\nLocal: -0.029186\nSIC: +0.000000\n--------------------------\nFree energy: -14.852991\nExtrapolated: -14.828566\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.55442 2.00000\n 0 5 5.55442 2.00000\n 0 6 5.55442 2.00000\n 0 7 11.81924 0.00000\n\n 1 4 5.97050 1.99999\n 1 5 7.42040 0.20799\n 1 6 8.63723 0.00000\n 1 7 8.63723 0.00000\n\n\nFermi level: 7.20504\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 12\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 0 1) ( 1 0 0) ( 0 1 0)\n ( 0 0 1) ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 1 0) ( 1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 -1 0) (-1 0 0) ( 0 0 -1) (-1 0 0) ( 0 0 -1) ( 0 -1 0)\n (-1 0 0) ( 0 -1 0) (-1 0 0) ( 0 0 -1) ( 0 -1 0) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 -0.33333333 6/27\n 2: 0.33333333 0.00000000 0.00000000 6/27\n 3: 0.33333333 0.33333333 -0.33333333 6/27\n 4: 0.33333333 0.33333333 0.00000000 6/27\n 5: 0.33333333 0.33333333 0.33333333 2/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 769, 788\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 199.47 MiB\n Calculator: 5.15 MiB\n Density: 2.43 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.83 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.94 MiB\n Arrays psit_nG: 0.87 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.06 MiB\n Projectors: 0.50 MiB\n PW-descriptor: 0.29 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n \n \n \n \n Al \n Al \n Al \n Al \n \n \n \n \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.100075 2.073801 2.073801 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.073801 0.100075 2.073801 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.073801 2.073801 0.100075 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.047526 0.100075 0.100075 18 0.2245\n 2. axis: yes 0.100075 4.047526 0.100075 18 0.2245\n 3. axis: yes 0.100075 0.100075 4.047526 18 0.2245\n\n Lengths: 4.050000 4.050000 4.050000\n Angles: 87.134016 87.134016 87.134016\n\nEffective grid spacing dv^(1/3) = 0.2247\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:47:35 -14.919271\niter: 2 22:47:40 -14.924183 -2.61 -0.93\niter: 3 22:47:45 -14.925894 -2.58 -0.95\niter: 4 22:47:51 -14.918258 -3.85 -1.27\niter: 5 22:47:56 -14.918454 -5.54 -2.06\niter: 6 22:48:01 -14.919068c -4.75 -2.00\niter: 7 22:48:06 -14.919062c -6.59 -3.08\niter: 8 22:48:12 -14.919072c -6.40 -3.13\niter: 9 22:48:18 -14.919070c -7.92c -3.40\niter: 10 22:48:23 -14.919070c -9.67c -3.80\niter: 11 22:48:30 -14.919071c -7.85c -3.79\niter: 12 22:48:36 -14.919070c -9.42c -4.39c\n\nConverged after 12 iterations.\n\nDipole moment: (-0.000000, -0.000000, 0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +15.399146\nPotential: -7.723286\nExternal: +0.000000\nXC: -22.549734\nEntropy (-ST): -0.030010\nLocal: -0.030192\nSIC: +0.000000\n--------------------------\nFree energy: -14.934075\nExtrapolated: -14.919070\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.54788 2.00000\n 0 5 5.54788 2.00000\n 0 6 5.54788 2.00000\n 0 7 11.92279 0.00000\n\n 1 4 6.14720 1.99999\n 1 5 7.68339 0.08558\n 1 6 8.32283 0.00015\n 1 7 8.32283 0.00015\n\n\nFermi level: 7.37261\n\nNo gap\nSystem changes: cell, positions \n\nInitialize ...\n\nspecies:\n Al:\n name: Aluminium\n id: 0292cae29f5d6237e50f6abdd43a7bdd\n Z: 13.0\n valence: 3\n core: 10\n charge: 0.0\n file: /srv/conda/envs/notebook/share/gpaw/Al.PBE.gz\n compensation charges: {type: gauss,\n rc: 0.34,\n lmax: 2}\n cutoffs: {filter: 1.91,\n core: 2.36}\n valence states:\n # energy rcut\n - 3s(2.00) -7.753 1.085\n - 3p(1.00) -2.712 1.085\n - s 19.459 1.085\n - p 24.499 1.085\n - d 0.000 1.085\n \n # Using partial waves for Al as LCAO basis\n\nReference energy: -26413.693060 # eV\n\nSpin-paired calculation\n\nConvergence criteria:\n Maximum [total energy] change in last 3 cyles: 0.0005 eV / valence electron\n Maximum integral of absolute [dens]ity change: 0.0001 electrons / valence electron\n Maximum integral of absolute [eigenst]ate change: 4e-08 eV^2 / valence electron\n Maximum number of scf [iter]ations: 333\n (Square brackets indicate name in SCF output, whereas a 'c' in\n the SCF output indicates the quantity has converged.)\n\nSymmetries present (total): 12\n\n ( 1 0 0) ( 1 0 0) ( 0 1 0) ( 0 1 0) ( 0 0 1) ( 0 0 1)\n ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 0 1) ( 1 0 0) ( 0 1 0)\n ( 0 0 1) ( 0 1 0) ( 0 0 1) ( 1 0 0) ( 0 1 0) ( 1 0 0)\n\n ( 0 0 -1) ( 0 0 -1) ( 0 -1 0) ( 0 -1 0) (-1 0 0) (-1 0 0)\n ( 0 -1 0) (-1 0 0) ( 0 0 -1) (-1 0 0) ( 0 0 -1) ( 0 -1 0)\n (-1 0 0) ( 0 -1 0) (-1 0 0) ( 0 0 -1) ( 0 -1 0) ( 0 0 -1)\n\n27 k-points: 3 x 3 x 3 Monkhorst-Pack grid\n6 k-points in the irreducible part of the Brillouin zone\n k-points in crystal coordinates weights\n 0: 0.00000000 0.00000000 0.00000000 1/27\n 1: 0.33333333 0.00000000 -0.33333333 6/27\n 2: 0.33333333 0.00000000 0.00000000 6/27\n 3: 0.33333333 0.33333333 -0.33333333 6/27\n 4: 0.33333333 0.33333333 0.00000000 6/27\n 5: 0.33333333 0.33333333 0.33333333 2/27\n\nWave functions: Plane wave expansion\n Cutoff energy: 300.000 eV\n Number of coefficients (min, max): 760, 787\n Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n Using FFTW library\n ScaLapack parameters: grid=1x1, blocksize=None\n Wavefunction extrapolation:\n Improved wavefunction reuse through dual PAW basis \n\nOccupation numbers: Fermi-Dirac:\n width: 0.1000 # eV\n \n\nEigensolver\n Davidson(niter=2) \n\nDensities:\n Coarse grid: 18*18*18 grid\n Fine grid: 36*36*36 grid\n Total Charge: 0.000000 \n\nDensity mixing:\n Method: separate\n Backend: pulay\n Linear mixing parameter: 0.05\n old densities: 5\n Damping of long wavelength oscillations: 50 \n\nHamiltonian:\n XC and Coulomb potentials evaluated on a 36*36*36 grid\n Using the PBE Exchange-Correlation functional\n External potential:\n NoExternalPotential\n \n\nXC parameters: PBE with 2 nearest neighbor stencil\n\nMemory estimate:\n Process memory now: 200.70 MiB\n Calculator: 5.13 MiB\n Density: 2.42 MiB\n Arrays: 1.16 MiB\n Localized functions: 0.81 MiB\n Mixer: 0.44 MiB\n Hamiltonian: 0.77 MiB\n Arrays: 0.76 MiB\n XC: 0.00 MiB\n Poisson: 0.00 MiB\n vbar: 0.02 MiB\n Wavefunctions: 1.94 MiB\n Arrays psit_nG: 0.86 MiB\n Eigensolver: 0.23 MiB\n Projections: 0.06 MiB\n Projectors: 0.50 MiB\n PW-descriptor: 0.29 MiB\n\nTotal number of cores used: 1\nOpenMP threads: 16\n\nNumber of atoms: 4\nNumber of atomic orbitals: 16\nNumber of bands in calculation: 12\nNumber of valence electrons: 12\nBands to converge: occupied\n\n... initialized\n\nInitializing position-dependent things.\n\nDensity initialized from atomic densities\nCreating initial wave functions:\n 12 bands from LCAO basis set\n\n \n \n \n \n Al \n Al \n Al \n \n Al \n \n \n \n \n\nPositions:\n 0 Al 0.000000 0.000000 0.000000 ( 0.0000, 0.0000, 0.0000)\n 1 Al 0.198128 2.119212 2.119212 ( 0.0000, 0.0000, 0.0000)\n 2 Al 2.119212 0.198128 2.119212 ( 0.0000, 0.0000, 0.0000)\n 3 Al 2.119212 2.119212 0.198128 ( 0.0000, 0.0000, 0.0000)\n\nUnit cell:\n periodic x y z points spacing\n 1. axis: yes 4.040296 0.198128 0.198128 18 0.2229\n 2. axis: yes 0.198128 4.040296 0.198128 18 0.2229\n 3. axis: yes 0.198128 0.198128 4.040296 18 0.2229\n\n Lengths: 4.050000 4.050000 4.050000\n Angles: 84.260830 84.260830 84.260830\n\nEffective grid spacing dv^(1/3) = 0.2239\n\n iter time total log10-change:\n energy eigst dens\niter: 1 22:48:45 -14.617275\niter: 2 22:48:51 -14.621858 -2.58 -0.92\niter: 3 22:48:56 -14.622996c -2.48 -0.93\niter: 4 22:49:02 -14.611982 -3.79 -1.34\niter: 5 22:49:07 -14.612650 -5.20 -1.90\niter: 6 22:49:13 -14.613003c -4.86 -2.02\niter: 7 22:49:18 -14.613004c -6.47 -3.00\niter: 8 22:49:24 -14.613019c -6.42 -3.07\niter: 9 22:49:30 -14.613019c -8.00c -3.70\niter: 10 22:49:36 -14.613019c -9.07c -3.97\niter: 11 22:49:42 -14.613019c -8.48c -4.06c\n\nConverged after 11 iterations.\n\nDipole moment: (-0.000000, -0.000000, -0.000000) |e|*Ang\n\nEnergy contributions relative to reference atoms: (reference = -26413.693060)\n\nKinetic: +20.022062\nPotential: -11.287530\nExternal: +0.000000\nXC: -23.298354\nEntropy (-ST): -0.033644\nLocal: -0.032376\nSIC: +0.000000\n--------------------------\nFree energy: -14.629841\nExtrapolated: -14.613019\n\nShowing only first 2 kpts\n Kpt Band Eigenvalues Occupancy\n 0 4 5.69327 2.00000\n 0 5 5.69327 2.00000\n 0 6 5.69327 2.00000\n 0 7 11.44751 0.00000\n\n 1 4 6.31998 1.99994\n 1 5 7.72451 0.05504\n 1 6 7.72451 0.05504\n 1 7 8.02631 0.00276\n\n\nFermi level: 7.36802\n\nNo gap\n" + }, + { + "data": { + "text/plain": "{'energy': {'s_e_0': -14.93666639635226,\n 's_01_e_m0_05000': -14.509157650657773,\n 's_01_e_m0_02500': -14.841982287128575,\n 's_01_e_0_02500': -14.86185138418095,\n 's_01_e_0_05000': -14.667794842757818,\n 's_08_e_m0_05000': -14.761984598633523,\n 's_08_e_m0_02500': -14.915410384618987,\n 's_08_e_0_02500': -14.906256779085401,\n 's_08_e_0_05000': -14.792358225770455,\n 's_23_e_m0_05000': -14.276020694675015,\n 's_23_e_m0_02500': -14.82856618062893,\n 's_23_e_0_02500': -14.919070455416568,\n 's_23_e_0_05000': -14.613019415010102}}" + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result_dict = evaluate_with_ase(\n", + " task_dict=task_dict, ase_calculator=GPAW(xc=\"PBE\", mode=PW(300), kpts=(3, 3, 3))\n", + ")\n", + "result_dict" + ] + }, + { + "cell_type": "markdown", + "id": "064c0b0c-c69d-4457-b32d-1179036a6ac9", + "metadata": {}, + "source": "The atomistic structures are evaluated with the `evaluate_with_ase()` function, which returns the `result_dict`. This \n`result_dict` in analogy to the `task_dict` contains the same keys as well as the energies calculated with the \n[GPAW](https://wiki.fysik.dtu.dk/gpaw/) simulation code. Finally, the `result_dict` is provided as an input to the \n`analyse_structures()` function to calculate the corresponding elastic constants: " + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "245a78c5-8895-4f4f-b813-58fc0b9ea186", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "{'elastic_matrix': array([[98.43569593, 63.17413032, 63.17413032, 0. , 0. ,\n 0. ],\n [63.17413032, 98.43569593, 63.17413032, 0. , 0. ,\n 0. ],\n [63.17413032, 63.17413032, 98.43569593, 0. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 84.66136139, 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 84.66136139,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0. ,\n 84.66136139]]),\n 'elastic_matrix_inverse': array([[ 0.02038923, -0.00797026, -0.00797026, 0. , 0. ,\n 0. ],\n [-0.00797026, 0.02038923, -0.00797026, 0. , 0. ,\n 0. ],\n [-0.00797026, -0.00797026, 0.02038923, 0. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0.01181176, 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0.01181176,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0. ,\n 0.01181176]]),\n 'bulkmodul_voigt': 74.92798552184198,\n 'bulkmodul_reuss': 74.92798552184202,\n 'bulkmodul_hill': 74.927985521842,\n 'shearmodul_voigt': 57.84912995743317,\n 'shearmodul_reuss': 33.58561744891993,\n 'shearmodul_hill': 45.71737370317655,\n 'youngsmodul_voigt': 138.02583917911684,\n 'youngsmodul_reuss': 87.65940807073069,\n 'youngsmodul_hill': 113.97206957810407,\n 'poissonsratio_voigt': 0.19298111553864067,\n 'poissonsratio_reuss': 0.3050140912855198,\n 'poissonsratio_hill': 0.24648531123065173,\n 'AVR': 26.536424277175126,\n 'elastic_matrix_eigval': EigResult(eigenvalues=array([ 35.26156561, 224.78395657, 35.26156561, 84.66136139,\n 84.66136139, 84.66136139]), eigenvectors=array([[-0.81649658, 0.57735027, 0.40373959, 0. , 0. ,\n 0. ],\n [ 0.40824829, 0.57735027, -0.81648004, 0. , 0. ,\n 0. ],\n [ 0.40824829, 0.57735027, 0.41274045, 0. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 1. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 1. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0. ,\n 1. ]]))}" + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "elastic_dict = workflow.analyse_structures(output_dict=result_dict)\n", + "elastic_dict" + ] + }, + { + "cell_type": "markdown", + "id": "43fe5df0-4142-464b-ab13-99e52868e57f", + "metadata": {}, + "source": "The bulk modulus calculated from the elastic constants `C11` and `C12` based on a strain of +/- 5% is calculated with \nthe [GPAW](https://wiki.fysik.dtu.dk/gpaw/) simulation code to be 74.9GPa. This differs from the bulk modulus calculated\nfrom the Equation of State above by 2.6GPa. In comparison to the experimental bulk modulus for Aluminium which is\n[reported to be 76GPa](https://periodictable.com/Elements/013/data.html) the calculation based on the elastic constants\nseem to be more precise, still this is more likely related to error cancellation. In general elastic properties calculated\nfrom density functional theory are expected to have errors of about 5-10% unless carefully converged." + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} \ No newline at end of file diff --git a/notebooks/free_energy_calculation.ipynb b/notebooks/free_energy_calculation.ipynb index 8b545838..8a048c23 100644 --- a/notebooks/free_energy_calculation.ipynb +++ b/notebooks/free_energy_calculation.ipynb @@ -26,14 +26,24 @@ "source": [ "from ase.build import bulk\n", "import numpy as np\n", - "from atomistics.workflows import optimize_positions_and_volume, LangevinWorkflow, PhonopyWorkflow, QuasiHarmonicWorkflow\n", - "from atomistics.calculators import evaluate_with_lammps_library, evaluate_with_lammps, get_potential_by_name, evaluate_with_hessian\n", + "from atomistics.workflows import (\n", + " optimize_positions_and_volume,\n", + " LangevinWorkflow,\n", + " PhonopyWorkflow,\n", + " QuasiHarmonicWorkflow,\n", + ")\n", + "from atomistics.calculators import (\n", + " evaluate_with_lammps_library,\n", + " evaluate_with_lammps,\n", + " get_potential_by_name,\n", + " evaluate_with_hessian,\n", + ")\n", "from pylammpsmpi import LammpsASELibrary\n", "from phonopy.units import VaspToTHz\n", "from tqdm import tqdm\n", "import matplotlib.pyplot as plt\n", "import pandas\n", - "import scipy.constants " + "import scipy.constants" ] }, { @@ -52,16 +62,17 @@ "outputs": [], "source": [ "structure_bulk = bulk(\"Al\", cubic=True)\n", - "df_pot_selected = pandas.DataFrame({\n", - " \"Config\": [[\n", - " \"pair_style morse/smooth/linear 9.0\",\n", - " \"pair_coeff * * 0.5 1.8 2.95\"\n", - " ]],\n", - " \"Filename\": [[]],\n", - " \"Model\": [\"Morse\"],\n", - " \"Name\": [\"Morse\"],\n", - " \"Species\": [[\"Al\"]],\n", - "})" + "df_pot_selected = pandas.DataFrame(\n", + " {\n", + " \"Config\": [\n", + " [\"pair_style morse/smooth/linear 9.0\", \"pair_coeff * * 0.5 1.8 2.95\"]\n", + " ],\n", + " \"Filename\": [[]],\n", + " \"Model\": [\"Morse\"],\n", + " \"Name\": [\"Morse\"],\n", + " \"Species\": [[\"Al\"]],\n", + " }\n", + ")" ] }, { @@ -372,9 +383,19 @@ ], "source": [ "plt.title(\"Helmholtz Free Energy\")\n", - "plt.plot(term_base_dict['temperatures'], term_base_dict['free_energy'], label=\"Harmonic\")\n", - "plt.plot(term_qh_dict['temperatures'], term_qh_dict['free_energy'], label=\"Quasi-Harmonic (qm)\")\n", - "plt.plot(term_qh_cl_dict['temperatures'], term_qh_cl_dict['free_energy'], label=\"Quasi-Harmonic (cl)\")\n", + "plt.plot(\n", + " term_base_dict[\"temperatures\"], term_base_dict[\"free_energy\"], label=\"Harmonic\"\n", + ")\n", + "plt.plot(\n", + " term_qh_dict[\"temperatures\"],\n", + " term_qh_dict[\"free_energy\"],\n", + " label=\"Quasi-Harmonic (qm)\",\n", + ")\n", + "plt.plot(\n", + " term_qh_cl_dict[\"temperatures\"],\n", + " term_qh_cl_dict[\"free_energy\"],\n", + " label=\"Quasi-Harmonic (cl)\",\n", + ")\n", "plt.xlabel(\"Temperature (K)\")\n", "plt.ylabel(\"Helmholtz Free Energy (eV)\")\n", "plt.legend()" @@ -409,8 +430,10 @@ ], "source": [ "plt.title(\"Entropy\")\n", - "plt.plot(term_base_dict['temperatures'], term_base_dict['entropy'], label=\"harmonic\")\n", - "plt.plot(term_qh_dict['temperatures'], term_qh_dict['entropy'], label=\"quasi-harmonic (qm)\")\n", + "plt.plot(term_base_dict[\"temperatures\"], term_base_dict[\"entropy\"], label=\"harmonic\")\n", + "plt.plot(\n", + " term_qh_dict[\"temperatures\"], term_qh_dict[\"entropy\"], label=\"quasi-harmonic (qm)\"\n", + ")\n", "plt.xlabel(\"Temperature (K)\")\n", "plt.ylabel(\"Entropy (J/K/mol)\")\n", "plt.legend()" @@ -445,9 +468,18 @@ ], "source": [ "plt.title(\"Heat Capacity\")\n", - "plt.plot(term_base_dict['temperatures'], term_base_dict['heat_capacity'], label=\"harmonic\")\n", - "plt.plot(term_qh_dict['temperatures'], term_qh_dict['heat_capacity'], label=\"quasi-harmonic\")\n", - "plt.axhline(3 * scipy.constants.Boltzmann * scipy.constants.Avogadro * len(structure_opt), color=\"black\", linestyle=\"--\", label=\"$3Nk_B$\")\n", + "plt.plot(\n", + " term_base_dict[\"temperatures\"], term_base_dict[\"heat_capacity\"], label=\"harmonic\"\n", + ")\n", + "plt.plot(\n", + " term_qh_dict[\"temperatures\"], term_qh_dict[\"heat_capacity\"], label=\"quasi-harmonic\"\n", + ")\n", + "plt.axhline(\n", + " 3 * scipy.constants.Boltzmann * scipy.constants.Avogadro * len(structure_opt),\n", + " color=\"black\",\n", + " linestyle=\"--\",\n", + " label=\"$3Nk_B$\",\n", + ")\n", "plt.xlabel(\"Temperature (K)\")\n", "plt.ylabel(\"Heat Capacity (J/K/mol)\")\n", "plt.legend()" @@ -496,8 +528,8 @@ "metadata": {}, "outputs": [], "source": [ - "lattice_constant_lst = np.array(term_qh_dict['volumes']) ** (1/3)\n", - "temperature_lst = term_qh_dict['temperatures']" + "lattice_constant_lst = np.array(term_qh_dict[\"volumes\"]) ** (1 / 3)\n", + "temperature_lst = term_qh_dict[\"temperatures\"]" ] }, { @@ -560,7 +592,9 @@ "free_energy_lst, eng_lambda_dependence_lst = [], []\n", "for lattice_constant, temperature in zip(lattice_constant_lst, temperature_lst):\n", " structure = bulk(\"Al\", a=lattice_constant, cubic=True).repeat([3, 3, 3])\n", - " equilibrium_lammps = evaluate_with_lammps(task_dict={\"calc_energy\": structure}, potential_dataframe=df_pot_selected)['energy']\n", + " equilibrium_lammps = evaluate_with_lammps(\n", + " task_dict={\"calc_energy\": structure}, potential_dataframe=df_pot_selected\n", + " )[\"energy\"]\n", " workflow_fix = PhonopyWorkflow(\n", " structure=structure,\n", " interaction_range=10,\n", @@ -577,7 +611,7 @@ " )\n", " workflow_fix.analyse_structures(output_dict=result_dict)\n", " energy_pot_all_lst, energy_mean_lst, energy_kin_all_lst = [], [], []\n", - " for lambda_parameter in lambda_lst: \n", + " for lambda_parameter in lambda_lst:\n", " thermo_eng_pot_lst, thermo_eng_kin_lst = [], []\n", " workflow_md_thermo = LangevinWorkflow(\n", " structure=structure,\n", @@ -610,10 +644,18 @@ " lmp=lmp,\n", " )\n", " result_dict = {\n", - " \"forces\": {0: (1-lambda_parameter) * hessian_dict[\"forces\"][0] + lambda_parameter * lammps_dict[\"forces\"][0]},\n", - " \"energy\": {0: (1-lambda_parameter) * hessian_dict[\"energy\"][0] + lambda_parameter * (lammps_dict[\"energy\"][0] - equilibrium_lammps)},\n", + " \"forces\": {\n", + " 0: (1 - lambda_parameter) * hessian_dict[\"forces\"][0]\n", + " + lambda_parameter * lammps_dict[\"forces\"][0]\n", + " },\n", + " \"energy\": {\n", + " 0: (1 - lambda_parameter) * hessian_dict[\"energy\"][0]\n", + " + lambda_parameter * (lammps_dict[\"energy\"][0] - equilibrium_lammps)\n", + " },\n", " }\n", - " eng_pot, eng_kin = workflow_md_thermo.analyse_structures(output_dict=result_dict)\n", + " eng_pot, eng_kin = workflow_md_thermo.analyse_structures(\n", + " output_dict=result_dict\n", + " )\n", " thermo_eng_pot_lst.append(eng_pot)\n", " thermo_eng_kin_lst.append(eng_kin)\n", " lmp.close()\n", @@ -622,7 +664,9 @@ " energy_pot_all_lst.append(thermo_eng_pot_lst)\n", " energy_kin_all_lst.append(thermo_eng_kin_lst)\n", " eng_lambda_dependence_lst.append(np.array(energy_mean_lst) / len(structure) * 1000)\n", - " fit = np.poly1d(np.polyfit(lambda_lst, np.array(energy_mean_lst) / len(structure) * 1000, 3))\n", + " fit = np.poly1d(\n", + " np.polyfit(lambda_lst, np.array(energy_mean_lst) / len(structure) * 1000, 3)\n", + " )\n", " integral = np.polyint(fit)\n", " free_energy_lst.append(integral(1.0) - integral(0.0))" ] @@ -672,9 +716,17 @@ ], "source": [ "plt.title(\"Helmholtz Free Energy\")\n", - "plt.plot(term_base_dict['temperatures'], term_base_dict['free_energy'], label=\"Harmonic\")\n", - "plt.plot(term_qh_dict['temperatures'], term_qh_dict['free_energy'], label=\"Quasi-Harmonic\")\n", - "plt.plot(term_qh_dict['temperatures'], term_qh_dict['free_energy'] - np.array(free_energy_lst) / 1000, label=\"Thermodynamic Integration\")\n", + "plt.plot(\n", + " term_base_dict[\"temperatures\"], term_base_dict[\"free_energy\"], label=\"Harmonic\"\n", + ")\n", + "plt.plot(\n", + " term_qh_dict[\"temperatures\"], term_qh_dict[\"free_energy\"], label=\"Quasi-Harmonic\"\n", + ")\n", + "plt.plot(\n", + " term_qh_dict[\"temperatures\"],\n", + " term_qh_dict[\"free_energy\"] - np.array(free_energy_lst) / 1000,\n", + " label=\"Thermodynamic Integration\",\n", + ")\n", "plt.xlabel(\"Temperature (K)\")\n", "plt.ylabel(\"Helmholtz Free Energy (eV)\")\n", "plt.legend()" diff --git a/notebooks/lammps_workflows.ipynb b/notebooks/lammps_workflows.ipynb index 82abb7e3..8cbad267 100644 --- a/notebooks/lammps_workflows.ipynb +++ b/notebooks/lammps_workflows.ipynb @@ -1 +1,1227 @@ -{"metadata":{"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":5,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# Workflows\nTo demonstrate the workflows implemented in the `atomistics` package, the [LAMMPS](https://www.lammps.org/) molecular \ndynamics simulation code is used in the following demonstrations. Still the same `workflows` can also be used with other\nsimulation codes:","metadata":{},"id":"29680e01-8658-4085-aada-eaaa9d8705be"},{"cell_type":"code","source":"from atomistics.calculators import evaluate_with_lammps, get_potential_by_name\n\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\nresult_dict = evaluate_with_lammps(\n task_dict={},\n potential_dataframe=potential_dataframe,\n)","metadata":{"trusted":true},"execution_count":1,"outputs":[{"name":"stderr","text":"[jupyter-pyiron-2datomistics-2dloteusr2:00647] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n","output_type":"stream"}],"id":"76ec535d-d9cb-4d68-9208-c9b0c029c402"},{"cell_type":"markdown","source":"The interatomic potential for Aluminium from Mishin named `1999--Mishin-Y--Al--LAMMPS--ipr1` is used in the evaluation\nwith [LAMMPS](https://www.lammps.org/) `evaluate_with_lammps()`. ","metadata":{},"id":"d813a092-a7d8-49e6-8914-02c1b9e105f6"},{"cell_type":"markdown","source":"## Elastic Matrix \nThe elastic constants and elastic moduli can be calculated using the `ElasticMatrixWorkflow`: ","metadata":{},"id":"70bac169-3b94-486f-afa9-efe5005f1cf0"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import evaluate_with_lammps, get_potential_by_name\nfrom atomistics.workflows import ElasticMatrixWorkflow\n\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\nworkflow = ElasticMatrixWorkflow(\n structure=bulk(\"Al\", cubic=True), \n num_of_point=5, \n eps_range=0.005, \n sqrt_eta=True, \n fit_order=2,\n)\ntask_dict = workflow.generate_structures()\nresult_dict = evaluate_with_lammps(\n task_dict=task_dict,\n potential_dataframe=potential_dataframe,\n)\nfit_dict = workflow.analyse_structures(output_dict=result_dict)\nprint(fit_dict)","metadata":{"trusted":true},"execution_count":2,"outputs":[{"name":"stdout","text":"{'elastic_matrix': array([[114.10393023, 60.51098897, 60.51098897, 0. ,\n 0. , 0. ],\n [ 60.51098897, 114.10393023, 60.51098897, 0. ,\n 0. , 0. ],\n [ 60.51098897, 60.51098897, 114.10393023, 0. ,\n 0. , 0. ],\n [ 0. , 0. , 0. , 51.23931149,\n 0. , 0. ],\n [ 0. , 0. , 0. , 0. ,\n 51.23931149, 0. ],\n [ 0. , 0. , 0. , 0. ,\n 0. , 51.23931149]]), 'elastic_matrix_inverse': array([[ 0.01385713, -0.00480204, -0.00480204, 0. , 0. ,\n 0. ],\n [-0.00480204, 0.01385713, -0.00480204, 0. , 0. ,\n 0. ],\n [-0.00480204, -0.00480204, 0.01385713, 0. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0.01951627, 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0.01951627,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0. ,\n 0.01951627]]), 'bulkmodul_voigt': 78.37530272473929, 'bulkmodul_reuss': 78.37530272473931, 'bulkmodul_hill': 78.3753027247393, 'shearmodul_voigt': 41.462175146677424, 'shearmodul_reuss': 37.54162684596518, 'shearmodul_hill': 39.501900996321304, 'youngsmodul_voigt': 105.74025607889799, 'youngsmodul_reuss': 97.1183728107761, 'youngsmodul_hill': 101.46008564559224, 'poissonsratio_voigt': 0.2751412064710683, 'poissonsratio_reuss': 0.29347581564934205, 'poissonsratio_hill': 0.2842430754793411, 'AVR': 4.962480541224269, 'elastic_matrix_eigval': EigResult(eigenvalues=array([ 53.59294126, 235.12590817, 53.59294126, 51.23931149,\n 51.23931149, 51.23931149]), eigenvectors=array([[-0.81649658, 0.57735027, 0.11541902, 0. , 0. ,\n 0. ],\n [ 0.40824829, 0.57735027, -0.75771582, 0. , 0. ,\n 0. ],\n [ 0.40824829, 0.57735027, 0.6422968 , 0. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 1. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 1. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0. ,\n 1. ]]))}\n","output_type":"stream"}],"id":"f26f2645-e1c7-4b7e-8414-e4632b1439f9"},{"cell_type":"markdown","source":"The `ElasticMatrixWorkflow` takes an `ase.atoms.Atoms` object as `structure` input as well as the number of points \n`num_of_point` for each compression direction. Depending on the symmetry of the input `structure` the number of \ncalculations required to calculate the elastic matrix changes. The compression and elongation range is defined by the\n`eps_range` parameter. Furthermore, `sqrt_eta` and `fit_order` describe how the change in energy over compression and\nelongation is fitted to calculate the resulting pressure. ","metadata":{},"id":"262aefd1-9cf9-4b35-8d94-03996b21166b"},{"cell_type":"markdown","source":"## Energy Volume Curve\nThe `EnergyVolumeCurveWorkflow` can be used to calculate the equilibrium properties: equilibrium volume, equilibrium \nenergy, equilibrium bulk modulus and the pressure derivative of the equilibrium bulk modulus. ","metadata":{},"id":"dc5356a8-0b07-4a0a-a549-9a20cf3c64cc"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import evaluate_with_lammps, get_potential_by_name\nfrom atomistics.workflows import EnergyVolumeCurveWorkflow\n\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\nworkflow = EnergyVolumeCurveWorkflow(\n structure=bulk(\"Al\", cubic=True), \n num_points=11,\n fit_type=\"polynomial\",\n fit_order=3,\n vol_range=0.05,\n axes=(\"x\", \"y\", \"z\"),\n strains=None,\n)\ntask_dict = workflow.generate_structures()\nresult_dict = evaluate_with_lammps(\n task_dict=task_dict,\n potential_dataframe=potential_dataframe,\n)\nfit_dict = workflow.analyse_structures(output_dict=result_dict)\nprint(fit_dict)","metadata":{"trusted":true},"execution_count":3,"outputs":[{"name":"stdout","text":"{'b_prime_eq': 1.279502459079921, 'bulkmodul_eq': 77.7250135953191, 'volume_eq': 66.43019853103964, 'energy_eq': -13.43996804374383, 'fit_dict': {'fit_type': 'polynomial', 'least_square_error': 3.225313797039607e-10, 'poly_fit': array([-4.17645808e-05, 1.19746500e-02, -1.03803906e+00, 1.49168639e+01]), 'fit_order': 3}, 'energy': [-13.398169481534445, -13.413389552957456, -13.425112589013958, -13.433411420804067, -13.438357630783006, -13.439999952539933, -13.438383476946305, -13.433607982916406, -13.425774537190858, -13.414961805921427, -13.401233093668836], 'volume': [63.10861874999998, 63.77291999999998, 64.43722124999998, 65.1015225, 65.76582375000004, 66.43012500000002, 67.09442624999994, 67.75872750000002, 68.42302874999999, 69.08732999999997, 69.75163125000002]}\n","output_type":"stream"}],"id":"720a7662-fdee-496d-b355-ff4881f5c633"},{"cell_type":"markdown","source":"The input parameters for the `EnergyVolumeCurveWorkflow` in addition to the `ase.atoms.Atoms` object defined \nas `structure` are: \n\n* `num_points` the number of strains to calculate energies and volumes. \n* `fit_type` the type of the fit which should be used to calculate the equilibrium properties. This can either be a \n `polynomial` fit or a specific equation of state like the Birch equation (`birch`), the Birch-Murnaghan equation \n (`birchmurnaghan`) the Murnaghan equation (`murnaghan`), the Pourier Tarnatola eqaution (`pouriertarantola`) or the\n Vinet equation (`vinet`). \n* `fit_order` for the `polynomial` fit type the order of the polynomial can be set, for the other fit types this \n parameter is ignored. \n* `vol_range` specifies the amount of compression and elongation to be applied relative to the absolute volume. \n* `axes` specifies the axes which are compressed, typically a uniform compression is applied. \n* `strains` specifies the strains directly rather than deriving them from the range of volume compression `vol_range`. \n\nBeyond calculating the equilibrium properties the `EnergyVolumeCurveWorkflow` can also be used to calculate the thermal\nproperties using the [Moruzzi, V. L. et al.](https://link.aps.org/doi/10.1103/PhysRevB.37.790) model: ","metadata":{},"id":"13c95c80-137d-49bf-8016-b3c15279fbcf"},{"cell_type":"code","source":"tp_dict = workflow.get_thermal_properties(\n t_min=1,\n t_max=1500,\n t_step=50,\n temperatures=None,\n constant_volume=False,\n)\nprint(tp_dict)","metadata":{"trusted":true},"execution_count":4,"outputs":[{"name":"stdout","text":"{'temperatures': array([ 1, 51, 101, 151, 201, 251, 301, 351, 401, 451, 501,\n 551, 601, 651, 701, 751, 801, 851, 901, 951, 1001, 1051,\n 1101, 1151, 1201, 1251, 1301, 1351, 1401, 1451, 1501]), 'volumes': array([66.48459155, 66.48492729, 66.48841343, 66.49613572, 66.50654263,\n 66.51846055, 66.53126421, 66.5446199 , 66.55833931, 66.57230985,\n 66.58646057, 66.6007448 , 66.61513063, 66.6295956 , 66.64412341,\n 66.65870199, 66.6733222 , 66.68797701, 66.70266093, 66.71736958,\n 66.73209946, 66.74684773, 66.76161205, 66.77639048, 66.79118142,\n 66.8059835 , 66.82079558, 66.83561668, 66.85044595, 66.86528267,\n 66.88012622]), 'free_energy': array([ 0.18879418, 0.18840183, 0.18352524, 0.16909367, 0.1440755 ,\n 0.10931095, 0.06593656, 0.01498215, -0.04269081, -0.1063728 ,\n -0.1754776 , -0.24951635, -0.328077 , -0.41080851, -0.49740877,\n -0.58761537, -0.68119851, -0.77795536, -0.87770572, -0.98028844,\n -1.08555864, -1.19338539, -1.3036498 , -1.41624343, -1.53106703,\n -1.6480294 , -1.76704645, -1.88804043, -2.01093923, -2.13567578,\n -2.26218757]), 'entropy': array([ 0.75685476, 5.08219062, 18.62461552, 38.05446426,\n 57.6693229 , 75.37710506, 90.99476554, 104.78762778,\n 117.06473011, 128.09164494, 138.08127289, 147.20167195,\n 155.58579193, 163.33970927, 170.54896552, 177.28330938,\n 183.60022562, 189.54757244, 195.16556897, 200.48830826,\n 205.54492122, 210.36048158, 214.95671661, 219.35257076,\n 223.56465688, 227.60762034, 231.49443548, 235.23664867,\n 238.84457908, 242.32748555, 244.0403182 ]), 'heat_capacity': array([8.65067172e-02, 9.11255799e+00, 3.33019964e+01, 5.89575081e+01,\n 7.50185080e+01, 8.36468610e+01, 8.85256734e+01, 9.15055757e+01,\n 9.34491088e+01, 9.47846079e+01, 9.57412353e+01, 9.64498999e+01,\n 9.69896043e+01, 9.74102601e+01, 9.77446368e+01, 9.80149634e+01,\n 9.82367471e+01, 9.84210719e+01, 9.85760297e+01, 9.87076399e+01,\n 9.88204550e+01, 9.89179695e+01, 9.90029019e+01, 9.90773926e+01,\n 9.91431454e+01, 9.92015302e+01, 9.92536586e+01, 9.93004401e+01,\n 9.93426247e+01, nan, nan])}\n","output_type":"stream"}],"id":"8a9a8e77-a6f0-4466-8c3d-fc1ca6ebbaf0"},{"cell_type":"markdown","source":"Or alternatively directly calculate the thermal expansion:","metadata":{},"id":"ebebb63f-3897-4028-ad23-708aaaf9cc26"},{"cell_type":"code","source":"thermal_properties_dict = workflow.get_thermal_properties( \n t_min=1, \n t_max=1500, \n t_step=50, \n constant_volume=False,\n output_keys=[\"temperatures\", \"volumes\"],\n)\ntemperatures, volumes = thermal_properties_dict[\"temperatures\"], thermal_properties_dict[\"volumes\"]","metadata":{"trusted":true},"execution_count":5,"outputs":[],"id":"6e963779-cd59-4985-9a72-9652dd1f1408"},{"cell_type":"markdown","source":"The [Moruzzi, V. L. et al.](https://link.aps.org/doi/10.1103/PhysRevB.37.790) model is a quantum mechanical approximation, so the equilibrium volume at 0K is not\nthe same as the equilibrium volume calculated by fitting the equation of state. ","metadata":{},"id":"e3f4357d-8b81-41bd-a90b-556f231b9766"},{"cell_type":"markdown","source":"## Molecular Dynamics \nJust like the structure optimization also the molecular dynamics calculation can either be implemented inside the\nsimulation code or in the `atomistics` package. The latter has the advantage that it is the same implementation for all\ndifferent simulation codes, while the prior has the advantage that it is usually faster and computationally more efficient.","metadata":{},"id":"ac4095fb-0e11-46bc-8c8d-54bc97ddfe18"},{"cell_type":"markdown","source":"### Implemented in Simulation Code \nThe [LAMMPS](https://lammps.org/) simulation code implements a wide range of different simulation workflows, this \nincludes molecular dynamics. In the `atomistics` package these can be directly accessed via the python interface. ","metadata":{},"id":"1cfe604e-1e02-4a64-a49b-eccd1b32c9fc"},{"cell_type":"markdown","source":"#### Langevin Thermostat\nThe Langevin thermostat is currently the only thermostat which is available as both a stand-alone python interface and\nan integrated interface inside the [LAMMPS](https://lammps.org/) simulation code. The latter is introduced here:","metadata":{},"id":"0e52ed95-1510-4944-a5a6-8ea9d49c906f"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import (\n calc_molecular_dynamics_langevin_with_lammps, \n get_potential_by_name,\n)\n\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\nresult_dict = calc_molecular_dynamics_langevin_with_lammps(\n structure=bulk(\"Al\", cubic=True).repeat([10, 10, 10]),\n potential_dataframe=potential_dataframe,\n Tstart=100,\n Tstop=100,\n Tdamp=0.1,\n run=100,\n thermo=10,\n timestep=0.001,\n seed=4928459,\n dist=\"gaussian\",\n output_keys=(\"positions\", \"cell\", \"forces\", \"temperature\", \"energy_pot\", \"energy_tot\", \"pressure\", \"velocities\"),\n)","metadata":{"trusted":true},"execution_count":6,"outputs":[],"id":"2e0c22ea-562b-4669-a34b-1d60a8bd1e2c"},{"cell_type":"markdown","source":"In addition to the typical LAMMPS input parameters like the atomistic structure `structure` as `ase.atoms.Atoms` object\nand the `pandas.DataFrame` for the interatomic potential `potential_dataframe` are: \n\n* `Tstart` start temperature \n* `Tstop` end temperature\n* `Tdamp` temperature damping parameter \n* `run` number of molecular dynamics steps to be executed during one temperature step\n* `thermo` refresh rate for the thermo dynamic properties, this should typically be the same as the number of molecular\n dynamics steps. \n* `timestep` time step - typically 1fs defined as `0.001`.\n* `seed` random seed for the molecular dynamics \n* `dist` initial velocity distribution \n* `lmp` Lammps library instance as `pylammpsmpi.LammpsASELibrary` object \n* `output` the output quantities which are extracted from the molecular dynamics simulation","metadata":{},"id":"e21267cb-9fb6-4c1f-8912-c281dc899323"},{"cell_type":"markdown","source":"#### Nose Hoover Thermostat\nCanonical ensemble (nvt) - volume and temperature constraints molecular dynamics:","metadata":{},"id":"be5d582d-9952-4a5b-b704-1a9acdb8b306"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import (\n calc_molecular_dynamics_nvt_with_lammps, \n get_potential_by_name,\n)\n\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\nresult_dict = calc_molecular_dynamics_nvt_with_lammps(\n structure=bulk(\"Al\", cubic=True).repeat([10, 10, 10]),\n potential_dataframe=potential_dataframe,\n Tstart=100,\n Tstop=100,\n Tdamp=0.1,\n run=100,\n thermo=10,\n timestep=0.001,\n seed=4928459,\n dist=\"gaussian\",\n output_keys=(\"positions\", \"cell\", \"forces\", \"temperature\", \"energy_pot\", \"energy_tot\", \"pressure\"),\n)","metadata":{"trusted":true},"execution_count":7,"outputs":[],"id":"9717893e-4dea-46f7-9317-bb314bc5bbdd"},{"cell_type":"markdown","source":"In addition to the typical LAMMPS input parameters like the atomistic structure `structure` as `ase.atoms.Atoms` object\nand the `pandas.DataFrame` for the interatomic potential `potential_dataframe` are: \n\n* `Tstart` start temperature \n* `Tstop` end temperature\n* `Tdamp` temperature damping parameter \n* `run` number of molecular dynamics steps to be executed during one temperature step\n* `thermo` refresh rate for the thermo dynamic properties, this should typically be the same as the number of molecular\n dynamics steps. \n* `timestep` time step - typically 1fs defined as `0.001`.\n* `seed` random seed for the molecular dynamics \n* `dist` initial velocity distribution \n* `lmp` Lammps library instance as `pylammpsmpi.LammpsASELibrary` object \n* `output` the output quantities which are extracted from the molecular dynamics simulation","metadata":{},"id":"72797e59-72f5-4d32-b7cf-5ad806b91909"},{"cell_type":"markdown","source":"Isothermal-isobaric ensemble (npt) - pressure and temperature constraints molecular dynamics:","metadata":{},"id":"8356bf7f-bf7d-40e0-8f3c-02309cd74d92"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import (\n calc_molecular_dynamics_npt_with_lammps, \n get_potential_by_name,\n)\n\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\nresult_dict = calc_molecular_dynamics_npt_with_lammps(\n structure=bulk(\"Al\", cubic=True).repeat([10, 10, 10]),\n potential_dataframe=potential_dataframe,\n Tstart=100,\n Tstop=100,\n Tdamp=0.1,\n run=100,\n thermo=100,\n timestep=0.001,\n Pstart=0.0,\n Pstop=0.0,\n Pdamp=1.0,\n seed=4928459,\n dist=\"gaussian\",\n output_keys=(\"positions\", \"cell\", \"forces\", \"temperature\", \"energy_pot\", \"energy_tot\", \"pressure\"),\n)","metadata":{"trusted":true},"execution_count":8,"outputs":[],"id":"1327d554-0df1-45fa-b35c-ec4955ce756f"},{"cell_type":"markdown","source":"The input parameters for the isothermal-isobaric ensemble (npt) are the same as for the canonical ensemble (nvt) plus:\n\n* `Pstart` start pressure \n* `Pstop` end pressure \n* `Pdamp` pressure damping parameter ","metadata":{},"id":"e6aeb0fe-ace6-4e55-a3c2-06be85aaf05e"},{"cell_type":"markdown","source":"Isenthalpic ensemble (nph) - pressure and helmholtz-energy constraints molecular dynamics:","metadata":{},"id":"04f5854b-d803-4023-af04-55efc22ee1e3"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import (\n calc_molecular_dynamics_nph_with_lammps, \n get_potential_by_name,\n)\n\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\nresult_dict = calc_molecular_dynamics_nph_with_lammps(\n structure=bulk(\"Al\", cubic=True).repeat([10, 10, 10]),\n potential_dataframe=potential_dataframe,\n run=100,\n thermo=100,\n timestep=0.001,\n Tstart=100,\n Pstart=0.0,\n Pstop=0.0,\n Pdamp=1.0,\n seed=4928459,\n dist=\"gaussian\",\n output_keys=(\"positions\", \"cell\", \"forces\", \"temperature\", \"energy_pot\", \"energy_tot\", \"pressure\"),\n)","metadata":{"trusted":true},"execution_count":9,"outputs":[],"id":"5f64f60c-89ce-423b-a487-ea96780b1c20"},{"cell_type":"markdown","source":"#### Thermal Expansion\nOne example of a molecular dynamics calculation with the LAMMPS simulation code is the calculation of the thermal \nexpansion: ","metadata":{},"id":"3b4c6022-e1d5-467b-ac1b-d3617670fe67"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import (\n calc_molecular_dynamics_thermal_expansion_with_lammps, \n evaluate_with_lammps, \n get_potential_by_name,\n)\n\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\ntemperatures_md, volumes_md = calc_molecular_dynamics_thermal_expansion_with_lammps(\n structure=bulk(\"Al\", cubic=True).repeat([10, 10, 10]),\n potential_dataframe=potential_dataframe,\n Tstart=100,\n Tstop=1000,\n Tstep=100,\n Tdamp=0.1,\n run=100,\n thermo=100,\n timestep=0.001,\n Pstart=0.0,\n Pstop=0.0,\n Pdamp=1.0,\n seed=4928459,\n dist=\"gaussian\",\n lmp=None,\n)","metadata":{"trusted":true},"execution_count":10,"outputs":[{"name":"stderr","text":"100%|██████████| 10/10 [00:05<00:00, 1.69it/s]\n","output_type":"stream"}],"id":"d3e4bda7-9aa4-4a82-8c51-9606b0e77f75"},{"cell_type":"markdown","source":"In addition to the typical LAMMPS input parameters like the atomistic structure `structure` as `ase.atoms.Atoms` object\nand the `pandas.DataFrame` for the interatomic potential `potential_dataframe` are: \n\n* `Tstart` start temperature \n* `Tstop` end temperature \n* `Tstep` temperature step \n* `Tdamp` temperature damping parameter \n* `run` number of molecular dynamics steps to be executed during one temperature step\n* `thermo` refresh rate for the thermo dynamic properties, this should typically be the same as the number of molecular\n dynamics steps. \n* `timestep` time step - typically 1fs defined as `0.001`.\n* `Pstart` start pressure \n* `Pstop` end pressure \n* `Pdamp` pressure damping parameter \n* `seed` random seed for the molecular dynamics \n* `dist` initial velocity distribution \n* `lmp` Lammps library instance as `pylammpsmpi.LammpsASELibrary` object \n\nThese input parameters are based on the LAMMPS fix `nvt/npt`, you can read more about the specific implementation on the\n[LAMMPS website](https://docs.lammps.org/fix_nh.html). \n","metadata":{},"id":"08c20c91-9e7c-4770-b01f-1765064797dd"},{"cell_type":"markdown","source":"#### Phonons from Molecular Dynamics\nThe softening of the phonon modes is calculated for Silicon using the [Tersoff interatomic potential](https://journals.aps.org/prb/abstract/10.1103/PhysRevB.38.9902) \nwhich is available via the [NIST potentials repository](https://www.ctcms.nist.gov/potentials/entry/1988--Tersoff-J--Si-c/). \nSilicon is chosen based on its diamond crystal lattice which requires less calculation than the face centered cubic (fcc)\ncrystal of Aluminium. The simulation workflow consists of three distinct steps:\n\n* Starting with the optimization of the equilibrium structure. \n* Followed by the calculation of the 0K phonon spectrum. \n* Finally, the finite temperature phonon spectrum is calculated using molecular dynamics. \n\nThe finite temperature phonon spectrum is calculated using the [DynaPhoPy](https://abelcarreras.github.io/DynaPhoPy/)\npackage, which is integrated inside the `atomistics` package. As a prerequisite the dependencies, imported and the bulk \nsilicon diamond structure is created and the Tersoff interatomic potential is loaded: ","metadata":{},"id":"e57a6740-8546-4763-a9b3-140f0cae1543"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import (\n calc_molecular_dynamics_phonons_with_lammps,\n evaluate_with_lammps, \n)\nfrom atomistics.workflows import optimize_positions_and_volume, PhonopyWorkflow\nfrom dynaphopy import Quasiparticle\nimport pandas\nfrom phonopy.units import VaspToTHz\nimport spglib\n\nstructure_bulk = bulk(\"Si\", cubic=True)\npotential_dataframe = get_potential_by_name(\n potential_name='1988--Tersoff-J--Si-c--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)","metadata":{"trusted":true},"execution_count":11,"outputs":[],"id":"793b72ff-6b0b-46d8-a121-2c93ea6e7a32"},{"cell_type":"markdown","source":"The first step is optimizing the Silicon diamond structure to match the lattice specifications implemented in the Tersoff \ninteratomic potential:","metadata":{},"id":"743dce70-a4f0-4063-b353-51d26def4005"},{"cell_type":"code","source":"task_dict = optimize_positions_and_volume(structure=structure_bulk)\nresult_dict = evaluate_with_lammps(\n task_dict=task_dict,\n potential_dataframe=potential_dataframe,\n)\nstructure_ase = result_dict[\"structure_with_optimized_positions_and_volume\"]","metadata":{"trusted":true},"execution_count":12,"outputs":[],"id":"e96fb9d9-da43-49cb-8383-5eb93eea9dc1"},{"cell_type":"markdown","source":"As a second step the 0K phonons are calculated using the `PhonopyWorkflow` which is explained in more detail below in \nthe section on [Phonons](https://atomistics.readthedocs.io/en/latest/workflows.html#phonons). ","metadata":{},"id":"c54c83b5-e710-405f-846b-e270267f8646"},{"cell_type":"code","source":"cell = (structure_ase.cell.array, structure_ase.get_scaled_positions(), structure_ase.numbers)\nprimitive_matrix = spglib.standardize_cell(cell=cell, to_primitive=True)[0] / structure_ase.get_volume() ** (1/3)\nworkflow = PhonopyWorkflow(\n structure=structure_ase,\n interaction_range=10,\n factor=VaspToTHz,\n displacement=0.01,\n dos_mesh=20,\n primitive_matrix=primitive_matrix,\n number_of_snapshots=None,\n)\ntask_dict = workflow.generate_structures()\nresult_dict = evaluate_with_lammps(\n task_dict=task_dict,\n potential_dataframe=potential_dataframe,\n)\nworkflow.analyse_structures(output_dict=result_dict)","metadata":{"trusted":true},"execution_count":13,"outputs":[{"execution_count":13,"output_type":"execute_result","data":{"text/plain":"{'mesh_dict': {'qpoints': array([[0.025, 0.025, 0.025],\n [0.075, 0.025, 0.025],\n [0.125, 0.025, 0.025],\n ...,\n [0.525, 0.525, 0.425],\n [0.475, 0.475, 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0.56818182],\n [0.5 , 0.4280303 , 0.5719697 ],\n [0.5 , 0.42424242, 0.57575758],\n [0.5 , 0.42045455, 0.57954545],\n [0.5 , 0.41666667, 0.58333333],\n [0.5 , 0.41287879, 0.58712121],\n [0.5 , 0.40909091, 0.59090909],\n [0.5 , 0.40530303, 0.59469697],\n [0.5 , 0.40151515, 0.59848485],\n [0.5 , 0.39772727, 0.60227273],\n [0.5 , 0.39393939, 0.60606061],\n [0.5 , 0.39015152, 0.60984848],\n [0.5 , 0.38636364, 0.61363636],\n [0.5 , 0.38257576, 0.61742424],\n [0.5 , 0.37878788, 0.62121212],\n [0.5 , 0.375 , 0.625 ],\n [0.5 , 0.37121212, 0.62878788],\n [0.5 , 0.36742424, 0.63257576],\n [0.5 , 0.36363636, 0.63636364],\n [0.5 , 0.35984848, 0.64015152],\n [0.5 , 0.35606061, 0.64393939],\n [0.5 , 0.35227273, 0.64772727],\n [0.5 , 0.34848485, 0.65151515],\n [0.5 , 0.34469697, 0.65530303],\n [0.5 , 0.34090909, 0.65909091],\n [0.5 , 0.33712121, 0.66287879],\n [0.5 , 0.33333333, 0.66666667],\n [0.5 , 0.32954545, 0.67045455],\n [0.5 , 0.32575758, 0.67424242],\n [0.5 , 0.3219697 , 0.6780303 ],\n [0.5 , 0.31818182, 0.68181818],\n [0.5 , 0.31439394, 0.68560606],\n [0.5 , 0.31060606, 0.68939394],\n [0.5 , 0.30681818, 0.69318182],\n [0.5 , 0.3030303 , 0.6969697 ],\n [0.5 , 0.29924242, 0.70075758],\n [0.5 , 0.29545455, 0.70454545],\n [0.5 , 0.29166667, 0.70833333],\n [0.5 , 0.28787879, 0.71212121],\n [0.5 , 0.28409091, 0.71590909],\n [0.5 , 0.28030303, 0.71969697],\n [0.5 , 0.27651515, 0.72348485],\n [0.5 , 0.27272727, 0.72727273],\n [0.5 , 0.26893939, 0.73106061],\n [0.5 , 0.26515152, 0.73484848],\n [0.5 , 0.26136364, 0.73863636],\n [0.5 , 0.25757576, 0.74242424],\n [0.5 , 0.25378788, 0.74621212],\n [0.5 , 0.25 , 0.75 ]]),\n array([[0.5 , 0.25 , 0.75 ],\n [0.5 , 0.24468085, 0.74468085],\n [0.5 , 0.2393617 , 0.7393617 ],\n [0.5 , 0.23404255, 0.73404255],\n [0.5 , 0.2287234 , 0.7287234 ],\n [0.5 , 0.22340426, 0.72340426],\n [0.5 , 0.21808511, 0.71808511],\n [0.5 , 0.21276596, 0.71276596],\n [0.5 , 0.20744681, 0.70744681],\n [0.5 , 0.20212766, 0.70212766],\n [0.5 , 0.19680851, 0.69680851],\n [0.5 , 0.19148936, 0.69148936],\n [0.5 , 0.18617021, 0.68617021],\n [0.5 , 0.18085106, 0.68085106],\n [0.5 , 0.17553191, 0.67553191],\n [0.5 , 0.17021277, 0.67021277],\n [0.5 , 0.16489362, 0.66489362],\n [0.5 , 0.15957447, 0.65957447],\n [0.5 , 0.15425532, 0.65425532],\n [0.5 , 0.14893617, 0.64893617],\n [0.5 , 0.14361702, 0.64361702],\n [0.5 , 0.13829787, 0.63829787],\n [0.5 , 0.13297872, 0.63297872],\n [0.5 , 0.12765957, 0.62765957],\n [0.5 , 0.12234043, 0.62234043],\n [0.5 , 0.11702128, 0.61702128],\n [0.5 , 0.11170213, 0.61170213],\n [0.5 , 0.10638298, 0.60638298],\n [0.5 , 0.10106383, 0.60106383],\n [0.5 , 0.09574468, 0.59574468],\n [0.5 , 0.09042553, 0.59042553],\n [0.5 , 0.08510638, 0.58510638],\n [0.5 , 0.07978723, 0.57978723],\n [0.5 , 0.07446809, 0.57446809],\n [0.5 , 0.06914894, 0.56914894],\n [0.5 , 0.06382979, 0.56382979],\n [0.5 , 0.05851064, 0.55851064],\n [0.5 , 0.05319149, 0.55319149],\n [0.5 , 0.04787234, 0.54787234],\n [0.5 , 0.04255319, 0.54255319],\n [0.5 , 0.03723404, 0.53723404],\n [0.5 , 0.03191489, 0.53191489],\n [0.5 , 0.02659574, 0.52659574],\n [0.5 , 0.0212766 , 0.5212766 ],\n [0.5 , 0.01595745, 0.51595745],\n [0.5 , 0.0106383 , 0.5106383 ],\n [0.5 , 0.00531915, 0.50531915],\n [0.5 , 0. , 0.5 ]])],\n 'distances': [array([0. , 0.00195846, 0.00391691, 0.00587537, 0.00783383,\n 0.00979229, 0.01175074, 0.0137092 , 0.01566766, 0.01762611,\n 0.01958457, 0.02154303, 0.02350149, 0.02545994, 0.0274184 ,\n 0.02937686, 0.03133531, 0.03329377, 0.03525223, 0.03721068,\n 0.03916914, 0.0411276 , 0.04308606, 0.04504451, 0.04700297,\n 0.04896143, 0.05091988, 0.05287834, 0.0548368 , 0.05679526,\n 0.05875371, 0.06071217, 0.06267063, 0.06462908, 0.06658754,\n 0.068546 , 0.07050446, 0.07246291, 0.07442137, 0.07637983,\n 0.07833828, 0.08029674, 0.0822552 , 0.08421366, 0.08617211,\n 0.08813057, 0.09008903, 0.09204748, 0.09400594, 0.0959644 ,\n 0.09792285, 0.09988131, 0.10183977, 0.10379823, 0.10575668,\n 0.10771514, 0.1096736 , 0.11163205, 0.11359051, 0.11554897,\n 0.11750743, 0.11946588, 0.12142434, 0.1233828 , 0.12534125,\n 0.12729971, 0.12925817, 0.13121663, 0.13317508, 0.13513354,\n 0.137092 , 0.13905045, 0.14100891, 0.14296737, 0.14492583,\n 0.14688428, 0.14884274, 0.1508012 , 0.15275965, 0.15471811,\n 0.15667657, 0.15863503, 0.16059348, 0.16255194, 0.1645104 ,\n 0.16646885, 0.16842731, 0.17038577, 0.17234422, 0.17430268,\n 0.17626114, 0.1782196 , 0.18017805, 0.18213651, 0.18409497]),\n array([0.18409497, 0.18606731, 0.18803966, 0.190012 , 0.19198435,\n 0.19395669, 0.19592904, 0.19790139, 0.19987373, 0.20184608,\n 0.20381842, 0.20579077, 0.20776311, 0.20973546, 0.2117078 ,\n 0.21368015, 0.21565249, 0.21762484, 0.21959719, 0.22156953,\n 0.22354188, 0.22551422, 0.22748657, 0.22945891, 0.23143126,\n 0.2334036 , 0.23537595, 0.23734829, 0.23932064, 0.24129299,\n 0.24326533, 0.24523768, 0.24721002, 0.24918237]),\n array([0.24918237, 0.25113499, 0.25308761, 0.25504023, 0.25699286,\n 0.25894548, 0.2608981 , 0.26285072, 0.26480334, 0.26675597,\n 0.26870859, 0.27066121, 0.27261383, 0.27456645, 0.27651908,\n 0.2784717 , 0.28042432, 0.28237694, 0.28432956, 0.28628219,\n 0.28823481, 0.29018743, 0.29214005, 0.29409267, 0.2960453 ,\n 0.29799792, 0.29995054, 0.30190316, 0.30385578, 0.30580841,\n 0.30776103, 0.30971365, 0.31166627, 0.31361889, 0.31557152,\n 0.31752414, 0.31947676, 0.32142938, 0.323382 , 0.32533463,\n 0.32728725, 0.32923987, 0.33119249, 0.33314511, 0.33509774,\n 0.33705036, 0.33900298, 0.3409556 , 0.34290822, 0.34486085,\n 0.34681347, 0.34876609, 0.35071871, 0.35267133, 0.35462396,\n 0.35657658, 0.3585292 , 0.36048182, 0.36243444, 0.36438707,\n 0.36633969, 0.36829231, 0.37024493, 0.37219755, 0.37415018,\n 0.3761028 , 0.37805542, 0.38000804, 0.38196066, 0.38391329,\n 0.38586591, 0.38781853, 0.38977115, 0.39172377, 0.3936764 ,\n 0.39562902, 0.39758164, 0.39953426, 0.40148688, 0.40343951,\n 0.40539213, 0.40734475, 0.40929737, 0.41124999, 0.41320262,\n 0.41515524, 0.41710786, 0.41906048, 0.4210131 , 0.42296573,\n 0.42491835, 0.42687097, 0.42882359, 0.43077621, 0.43272884,\n 0.43468146, 0.43663408, 0.4385867 , 0.44053932, 0.44249194,\n 0.44444457]),\n array([0.44444457, 0.44641285, 0.44838113, 0.45034942, 0.4523177 ,\n 0.45428598, 0.45625426, 0.45822255, 0.46019083, 0.46215911,\n 0.4641274 , 0.46609568, 0.46806396, 0.47003225, 0.47200053,\n 0.47396881, 0.47593709, 0.47790538, 0.47987366, 0.48184194,\n 0.48381023, 0.48577851, 0.48774679, 0.48971507, 0.49168336,\n 0.49365164, 0.49561992, 0.49758821, 0.49955649, 0.50152477,\n 0.50349306, 0.50546134, 0.50742962, 0.5093979 , 0.51136619,\n 0.51333447, 0.51530275, 0.51727104, 0.51923932, 0.5212076 ,\n 0.52317588, 0.52514417, 0.52711245, 0.52908073, 0.53104902,\n 0.5330173 , 0.53498558, 0.53695387, 0.53892215, 0.54089043,\n 0.54285871, 0.544827 , 0.54679528, 0.54876356, 0.55073185,\n 0.55270013, 0.55466841, 0.55663669, 0.55860498, 0.56057326,\n 0.56254154, 0.56450983, 0.56647811, 0.56844639, 0.57041468,\n 0.57238296, 0.57435124, 0.57631952, 0.57828781, 0.58025609,\n 0.58222437, 0.58419266, 0.58616094, 0.58812922, 0.5900975 ,\n 0.59206579, 0.59403407, 0.59600235, 0.59797064, 0.59993892,\n 0.6019072 , 0.60387549]),\n array([0.60387549, 0.60584783, 0.60782018, 0.60979252, 0.61176487,\n 0.61373721, 0.61570956, 0.6176819 , 0.61965425, 0.62162659,\n 0.62359894, 0.62557129, 0.62754363, 0.62951598, 0.63148832,\n 0.63346067, 0.63543301, 0.63740536, 0.6393777 , 0.64135005,\n 0.64332239, 0.64529474, 0.64726709, 0.64923943, 0.65121178,\n 0.65318412, 0.65515647, 0.65712881, 0.65910116, 0.6610735 ,\n 0.66304585, 0.66501819, 0.66699054, 0.66896289, 0.67093523,\n 0.67290758, 0.67487992, 0.67685227, 0.67882461, 0.68079696,\n 0.6827693 , 0.68474165, 0.68671399, 0.68868634, 0.69065869,\n 0.69263103, 0.69460338, 0.69657572, 0.69854807, 0.70052041,\n 0.70249276, 0.7044651 , 0.70643745, 0.70840979, 0.71038214,\n 0.71235449, 0.71432683, 0.71629918, 0.71827152, 0.72024387,\n 0.72221621, 0.72418856, 0.7261609 , 0.72813325, 0.73010559,\n 0.73207794, 0.73405029]),\n array([0.73405029, 0.73600874, 0.7379672 , 0.73992566, 0.74188411,\n 0.74384257, 0.74580103, 0.74775948, 0.74971794, 0.7516764 ,\n 0.75363486, 0.75559331, 0.75755177, 0.75951023, 0.76146868,\n 0.76342714, 0.7653856 , 0.76734406, 0.76930251, 0.77126097,\n 0.77321943, 0.77517788, 0.77713634, 0.7790948 , 0.78105326,\n 0.78301171, 0.78497017, 0.78692863, 0.78888708, 0.79084554,\n 0.792804 , 0.79476246, 0.79672091, 0.79867937, 0.80063783,\n 0.80259628, 0.80455474, 0.8065132 , 0.80847166, 0.81043011,\n 0.81238857, 0.81434703, 0.81630548, 0.81826394, 0.8202224 ,\n 0.82218085, 0.82413931, 0.82609777])],\n 'frequencies': [array([[2.18701057e-06, 2.19691522e-06, 2.20369934e-06, 1.60678991e+01,\n 1.60678991e+01, 1.60678991e+01],\n [1.06625590e-01, 1.06625590e-01, 1.53239098e-01, 1.60675081e+01,\n 1.60676418e+01, 1.60676418e+01],\n [2.13231909e-01, 2.13231909e-01, 3.06460038e-01, 1.60663351e+01,\n 1.60668701e+01, 1.60668701e+01],\n [3.19799678e-01, 3.19799678e-01, 4.59644667e-01, 1.60643797e+01,\n 1.60655844e+01, 1.60655844e+01],\n [4.26309607e-01, 4.26309607e-01, 6.12774843e-01, 1.60616416e+01,\n 1.60637853e+01, 1.60637853e+01],\n [5.32742383e-01, 5.32742383e-01, 7.65832440e-01, 1.60581201e+01,\n 1.60614737e+01, 1.60614737e+01],\n [6.39078667e-01, 6.39078667e-01, 9.18799354e-01, 1.60538144e+01,\n 1.60586506e+01, 1.60586506e+01],\n [7.45299086e-01, 7.45299086e-01, 1.07165751e+00, 1.60487235e+01,\n 1.60553175e+01, 1.60553175e+01],\n [8.51384225e-01, 8.51384225e-01, 1.22438885e+00, 1.60428463e+01,\n 1.60514759e+01, 1.60514759e+01],\n [9.57314622e-01, 9.57314622e-01, 1.37697538e+00, 1.60361814e+01,\n 1.60471277e+01, 1.60471277e+01],\n [1.06307076e+00, 1.06307076e+00, 1.52939913e+00, 1.60287272e+01,\n 1.60422751e+01, 1.60422751e+01],\n [1.16863306e+00, 1.16863306e+00, 1.68164218e+00, 1.60204822e+01,\n 1.60369205e+01, 1.60369205e+01],\n [1.27398186e+00, 1.27398186e+00, 1.83368666e+00, 1.60114444e+01,\n 1.60310665e+01, 1.60310665e+01],\n [1.37909745e+00, 1.37909745e+00, 1.98551477e+00, 1.60016119e+01,\n 1.60247161e+01, 1.60247161e+01],\n [1.48396001e+00, 1.48396001e+00, 2.13710877e+00, 1.59909824e+01,\n 1.60178724e+01, 1.60178724e+01],\n [1.58854964e+00, 1.58854964e+00, 2.28845098e+00, 1.59795536e+01,\n 1.60105390e+01, 1.60105390e+01],\n [1.69284632e+00, 1.69284632e+00, 2.43952381e+00, 1.59673229e+01,\n 1.60027197e+01, 1.60027197e+01],\n [1.79682995e+00, 1.79682995e+00, 2.59030972e+00, 1.59542878e+01,\n 1.59944185e+01, 1.59944185e+01],\n [1.90048030e+00, 1.90048030e+00, 2.74079128e+00, 1.59404453e+01,\n 1.59856398e+01, 1.59856398e+01],\n [2.00377700e+00, 2.00377700e+00, 2.89095116e+00, 1.59257926e+01,\n 1.59763882e+01, 1.59763882e+01],\n [2.10669956e+00, 2.10669956e+00, 3.04077208e+00, 1.59103264e+01,\n 1.59666687e+01, 1.59666687e+01],\n [2.20922736e+00, 2.20922736e+00, 3.19023691e+00, 1.58940435e+01,\n 1.59564867e+01, 1.59564867e+01],\n [2.31133960e+00, 2.31133960e+00, 3.33932858e+00, 1.58769405e+01,\n 1.59458477e+01, 1.59458477e+01],\n [2.41301534e+00, 2.41301534e+00, 3.48803016e+00, 1.58590139e+01,\n 1.59347578e+01, 1.59347578e+01],\n [2.51423346e+00, 2.51423346e+00, 3.63632482e+00, 1.58402599e+01,\n 1.59232232e+01, 1.59232232e+01],\n [2.61497266e+00, 2.61497266e+00, 3.78419585e+00, 1.58206748e+01,\n 1.59112506e+01, 1.59112506e+01],\n [2.71521144e+00, 2.71521144e+00, 3.93162667e+00, 1.58002545e+01,\n 1.58988470e+01, 1.58988470e+01],\n [2.81492813e+00, 2.81492813e+00, 4.07860083e+00, 1.57789952e+01,\n 1.58860198e+01, 1.58860198e+01],\n [2.91410081e+00, 2.91410081e+00, 4.22510199e+00, 1.57568925e+01,\n 1.58727768e+01, 1.58727768e+01],\n [3.01270737e+00, 3.01270737e+00, 4.37111398e+00, 1.57339422e+01,\n 1.58591262e+01, 1.58591262e+01],\n [3.11072544e+00, 3.11072544e+00, 4.51662075e+00, 1.57101400e+01,\n 1.58450764e+01, 1.58450764e+01],\n [3.20813243e+00, 3.20813243e+00, 4.66160641e+00, 1.56854812e+01,\n 1.58306367e+01, 1.58306367e+01],\n [3.30490548e+00, 3.30490548e+00, 4.80605520e+00, 1.56599614e+01,\n 1.58158162e+01, 1.58158162e+01],\n [3.40102147e+00, 3.40102147e+00, 4.94995155e+00, 1.56335759e+01,\n 1.58006249e+01, 1.58006249e+01],\n [3.49645700e+00, 3.49645700e+00, 5.09328001e+00, 1.56063199e+01,\n 1.57850732e+01, 1.57850732e+01],\n [3.59118839e+00, 3.59118839e+00, 5.23602533e+00, 1.55781885e+01,\n 1.57691716e+01, 1.57691716e+01],\n [3.68519163e+00, 3.68519163e+00, 5.37817241e+00, 1.55491768e+01,\n 1.57529316e+01, 1.57529316e+01],\n [3.77844244e+00, 3.77844244e+00, 5.51970631e+00, 1.55192800e+01,\n 1.57363649e+01, 1.57363649e+01],\n [3.87091618e+00, 3.87091618e+00, 5.66061230e+00, 1.54884928e+01,\n 1.57194835e+01, 1.57194835e+01],\n [3.96258789e+00, 3.96258789e+00, 5.80087581e+00, 1.54568102e+01,\n 1.57023004e+01, 1.57023004e+01],\n [4.05343226e+00, 4.05343226e+00, 5.94048245e+00, 1.54242271e+01,\n 1.56848288e+01, 1.56848288e+01],\n [4.14342363e+00, 4.14342363e+00, 6.07941802e+00, 1.53907382e+01,\n 1.56670824e+01, 1.56670824e+01],\n [4.23253595e+00, 4.23253595e+00, 6.21766853e+00, 1.53563383e+01,\n 1.56490757e+01, 1.56490757e+01],\n [4.32074280e+00, 4.32074280e+00, 6.35522016e+00, 1.53210221e+01,\n 1.56308235e+01, 1.56308235e+01],\n [4.40801738e+00, 4.40801738e+00, 6.49205931e+00, 1.52847843e+01,\n 1.56123413e+01, 1.56123413e+01],\n [4.49433246e+00, 4.49433246e+00, 6.62817257e+00, 1.52476196e+01,\n 1.55936453e+01, 1.55936453e+01],\n [4.57966044e+00, 4.57966044e+00, 6.76354674e+00, 1.52095227e+01,\n 1.55747520e+01, 1.55747520e+01],\n [4.66397327e+00, 4.66397327e+00, 6.89816884e+00, 1.51704881e+01,\n 1.55556788e+01, 1.55556788e+01],\n [4.74724248e+00, 4.74724248e+00, 7.03202608e+00, 1.51305106e+01,\n 1.55364436e+01, 1.55364436e+01],\n [4.82943918e+00, 4.82943918e+00, 7.16510590e+00, 1.50895847e+01,\n 1.55170649e+01, 1.55170649e+01],\n [4.91053403e+00, 4.91053403e+00, 7.29739597e+00, 1.50477052e+01,\n 1.54975617e+01, 1.54975617e+01],\n [4.99049726e+00, 4.99049726e+00, 7.42888415e+00, 1.50048667e+01,\n 1.54779540e+01, 1.54779540e+01],\n [5.06929865e+00, 5.06929865e+00, 7.55955856e+00, 1.49610639e+01,\n 1.54582620e+01, 1.54582620e+01],\n [5.14690753e+00, 5.14690753e+00, 7.68940753e+00, 1.49162915e+01,\n 1.54385069e+01, 1.54385069e+01],\n [5.22329282e+00, 5.22329282e+00, 7.81841962e+00, 1.48705443e+01,\n 1.54187103e+01, 1.54187103e+01],\n [5.29842297e+00, 5.29842297e+00, 7.94658362e+00, 1.48238171e+01,\n 1.53988946e+01, 1.53988946e+01],\n [5.37226600e+00, 5.37226600e+00, 8.07388856e+00, 1.47761047e+01,\n 1.53790827e+01, 1.53790827e+01],\n [5.44478953e+00, 5.44478953e+00, 8.20032372e+00, 1.47274020e+01,\n 1.53592983e+01, 1.53592983e+01],\n [5.51596076e+00, 5.51596076e+00, 8.32587860e+00, 1.46777039e+01,\n 1.53395654e+01, 1.53395654e+01],\n [5.58574651e+00, 5.58574651e+00, 8.45054294e+00, 1.46270056e+01,\n 1.53199089e+01, 1.53199089e+01],\n [5.65411319e+00, 5.65411319e+00, 8.57430676e+00, 1.45753020e+01,\n 1.53003542e+01, 1.53003542e+01],\n [5.72102691e+00, 5.72102691e+00, 8.69716027e+00, 1.45225884e+01,\n 1.52809272e+01, 1.52809272e+01],\n [5.78645342e+00, 5.78645342e+00, 8.81909398e+00, 1.44688599e+01,\n 1.52616544e+01, 1.52616544e+01],\n [5.85035821e+00, 5.85035821e+00, 8.94009862e+00, 1.44141121e+01,\n 1.52425628e+01, 1.52425628e+01],\n [5.91270648e+00, 5.91270648e+00, 9.06016518e+00, 1.43583401e+01,\n 1.52236797e+01, 1.52236797e+01],\n [5.97346325e+00, 5.97346325e+00, 9.17928491e+00, 1.43015397e+01,\n 1.52050331e+01, 1.52050331e+01],\n [6.03259336e+00, 6.03259336e+00, 9.29744928e+00, 1.42437065e+01,\n 1.51866511e+01, 1.51866511e+01],\n [6.09006155e+00, 6.09006155e+00, 9.41465007e+00, 1.41848361e+01,\n 1.51685625e+01, 1.51685625e+01],\n [6.14583250e+00, 6.14583250e+00, 9.53087927e+00, 1.41249246e+01,\n 1.51507959e+01, 1.51507959e+01],\n [6.19987090e+00, 6.19987090e+00, 9.64612916e+00, 1.40639678e+01,\n 1.51333805e+01, 1.51333805e+01],\n [6.25214152e+00, 6.25214152e+00, 9.76039224e+00, 1.40019619e+01,\n 1.51163455e+01, 1.51163455e+01],\n [6.30260929e+00, 6.30260929e+00, 9.87366131e+00, 1.39389032e+01,\n 1.50997202e+01, 1.50997202e+01],\n [6.35123937e+00, 6.35123937e+00, 9.98592942e+00, 1.38747880e+01,\n 1.50835337e+01, 1.50835337e+01],\n [6.39799726e+00, 6.39799726e+00, 1.00971898e+01, 1.38096130e+01,\n 1.50678154e+01, 1.50678154e+01],\n [6.44284885e+00, 6.44284885e+00, 1.02074362e+01, 1.37433748e+01,\n 1.50525941e+01, 1.50525941e+01],\n [6.48576059e+00, 6.48576059e+00, 1.03166622e+01, 1.36760703e+01,\n 1.50378985e+01, 1.50378985e+01],\n [6.52669951e+00, 6.52669951e+00, 1.04248621e+01, 1.36076964e+01,\n 1.50237569e+01, 1.50237569e+01],\n [6.56563338e+00, 6.56563338e+00, 1.05320301e+01, 1.35382504e+01,\n 1.50101972e+01, 1.50101972e+01],\n [6.60253081e+00, 6.60253081e+00, 1.06381608e+01, 1.34677297e+01,\n 1.49972465e+01, 1.49972465e+01],\n [6.63736135e+00, 6.63736135e+00, 1.07432492e+01, 1.33961316e+01,\n 1.49849313e+01, 1.49849313e+01],\n [6.67009563e+00, 6.67009563e+00, 1.08472903e+01, 1.33234540e+01,\n 1.49732773e+01, 1.49732773e+01],\n [6.70070547e+00, 6.70070547e+00, 1.09502796e+01, 1.32496947e+01,\n 1.49623091e+01, 1.49623091e+01],\n [6.72916397e+00, 6.72916397e+00, 1.10522127e+01, 1.31748518e+01,\n 1.49520504e+01, 1.49520504e+01],\n [6.75544567e+00, 6.75544567e+00, 1.11530855e+01, 1.30989236e+01,\n 1.49425237e+01, 1.49425237e+01],\n [6.77952663e+00, 6.77952663e+00, 1.12528941e+01, 1.30219085e+01,\n 1.49337500e+01, 1.49337500e+01],\n [6.80138457e+00, 6.80138457e+00, 1.13516350e+01, 1.29438053e+01,\n 1.49257493e+01, 1.49257493e+01],\n [6.82099896e+00, 6.82099896e+00, 1.14493049e+01, 1.28646126e+01,\n 1.49185396e+01, 1.49185396e+01],\n [6.83835113e+00, 6.83835113e+00, 1.15459006e+01, 1.27843298e+01,\n 1.49121375e+01, 1.49121375e+01],\n [6.85342435e+00, 6.85342435e+00, 1.16414194e+01, 1.27029559e+01,\n 1.49065581e+01, 1.49065581e+01],\n [6.86620396e+00, 6.86620396e+00, 1.17358587e+01, 1.26204906e+01,\n 1.49018144e+01, 1.49018144e+01],\n [6.87667737e+00, 6.87667737e+00, 1.18292162e+01, 1.25369336e+01,\n 1.48979177e+01, 1.48979177e+01],\n [6.88483424e+00, 6.88483424e+00, 1.19214899e+01, 1.24522848e+01,\n 1.48948771e+01, 1.48948771e+01],\n [6.89066641e+00, 6.89066641e+00, 1.20126778e+01, 1.23665443e+01,\n 1.48927000e+01, 1.48927000e+01],\n [6.89416806e+00, 6.89416806e+00, 1.21027784e+01, 1.22797127e+01,\n 1.48913917e+01, 1.48913917e+01],\n [6.89533567e+00, 6.89533567e+00, 1.21917904e+01, 1.21917904e+01,\n 1.48909552e+01, 1.48909552e+01]]),\n array([[ 6.89533567, 6.89533567, 12.19179039, 12.19179039, 14.89095524,\n 14.89095524],\n [ 6.89476599, 6.89721307, 12.19035931, 12.19131253, 14.89109076,\n 14.89177681],\n [ 6.8930571 , 6.90283616, 12.18607431, 12.18988157, 14.8914973 ,\n 14.89423361],\n [ 6.89020956, 6.91217764, 12.17895978, 12.18750534, 14.89217481,\n 14.89830206],\n [ 6.88622426, 6.92519216, 12.16905574, 12.18419693, 14.89312318,\n 14.90394357],\n [ 6.88110243, 6.9418166 , 12.15641674, 12.17997485, 14.89434227,\n 14.91110552],\n [ 6.8748457 , 6.96197032, 12.1411106 , 12.17486306, 14.89583189,\n 14.9197226 ],\n [ 6.86745601, 6.98555564, 12.1232168 , 12.16889124, 14.89759181,\n 14.92971834],\n [ 6.85893568, 7.0124582 , 12.10282475, 12.16209492, 14.89962177,\n 14.94100685],\n [ 6.84928737, 7.04254753, 12.08003199, 12.15451577, 14.90192145,\n 14.9534946 ],\n [ 6.83851409, 7.07567754, 12.05494232, 12.14620185, 14.90449047,\n 14.96708225],\n [ 6.8266192 , 7.11168706, 12.02766403, 12.13720797, 14.90732842,\n 14.98166641],\n [ 6.81360641, 7.1504004 , 11.99830825, 12.12759601, 14.91043482,\n 14.99714124],\n [ 6.79947975, 7.19162786, 11.96698741, 12.11743535, 14.91380915,\n 15.01339997],\n [ 6.78424361, 7.23516623, 11.93381387, 12.10680327, 14.91745083,\n 15.03033626],\n [ 6.7679027 , 7.28079926, 11.89889873, 12.0957854 , 14.9213592 ,\n 15.04784527],\n [ 6.75046209, 7.32829805, 11.86235086, 12.08447621, 14.92553355,\n 15.06582469],\n [ 6.73192714, 7.3774215 , 11.82427602, 12.07297947, 14.92997311,\n 15.0841755 ],\n [ 6.71230356, 7.42791658, 11.78477623, 12.06140874, 14.93467703,\n 15.1028026 ],\n [ 6.69159738, 7.47951874, 11.74394921, 12.0498878 , 14.93964437,\n 15.12161529],\n [ 6.66981492, 7.53195215, 11.701888 , 12.03855107, 14.94487413,\n 15.14052765],\n [ 6.64696284, 7.58493013, 11.65868065, 12.02754391, 14.95036522,\n 15.15945873],\n [ 6.62304809, 7.6381555 , 11.61441001, 12.01702285, 14.95611647,\n 15.17833279],\n [ 6.59807794, 7.69132112, 11.5691536 , 12.0071556 , 14.96212661,\n 15.19707928],\n [ 6.57205993, 7.74411056, 11.52298356, 11.99812092, 14.96839427,\n 15.21563293],\n [ 6.5450019 , 7.79619897, 11.47596658, 11.99010811, 14.974918 ,\n 15.23393372],\n [ 6.51691198, 7.8472543 , 11.42816396, 11.98331627, 14.98169623,\n 15.25192677],\n [ 6.48779857, 7.89693879, 11.3796316 , 11.9779531 , 14.98872728,\n 15.26956229],\n [ 6.45767036, 7.94491097, 11.33042012, 11.97423316, 14.99600936,\n 15.28679543],\n [ 6.42653627, 7.99082805, 11.28057486, 11.97237575, 15.00354058,\n 15.30358621],\n [ 6.39440553, 8.03434895, 11.23013602, 11.97260212, 15.01131889,\n 15.31989932],\n [ 6.36128757, 8.07513774, 11.17913872, 11.97513212, 15.01934216,\n 15.33570402],\n [ 6.3271921 , 8.11286763, 11.12761311, 11.98018037, 15.02760809,\n 15.35097401],\n [ 6.29212906, 8.1472254 , 11.07558447, 11.98795191, 15.03611427,\n 15.36568722]]),\n array([[6.29212906e+00, 8.14722540e+00, 1.10755845e+01, 1.19879519e+01,\n 1.50361143e+01, 1.53656872e+01],\n [6.25647352e+00, 8.17762824e+00, 1.10236007e+01, 1.19985158e+01,\n 1.50447695e+01, 1.53796873e+01],\n [6.21988972e+00, 8.20417287e+00, 1.09711594e+01, 1.20121030e+01,\n 1.50536551e+01, 1.53931105e+01],\n [6.18238794e+00, 8.22662180e+00, 1.09182714e+01, 1.20288578e+01,\n 1.50627683e+01, 1.54059471e+01],\n [6.14397867e+00, 8.24476801e+00, 1.08649436e+01, 1.20488984e+01,\n 1.50721062e+01, 1.54181907e+01],\n [6.10467261e+00, 8.25843843e+00, 1.08111782e+01, 1.20723127e+01,\n 1.50816657e+01, 1.54298385e+01],\n [6.06448062e+00, 8.26749638e+00, 1.07569737e+01, 1.20991563e+01,\n 1.50914436e+01, 1.54408909e+01],\n [6.02341375e+00, 8.27184310e+00, 1.07023245e+01, 1.21294507e+01,\n 1.51014366e+01, 1.54513515e+01],\n [5.98148322e+00, 8.27141809e+00, 1.06472210e+01, 1.21631830e+01,\n 1.51116412e+01, 1.54612269e+01],\n [5.93870041e+00, 8.26619826e+00, 1.05916501e+01, 1.22003070e+01,\n 1.51220536e+01, 1.54705266e+01],\n [5.89507685e+00, 8.25619607e+00, 1.05355947e+01, 1.22407444e+01,\n 1.51326701e+01, 1.54792629e+01],\n [5.85062423e+00, 8.24145671e+00, 1.04790345e+01, 1.22843880e+01,\n 1.51434866e+01, 1.54874505e+01],\n [5.80535435e+00, 8.22205454e+00, 1.04219458e+01, 1.23311050e+01,\n 1.51544990e+01, 1.54951070e+01],\n [5.75927918e+00, 8.19808909e+00, 1.03643013e+01, 1.23807412e+01,\n 1.51657030e+01, 1.55022519e+01],\n [5.71241078e+00, 8.16968082e+00, 1.03060712e+01, 1.24331247e+01,\n 1.51770940e+01, 1.55089071e+01],\n [5.66476132e+00, 8.13696682e+00, 1.02472222e+01, 1.24880707e+01,\n 1.51886673e+01, 1.55150965e+01],\n [5.61634311e+00, 8.10009673e+00, 1.01877186e+01, 1.25453849e+01,\n 1.52004182e+01, 1.55208458e+01],\n [5.56716850e+00, 8.05922898e+00, 1.01275221e+01, 1.26048678e+01,\n 1.52123416e+01, 1.55261825e+01],\n [5.51724999e+00, 8.01452741e+00, 1.00665919e+01, 1.26663173e+01,\n 1.52244322e+01, 1.55311356e+01],\n [5.46660010e+00, 7.96615838e+00, 1.00048851e+01, 1.27295323e+01,\n 1.52366848e+01, 1.55357354e+01],\n [5.41523147e+00, 7.91428833e+00, 9.94235680e+00, 1.27943144e+01,\n 1.52490938e+01, 1.55400135e+01],\n [5.36315676e+00, 7.85908189e+00, 9.87896026e+00, 1.28604702e+01,\n 1.52616534e+01, 1.55440024e+01],\n [5.31038872e+00, 7.80070024e+00, 9.81464731e+00, 1.29278126e+01,\n 1.52743579e+01, 1.55477354e+01],\n [5.25694012e+00, 7.73930008e+00, 9.74936842e+00, 1.29961616e+01,\n 1.52872010e+01, 1.55512465e+01],\n [5.20282376e+00, 7.67503275e+00, 9.68307301e+00, 1.30653456e+01,\n 1.53001767e+01, 1.55545700e+01],\n [5.14805250e+00, 7.60804370e+00, 9.61570966e+00, 1.31352015e+01,\n 1.53132784e+01, 1.55577406e+01],\n [5.09263918e+00, 7.53847222e+00, 9.54722637e+00, 1.32055749e+01,\n 1.53264997e+01, 1.55607929e+01],\n [5.03659669e+00, 7.46645125e+00, 9.47757079e+00, 1.32763204e+01,\n 1.53398339e+01, 1.55637613e+01],\n [4.97993788e+00, 7.39210746e+00, 9.40669052e+00, 1.33473013e+01,\n 1.53532739e+01, 1.55666801e+01],\n [4.92267563e+00, 7.31556132e+00, 9.33453328e+00, 1.34183894e+01,\n 1.53668129e+01, 1.55695827e+01],\n [4.86482279e+00, 7.23692730e+00, 9.26104725e+00, 1.34894651e+01,\n 1.53804435e+01, 1.55725021e+01],\n [4.80639218e+00, 7.15631413e+00, 9.18618123e+00, 1.35604165e+01,\n 1.53941585e+01, 1.55754701e+01],\n [4.74739660e+00, 7.07382508e+00, 9.10988493e+00, 1.36311397e+01,\n 1.54079504e+01, 1.55785176e+01],\n [4.68784882e+00, 6.98955824e+00, 9.03210916e+00, 1.37015378e+01,\n 1.54218114e+01, 1.55816741e+01],\n [4.62776153e+00, 6.90360685e+00, 8.95280611e+00, 1.37715211e+01,\n 1.54357340e+01, 1.55849678e+01],\n [4.56714742e+00, 6.81605958e+00, 8.87192951e+00, 1.38410062e+01,\n 1.54497101e+01, 1.55884254e+01],\n [4.50601906e+00, 6.72700084e+00, 8.78943483e+00, 1.39099162e+01,\n 1.54637317e+01, 1.55920716e+01],\n [4.44438898e+00, 6.63651108e+00, 8.70527953e+00, 1.39781798e+01,\n 1.54777906e+01, 1.55959297e+01],\n [4.38226965e+00, 6.54466702e+00, 8.61942314e+00, 1.40457313e+01,\n 1.54918787e+01, 1.56000208e+01],\n [4.31967342e+00, 6.45154194e+00, 8.53182751e+00, 1.41125102e+01,\n 1.55059874e+01, 1.56043639e+01],\n [4.25661258e+00, 6.35720591e+00, 8.44245688e+00, 1.41784608e+01,\n 1.55201084e+01, 1.56089764e+01],\n [4.19309930e+00, 6.26172600e+00, 8.35127806e+00, 1.42435321e+01,\n 1.55342331e+01, 1.56138729e+01],\n [4.12914566e+00, 6.16516649e+00, 8.25826052e+00, 1.43076773e+01,\n 1.55483527e+01, 1.56190663e+01],\n [4.06476362e+00, 6.06758902e+00, 8.16337647e+00, 1.43708539e+01,\n 1.55624585e+01, 1.56245671e+01],\n [3.99996504e+00, 5.96905281e+00, 8.06660096e+00, 1.44330230e+01,\n 1.55765418e+01, 1.56303834e+01],\n [3.93476163e+00, 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1.54312262e+01,\n 1.58074231e+01, 1.58395340e+01],\n [2.56244556e+00, 3.76287285e+00, 5.58407662e+00, 1.54681979e+01,\n 1.58182831e+01, 1.58510552e+01],\n [2.49118267e+00, 3.65451734e+00, 5.44517149e+00, 1.55039443e+01,\n 1.58291854e+01, 1.58623571e+01],\n [2.41973308e+00, 3.54608907e+00, 5.30456433e+00, 1.55384733e+01,\n 1.58401057e+01, 1.58734313e+01],\n [2.34810468e+00, 3.43760952e+00, 5.16229042e+00, 1.55717939e+01,\n 1.58510196e+01, 1.58842699e+01],\n [2.27630514e+00, 3.32909882e+00, 5.01838660e+00, 1.56039154e+01,\n 1.58619024e+01, 1.58948649e+01],\n [2.20434195e+00, 3.22057576e+00, 4.87289117e+00, 1.56348481e+01,\n 1.58727296e+01, 1.59052083e+01],\n [2.13222245e+00, 3.11205777e+00, 4.72584387e+00, 1.56646028e+01,\n 1.58834767e+01, 1.59152926e+01],\n [2.05995377e+00, 3.00356093e+00, 4.57728573e+00, 1.56931907e+01,\n 1.58941193e+01, 1.59251103e+01],\n [1.98754288e+00, 2.89509999e+00, 4.42725903e+00, 1.57206235e+01,\n 1.59046335e+01, 1.59346539e+01],\n [1.91499656e+00, 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1.60135473e+01],\n [1.18346297e+00, 1.70729471e+00, 2.69318669e+00, 1.59497156e+01,\n 1.60053528e+01, 1.60196502e+01],\n [1.10982948e+00, 1.59993840e+00, 2.52920191e+00, 1.59642614e+01,\n 1.60126188e+01, 1.60254073e+01],\n [1.03612996e+00, 1.49269275e+00, 2.36438337e+00, 1.59778120e+01,\n 1.60194921e+01, 1.60308142e+01],\n [9.62369353e-01, 1.38555533e+00, 2.19878458e+00, 1.59903781e+01,\n 1.60259578e+01, 1.60358666e+01],\n [8.88552464e-01, 1.27852278e+00, 2.03245949e+00, 1.60019699e+01,\n 1.60320020e+01, 1.60405607e+01],\n [8.14684015e-01, 1.17159077e+00, 1.86546247e+00, 1.60125969e+01,\n 1.60376114e+01, 1.60448929e+01],\n [7.40768631e-01, 1.06475413e+00, 1.69784826e+00, 1.60222682e+01,\n 1.60427741e+01, 1.60488597e+01],\n [6.66810854e-01, 9.58006865e-01, 1.52967192e+00, 1.60309922e+01,\n 1.60474790e+01, 1.60524581e+01],\n [5.92815147e-01, 8.51342252e-01, 1.36098882e+00, 1.60387766e+01,\n 1.60517159e+01, 1.60556853e+01],\n [5.18785904e-01, 7.44752868e-01, 1.19185462e+00, 1.60456283e+01,\n 1.60554758e+01, 1.60585387e+01],\n [4.44727457e-01, 6.38230684e-01, 1.02232518e+00, 1.60515536e+01,\n 1.60587508e+01, 1.60610163e+01],\n [3.70644079e-01, 5.31767125e-01, 8.52456593e-01, 1.60565579e+01,\n 1.60615337e+01, 1.60631159e+01],\n [2.96540000e-01, 4.25353148e-01, 6.82305119e-01, 1.60606459e+01,\n 1.60638187e+01, 1.60648360e+01],\n [2.22419407e-01, 3.18979315e-01, 5.11927163e-01, 1.60638214e+01,\n 1.60656010e+01, 1.60661753e+01],\n [1.48286457e-01, 2.12635869e-01, 3.41379243e-01, 1.60660875e+01,\n 1.60668768e+01, 1.60671327e+01],\n [7.41452829e-02, 1.06312817e-01, 1.70717968e-01, 1.60674463e+01,\n 1.60676434e+01, 1.60677074e+01],\n [2.18701057e-06, 2.19691522e-06, 2.20369934e-06, 1.60678991e+01,\n 1.60678991e+01, 1.60678991e+01]]),\n array([[2.18701057e-06, 2.19691522e-06, 2.20369934e-06, 1.60678991e+01,\n 1.60678991e+01, 1.60678991e+01],\n [8.68987455e-02, 8.68987455e-02, 1.77711678e-01, 1.60674173e+01,\n 1.60676826e+01, 1.60676826e+01],\n [1.73771843e-01, 1.73771843e-01, 3.55392732e-01, 1.60659718e+01,\n 1.60670336e+01, 1.60670336e+01],\n [2.60593637e-01, 2.60593637e-01, 5.33012548e-01, 1.60635622e+01,\n 1.60659527e+01, 1.60659527e+01],\n [3.47338458e-01, 3.47338458e-01, 7.10540526e-01, 1.60601876e+01,\n 1.60644410e+01, 1.60644410e+01],\n [4.33980615e-01, 4.33980615e-01, 8.87946095e-01, 1.60558468e+01,\n 1.60625002e+01, 1.60625002e+01],\n [5.20494388e-01, 5.20494388e-01, 1.06519872e+00, 1.60505385e+01,\n 1.60601324e+01, 1.60601324e+01],\n [6.06854021e-01, 6.06854021e-01, 1.24226790e+00, 1.60442608e+01,\n 1.60573401e+01, 1.60573401e+01],\n [6.93033715e-01, 6.93033715e-01, 1.41912319e+00, 1.60370117e+01,\n 1.60541264e+01, 1.60541264e+01],\n [7.79007624e-01, 7.79007624e-01, 1.59573422e+00, 1.60287888e+01,\n 1.60504947e+01, 1.60504947e+01],\n [8.64749842e-01, 8.64749842e-01, 1.77207066e+00, 1.60195894e+01,\n 1.60464489e+01, 1.60464489e+01],\n [9.50234402e-01, 9.50234402e-01, 1.94810227e+00, 1.60094105e+01,\n 1.60419936e+01, 1.60419936e+01],\n [1.03543527e+00, 1.03543527e+00, 2.12379889e+00, 1.59982489e+01,\n 1.60371336e+01, 1.60371336e+01],\n [1.12032632e+00, 1.12032632e+00, 2.29913045e+00, 1.59861010e+01,\n 1.60318742e+01, 1.60318742e+01],\n [1.20488137e+00, 1.20488137e+00, 2.47406698e+00, 1.59729630e+01,\n 1.60262213e+01, 1.60262213e+01],\n [1.28907413e+00, 1.28907413e+00, 2.64857859e+00, 1.59588309e+01,\n 1.60201811e+01, 1.60201811e+01],\n [1.37287823e+00, 1.37287823e+00, 2.82263554e+00, 1.59437003e+01,\n 1.60137605e+01, 1.60137605e+01],\n [1.45626718e+00, 1.45626718e+00, 2.99620815e+00, 1.59275668e+01,\n 1.60069667e+01, 1.60069667e+01],\n [1.53921441e+00, 1.53921441e+00, 3.16926692e+00, 1.59104255e+01,\n 1.59998074e+01, 1.59998074e+01],\n [1.62169322e+00, 1.62169322e+00, 3.34178242e+00, 1.58922716e+01,\n 1.59922907e+01, 1.59922907e+01],\n [1.70367680e+00, 1.70367680e+00, 3.51372537e+00, 1.58730998e+01,\n 1.59844254e+01, 1.59844254e+01],\n [1.78513824e+00, 1.78513824e+00, 3.68506663e+00, 1.58529049e+01,\n 1.59762205e+01, 1.59762205e+01],\n [1.86605049e+00, 1.86605049e+00, 3.85577716e+00, 1.58316813e+01,\n 1.59676856e+01, 1.59676856e+01],\n [1.94638637e+00, 1.94638637e+00, 4.02582809e+00, 1.58094236e+01,\n 1.59588308e+01, 1.59588308e+01],\n [2.02611858e+00, 2.02611858e+00, 4.19519065e+00, 1.57861259e+01,\n 1.59496667e+01, 1.59496667e+01],\n [2.10521970e+00, 2.10521970e+00, 4.36383622e+00, 1.57617825e+01,\n 1.59402042e+01, 1.59402042e+01],\n [2.18366216e+00, 2.18366216e+00, 4.53173632e+00, 1.57363875e+01,\n 1.59304548e+01, 1.59304548e+01],\n [2.26141827e+00, 2.26141827e+00, 4.69886256e+00, 1.57099349e+01,\n 1.59204304e+01, 1.59204304e+01],\n [2.33846020e+00, 2.33846020e+00, 4.86518671e+00, 1.56824189e+01,\n 1.59101434e+01, 1.59101434e+01],\n [2.41475999e+00, 2.41475999e+00, 5.03068062e+00, 1.56538334e+01,\n 1.58996067e+01, 1.58996067e+01],\n [2.49028953e+00, 2.49028953e+00, 5.19531627e+00, 1.56241727e+01,\n 1.58888336e+01, 1.58888336e+01],\n [2.56502062e+00, 2.56502062e+00, 5.35906572e+00, 1.55934309e+01,\n 1.58778377e+01, 1.58778377e+01],\n [2.63892491e+00, 2.63892491e+00, 5.52190112e+00, 1.55616024e+01,\n 1.58666334e+01, 1.58666334e+01],\n [2.71197391e+00, 2.71197391e+00, 5.68379466e+00, 1.55286816e+01,\n 1.58552351e+01, 1.58552351e+01],\n [2.78413905e+00, 2.78413905e+00, 5.84471859e+00, 1.54946631e+01,\n 1.58436580e+01, 1.58436580e+01],\n [2.85539161e+00, 2.85539161e+00, 6.00464518e+00, 1.54595418e+01,\n 1.58319175e+01, 1.58319175e+01],\n [2.92570282e+00, 2.92570282e+00, 6.16354668e+00, 1.54233130e+01,\n 1.58200294e+01, 1.58200294e+01],\n [2.99504375e+00, 2.99504375e+00, 6.32139531e+00, 1.53859722e+01,\n 1.58080101e+01, 1.58080101e+01],\n [3.06338544e+00, 3.06338544e+00, 6.47816320e+00, 1.53475153e+01,\n 1.57958762e+01, 1.57958762e+01],\n [3.13069883e+00, 3.13069883e+00, 6.63382235e+00, 1.53079386e+01,\n 1.57836448e+01, 1.57836448e+01],\n [3.19695480e+00, 3.19695480e+00, 6.78834460e+00, 1.52672393e+01,\n 1.57713331e+01, 1.57713331e+01],\n [3.26212420e+00, 3.26212420e+00, 6.94170153e+00, 1.52254148e+01,\n 1.57589589e+01, 1.57589589e+01],\n [3.32617785e+00, 3.32617785e+00, 7.09386444e+00, 1.51824635e+01,\n 1.57465403e+01, 1.57465403e+01],\n [3.38908653e+00, 3.38908653e+00, 7.24480421e+00, 1.51383844e+01,\n 1.57340955e+01, 1.57340955e+01],\n [3.45082108e+00, 3.45082108e+00, 7.39449126e+00, 1.50931777e+01,\n 1.57216433e+01, 1.57216433e+01],\n [3.51135231e+00, 3.51135231e+00, 7.54289542e+00, 1.50468445e+01,\n 1.57092025e+01, 1.57092025e+01],\n [3.57065115e+00, 3.57065115e+00, 7.68998576e+00, 1.49993872e+01,\n 1.56967922e+01, 1.56967922e+01],\n [3.62868855e+00, 3.62868855e+00, 7.83573054e+00, 1.49508094e+01,\n 1.56844317e+01, 1.56844317e+01],\n [3.68543561e+00, 3.68543561e+00, 7.98009691e+00, 1.49011166e+01,\n 1.56721405e+01, 1.56721405e+01],\n [3.74086353e+00, 3.74086353e+00, 8.12305082e+00, 1.48503158e+01,\n 1.56599383e+01, 1.56599383e+01],\n [3.79494372e+00, 3.79494372e+00, 8.26455669e+00, 1.47984162e+01,\n 1.56478448e+01, 1.56478448e+01],\n [3.84764774e+00, 3.84764774e+00, 8.40457720e+00, 1.47454295e+01,\n 1.56358798e+01, 1.56358798e+01],\n [3.89894744e+00, 3.89894744e+00, 8.54307290e+00, 1.46913700e+01,\n 1.56240633e+01, 1.56240633e+01],\n [3.94881489e+00, 3.94881489e+00, 8.68000183e+00, 1.46362550e+01,\n 1.56124152e+01, 1.56124152e+01],\n [3.99722251e+00, 3.99722251e+00, 8.81531907e+00, 1.45801056e+01,\n 1.56009552e+01, 1.56009552e+01],\n [4.04414305e+00, 4.04414305e+00, 8.94897617e+00, 1.45229472e+01,\n 1.55897031e+01, 1.55897031e+01],\n [4.08954967e+00, 4.08954967e+00, 9.08092045e+00, 1.44648099e+01,\n 1.55786787e+01, 1.55786787e+01],\n [4.13341596e+00, 4.13341596e+00, 9.21109424e+00, 1.44057295e+01,\n 1.55679014e+01, 1.55679014e+01],\n [4.17571599e+00, 4.17571599e+00, 9.33943387e+00, 1.43457486e+01,\n 1.55573906e+01, 1.55573906e+01],\n [4.21642438e+00, 4.21642438e+00, 9.46586854e+00, 1.42849178e+01,\n 1.55471651e+01, 1.55471651e+01],\n [4.25551631e+00, 4.25551631e+00, 9.59031884e+00, 1.42232967e+01,\n 1.55372439e+01, 1.55372439e+01],\n [4.29296759e+00, 4.29296759e+00, 9.71269507e+00, 1.41609564e+01,\n 1.55276452e+01, 1.55276452e+01],\n [4.32875473e+00, 4.32875473e+00, 9.83289509e+00, 1.40979808e+01,\n 1.55183871e+01, 1.55183871e+01],\n [4.36285493e+00, 4.36285493e+00, 9.95080172e+00, 1.40344699e+01,\n 1.55094870e+01, 1.55094870e+01],\n [4.39524622e+00, 4.39524622e+00, 1.00662796e+01, 1.39705427e+01,\n 1.55009619e+01, 1.55009619e+01],\n [4.42590741e+00, 4.42590741e+00, 1.01791712e+01, 1.39063409e+01,\n 1.54928283e+01, 1.54928283e+01],\n [4.45481822e+00, 4.45481822e+00, 1.02892922e+01, 1.38420341e+01,\n 1.54851020e+01, 1.54851020e+01],\n [4.48195930e+00, 4.48195930e+00, 1.03964254e+01, 1.37778256e+01,\n 1.54777983e+01, 1.54777983e+01],\n [4.50731227e+00, 4.50731227e+00, 1.05003136e+01, 1.37139594e+01,\n 1.54709315e+01, 1.54709315e+01],\n [4.53085979e+00, 4.53085979e+00, 1.06006514e+01, 1.36507288e+01,\n 1.54645154e+01, 1.54645154e+01],\n [4.55258558e+00, 4.55258558e+00, 1.06970744e+01, 1.35884865e+01,\n 1.54585629e+01, 1.54585629e+01],\n [4.57247450e+00, 4.57247450e+00, 1.07891482e+01, 1.35276567e+01,\n 1.54530860e+01, 1.54530860e+01],\n [4.59051254e+00, 4.59051254e+00, 1.08763552e+01, 1.34687473e+01,\n 1.54480960e+01, 1.54480960e+01],\n [4.60668693e+00, 4.60668693e+00, 1.09580822e+01, 1.34123627e+01,\n 1.54436029e+01, 1.54436029e+01],\n [4.62098611e+00, 4.62098611e+00, 1.10336096e+01, 1.33592147e+01,\n 1.54396162e+01, 1.54396162e+01],\n [4.63339981e+00, 4.63339981e+00, 1.11021066e+01, 1.33101273e+01,\n 1.54361441e+01, 1.54361441e+01],\n [4.64391906e+00, 4.64391906e+00, 1.11626377e+01, 1.32660299e+01,\n 1.54331937e+01, 1.54331937e+01],\n [4.65253622e+00, 4.65253622e+00, 1.12141885e+01, 1.32279317e+01,\n 1.54307713e+01, 1.54307713e+01],\n [4.65924501e+00, 4.65924501e+00, 1.12557173e+01, 1.31968704e+01,\n 1.54288819e+01, 1.54288819e+01],\n [4.66404052e+00, 4.66404052e+00, 1.12862369e+01, 1.31738300e+01,\n 1.54275295e+01, 1.54275295e+01],\n [4.66691923e+00, 4.66691923e+00, 1.13049205e+01, 1.31596347e+01,\n 1.54267169e+01, 1.54267169e+01],\n [4.66787904e+00, 4.66787904e+00, 1.13112137e+01, 1.31548379e+01,\n 1.54264459e+01, 1.54264459e+01]]),\n array([[ 4.66787904, 4.66787904, 11.31121369, 13.15483786, 15.42644585,\n 15.42644585],\n [ 4.66883944, 4.67093501, 11.31069683, 13.15420714, 15.42624753,\n 15.42662672],\n [ 4.6717197 , 4.68008535, 11.30914699, 13.15231706, 15.42565317,\n 15.42716712],\n [ 4.67651706, 4.69527771, 11.30656644, 13.14917383, 15.42466453,\n 15.42806041],\n [ 4.68322686, 4.71642595, 11.30295898, 13.14478769, 15.42328455,\n 15.42929564],\n [ 4.69184265, 4.74341172, 11.29832994, 13.13917277, 15.42151735,\n 15.43085774],\n [ 4.70235612, 4.77608661, 11.2926863 , 13.13234687, 15.41936818,\n 15.43272765],\n [ 4.71475714, 4.8142747 , 11.28603666, 13.12433117, 15.41684348,\n 15.43488268],\n [ 4.72903381, 4.85777545, 11.2783914 , 13.11514998, 15.4139508 ,\n 15.43729674],\n [ 4.74517241, 4.90636678, 11.26976269, 13.10483036, 15.41069884,\n 15.43994075],\n [ 4.7631575 , 4.95980823, 11.26016464, 13.09340178, 15.40709737,\n 15.44278297],\n [ 4.78297187, 5.01784414, 11.2496134 , 13.08089571, 15.40315728,\n 15.44578941],\n [ 4.80459662, 5.08020666, 11.2381273 , 13.06734527, 15.39889052,\n 15.4489242 ],\n [ 4.82801117, 5.14661861, 11.22572702, 13.0527848 , 15.39431009,\n 15.45215004],\n [ 4.85319328, 5.21679606, 11.21243575, 13.0372495 , 15.38943 ,\n 15.45542857],\n [ 4.88011907, 5.29045068, 11.1982794 , 13.02077504, 15.38426525,\n 15.45872076],\n [ 4.90876308, 5.36729169, 11.18328681, 13.00339721, 15.37883182,\n 15.46198731],\n [ 4.93909829, 5.44702758, 11.16749005, 12.98515157, 15.3731466 ,\n 15.46518895],\n [ 4.97109613, 5.5293674 , 11.15092462, 12.96607314, 15.3672274 ,\n 15.46828687],\n [ 5.00472652, 5.61402185, 11.13362983, 12.94619611, 15.36109287,\n 15.47124292],\n [ 5.03995793, 5.700704 , 11.11564913, 12.92555359, 15.35476249,\n 15.47401998],\n [ 5.07675735, 5.78912978, 11.09703046, 12.90417733, 15.34825653,\n 15.47658222],\n [ 5.11509038, 5.87901817, 11.07782674, 12.88209755, 15.34159598,\n 15.47889527],\n [ 5.15492119, 5.97009122, 11.05809624, 12.85934274, 15.33480255,\n 15.48092653],\n [ 5.19621261, 6.06207386, 11.03790317, 12.83593951, 15.32789857,\n 15.48264529],\n [ 5.23892611, 6.15469351, 11.01731817, 12.81191244, 15.32090699,\n 15.48402293],\n [ 5.28302184, 6.24767954, 10.99641896, 12.78728396, 15.3138513 ,\n 15.48503308],\n [ 5.32845864, 6.34076267, 10.9752909 , 12.76207432, 15.30675548,\n 15.48565171],\n [ 5.37519406, 6.43367414, 10.9540277 , 12.73630143, 15.29964395,\n 15.48585731],\n [ 5.42318436, 6.52614493, 10.93273212, 12.7099809 , 15.2925415 ,\n 15.48563092],\n [ 5.47238454, 6.61790486, 10.91151663, 12.68312596, 15.28547325,\n 15.48495625],\n [ 5.52274835, 6.7086817 , 10.89050415, 12.65574747, 15.27846454,\n 15.48381973],\n [ 5.57422825, 6.79820026, 10.86982865, 12.62785393, 15.27154095,\n 15.48221057],\n [ 5.62677547, 6.88618163, 10.84963575, 12.5994515 , 15.26472812,\n 15.48012081],\n [ 5.68033995, 6.97234249, 10.83008312, 12.57054404, 15.25805176,\n 15.47754532],\n [ 5.73487036, 7.05639464, 10.81134075, 12.5411332 , 15.25153756,\n 15.47448184],\n [ 5.79031407, 7.13804489, 10.7935908 , 12.51121847, 15.24521107,\n 15.47093096],\n [ 5.84661715, 7.21699523, 10.77702722, 12.4807973 , 15.23909766,\n 15.46689616],\n [ 5.90372431, 7.2929437 , 10.76185465, 12.44986521, 15.23322244,\n 15.46238371],\n [ 5.96157886, 7.36558575, 10.74828691, 12.41841593, 15.22761012,\n 15.45740272],\n [ 6.0201227 , 7.43461652, 10.73654446, 12.38644156, 15.22228498,\n 15.45196503],\n [ 6.07929625, 7.49973393, 10.72685125, 12.35393277, 15.21727073,\n 15.44608518],\n [ 6.13903837, 7.56064276, 10.71943035, 12.32087899, 15.21259043,\n 15.43978036],\n [ 6.19928628, 7.61705972, 10.71449888, 12.28726865, 15.20826641,\n 15.43307027],\n [ 6.25997552, 7.66871935, 10.71226189, 12.25308943, 15.2043201 ,\n 15.42597708],\n [ 6.32103977, 7.71538058, 10.71290574, 12.21832858, 15.20077199,\n 15.41852527],\n [ 6.3824108 , 7.75683366, 10.71659108, 12.1829732 , 15.19764149,\n 15.41074154],\n [ 6.44401828, 7.79290678, 10.72344609, 12.14701063, 15.1949468 ,\n 15.40265463],\n [ 6.50578968, 7.82347218, 10.73356042, 12.11042881, 15.19270483,\n 15.39429522],\n [ 6.56765 , 7.84845077, 10.74698037, 12.07321672, 15.19093108,\n 15.3856957 ],\n [ 6.62952167, 7.86781512, 10.76370597, 12.03536482, 15.18963947,\n 15.37689002],\n [ 6.69132422, 7.88159025, 10.78369008, 11.99686561, 15.18884231,\n 15.36791351],\n [ 6.75297411, 7.88985221, 10.80683981, 11.95771409, 15.18855011,\n 15.35880262],\n [ 6.81438433, 7.89272444, 10.83302013, 11.91790844, 15.18877153,\n 15.34959476],\n [ 6.87546417, 7.8903724 , 10.86205919, 11.87745058, 15.18951322,\n 15.34032804],\n [ 6.93611876, 7.88299691, 10.89375497, 11.83634691, 15.19077974,\n 15.33104105],\n [ 6.99624871, 7.87082671, 10.92788271, 11.79460901, 15.19257349,\n 15.32177261],\n [ 7.05574959, 7.85411092, 10.9642024 , 11.75225444, 15.19489459,\n 15.31256153],\n [ 7.11451149, 7.83311182, 11.00246595, 11.70930758, 15.1977408 ,\n 15.30344637],\n [ 7.17241836, 7.80809838, 11.04242367, 11.66580048, 15.2011075 ,\n 15.29446521],\n [ 7.22934748, 7.77934065, 11.08382976, 11.62177384, 15.2049876 ,\n 15.2856554 ],\n [ 7.28516874, 7.7471053 , 11.12644676, 11.57727795, 15.20937152,\n 15.27705331],\n [ 7.33974397, 7.7116521 , 11.17004895, 11.53237371, 15.21424716,\n 15.26869413],\n [ 7.39292613, 7.67323138, 11.21442482, 11.48713365, 15.21959992,\n 15.26061169],\n [ 7.44455862, 7.6320824 , 11.25937862, 11.44164301, 15.22541272,\n 15.25283819],\n [ 7.49447447, 7.58843228, 11.30473122, 11.39600072, 15.23166602,\n 15.24540409],\n [ 7.54249562, 7.54249562, 11.3503204 , 11.3503204 , 15.23833788,\n 15.23833788]]),\n array([[ 7.54249562, 7.54249562, 11.3503204 , 11.3503204 , 15.23833788,\n 15.23833788],\n [ 7.54166641, 7.54166641, 11.35130975, 11.35130975, 15.23801134,\n 15.23801134],\n [ 7.53918446, 7.53918446, 11.35427194, 11.35427194, 15.23703255,\n 15.23703255],\n [ 7.53506676, 7.53506676, 11.35918952, 11.35918952, 15.23540407,\n 15.23540407],\n [ 7.52934132, 7.52934132, 11.36603365, 11.36603365, 15.23313011,\n 15.23313011],\n [ 7.52204673, 7.52204673, 11.37476455, 11.37476455, 15.23021665,\n 15.23021665],\n [ 7.51323165, 7.51323165, 11.38533198, 11.38533198, 15.22667136,\n 15.22667136],\n [ 7.50295407, 7.50295407, 11.39767597, 11.39767597, 15.22250365,\n 15.22250365],\n [ 7.49128048, 7.49128048, 11.41172752, 11.41172752, 15.21772475,\n 15.21772475],\n [ 7.47828508, 7.47828508, 11.42740943, 11.42740943, 15.21234764,\n 15.21234764],\n [ 7.46404878, 7.46404878, 11.44463718, 11.44463718, 15.20638716,\n 15.20638716],\n [ 7.44865827, 7.44865827, 11.46331976, 11.46331976, 15.19986003,\n 15.19986003],\n [ 7.43220511, 7.43220511, 11.48336059, 11.48336059, 15.19278485,\n 15.19278485],\n [ 7.41478473, 7.41478473, 11.50465834, 11.50465834, 15.18518221,\n 15.18518221],\n [ 7.39649562, 7.39649562, 11.5271077 , 11.5271077 , 15.17707467,\n 15.17707467],\n [ 7.3774384 , 7.3774384 , 11.55060018, 11.55060018, 15.16848683,\n 15.16848683],\n [ 7.35771513, 7.35771513, 11.57502474, 11.57502474, 15.15944541,\n 15.15944541],\n [ 7.33742851, 7.33742851, 11.60026839, 11.60026839, 15.14997924,\n 15.14997924],\n [ 7.3166813 , 7.3166813 , 11.62621676, 11.62621676, 15.14011934,\n 15.14011934],\n [ 7.29557569, 7.29557569, 11.65275454, 11.65275454, 15.12989893,\n 15.12989893],\n [ 7.27421283, 7.27421283, 11.6797659 , 11.6797659 , 15.11935352,\n 15.11935352],\n [ 7.25269237, 7.25269237, 11.7071348 , 11.7071348 , 15.10852087,\n 15.10852087],\n [ 7.23111204, 7.23111204, 11.73474528, 11.73474528, 15.09744106,\n 15.09744106],\n [ 7.20956738, 7.20956738, 11.76248171, 11.76248171, 15.08615647,\n 15.08615647],\n [ 7.1881514 , 7.1881514 , 11.79022897, 11.79022897, 15.07471177,\n 15.07471177],\n [ 7.16695438, 7.16695438, 11.81787268, 11.81787268, 15.06315389,\n 15.06315389],\n [ 7.14606363, 7.14606363, 11.84529928, 11.84529928, 15.05153196,\n 15.05153196],\n [ 7.12556335, 7.12556335, 11.87239625, 11.87239625, 15.03989724,\n 15.03989724],\n [ 7.10553446, 7.10553446, 11.89905224, 11.89905224, 15.02830298,\n 15.02830298],\n [ 7.08605448, 7.08605448, 11.92515725, 11.92515725, 15.01680429,\n 15.01680429],\n [ 7.06719745, 7.06719745, 11.95060282, 11.95060282, 15.00545792,\n 15.00545792],\n [ 7.0490338 , 7.0490338 , 11.97528226, 11.97528226, 14.994322 ,\n 14.994322 ],\n [ 7.0316303 , 7.0316303 , 11.99909093, 11.99909093, 14.98345578,\n 14.98345578],\n [ 7.01504997, 7.01504997, 12.02192655, 12.02192655, 14.97291925,\n 14.97291925],\n [ 6.99935206, 6.99935206, 12.04368954, 12.04368954, 14.96277273,\n 14.96277273],\n [ 6.98459195, 6.98459195, 12.0642835 , 12.0642835 , 14.9530764 ,\n 14.9530764 ],\n [ 6.97082113, 6.97082113, 12.08361559, 12.08361559, 14.94388978,\n 14.94388978],\n [ 6.95808712, 6.95808712, 12.10159715, 12.10159715, 14.93527117,\n 14.93527117],\n [ 6.94643348, 6.94643348, 12.1181442 , 12.1181442 , 14.92727697,\n 14.92727697],\n [ 6.93589974, 6.93589974, 12.13317811, 12.13317811, 14.91996108,\n 14.91996108],\n [ 6.92652136, 6.92652136, 12.14662617, 12.14662617, 14.91337418,\n 14.91337418],\n [ 6.9183297 , 6.9183297 , 12.15842227, 12.15842227, 14.90756307,\n 14.90756307],\n [ 6.91135203, 6.91135203, 12.16850756, 12.16850756, 14.90256997,\n 14.90256997],\n [ 6.90561144, 6.90561144, 12.17683102, 12.17683102, 14.89843186,\n 14.89843186],\n [ 6.90112687, 6.90112687, 12.18335004, 12.18335004, 14.89517991,\n 14.89517991],\n [ 6.89791305, 6.89791305, 12.18803092, 12.18803092, 14.89283897,\n 14.89283897],\n [ 6.89598055, 6.89598055, 12.19084928, 12.19084928, 14.89142709,\n 14.89142709],\n [ 6.89533567, 6.89533567, 12.19179039, 12.19179039, 14.89095524,\n 14.89095524]])],\n 'eigenvectors': None,\n 'group_velocities': None},\n 'total_dos_dict': {'frequency_points': array([-1.21959488e+00, -1.12531879e+00, -1.03104271e+00, -9.36766620e-01,\n -8.42490534e-01, -7.48214449e-01, -6.53938363e-01, -5.59662277e-01,\n -4.65386192e-01, -3.71110106e-01, -2.76834020e-01, -1.82557935e-01,\n -8.82818488e-02, 5.99423689e-03, 1.00270323e-01, 1.94546408e-01,\n 2.88822494e-01, 3.83098580e-01, 4.77374665e-01, 5.71650751e-01,\n 6.65926837e-01, 7.60202922e-01, 8.54479008e-01, 9.48755094e-01,\n 1.04303118e+00, 1.13730727e+00, 1.23158335e+00, 1.32585944e+00,\n 1.42013552e+00, 1.51441161e+00, 1.60868769e+00, 1.70296378e+00,\n 1.79723987e+00, 1.89151595e+00, 1.98579204e+00, 2.08006812e+00,\n 2.17434421e+00, 2.26862029e+00, 2.36289638e+00, 2.45717246e+00,\n 2.55144855e+00, 2.64572464e+00, 2.74000072e+00, 2.83427681e+00,\n 2.92855289e+00, 3.02282898e+00, 3.11710506e+00, 3.21138115e+00,\n 3.30565724e+00, 3.39993332e+00, 3.49420941e+00, 3.58848549e+00,\n 3.68276158e+00, 3.77703766e+00, 3.87131375e+00, 3.96558984e+00,\n 4.05986592e+00, 4.15414201e+00, 4.24841809e+00, 4.34269418e+00,\n 4.43697026e+00, 4.53124635e+00, 4.62552244e+00, 4.71979852e+00,\n 4.81407461e+00, 4.90835069e+00, 5.00262678e+00, 5.09690286e+00,\n 5.19117895e+00, 5.28545504e+00, 5.37973112e+00, 5.47400721e+00,\n 5.56828329e+00, 5.66255938e+00, 5.75683546e+00, 5.85111155e+00,\n 5.94538764e+00, 6.03966372e+00, 6.13393981e+00, 6.22821589e+00,\n 6.32249198e+00, 6.41676806e+00, 6.51104415e+00, 6.60532024e+00,\n 6.69959632e+00, 6.79387241e+00, 6.88814849e+00, 6.98242458e+00,\n 7.07670066e+00, 7.17097675e+00, 7.26525284e+00, 7.35952892e+00,\n 7.45380501e+00, 7.54808109e+00, 7.64235718e+00, 7.73663326e+00,\n 7.83090935e+00, 7.92518544e+00, 8.01946152e+00, 8.11373761e+00,\n 8.20801369e+00, 8.30228978e+00, 8.39656586e+00, 8.49084195e+00,\n 8.58511804e+00, 8.67939412e+00, 8.77367021e+00, 8.86794629e+00,\n 8.96222238e+00, 9.05649846e+00, 9.15077455e+00, 9.24505064e+00,\n 9.33932672e+00, 9.43360281e+00, 9.52787889e+00, 9.62215498e+00,\n 9.71643106e+00, 9.81070715e+00, 9.90498323e+00, 9.99925932e+00,\n 1.00935354e+01, 1.01878115e+01, 1.02820876e+01, 1.03763637e+01,\n 1.04706397e+01, 1.05649158e+01, 1.06591919e+01, 1.07534680e+01,\n 1.08477441e+01, 1.09420202e+01, 1.10362963e+01, 1.11305723e+01,\n 1.12248484e+01, 1.13191245e+01, 1.14134006e+01, 1.15076767e+01,\n 1.16019528e+01, 1.16962289e+01, 1.17905049e+01, 1.18847810e+01,\n 1.19790571e+01, 1.20733332e+01, 1.21676093e+01, 1.22618854e+01,\n 1.23561615e+01, 1.24504375e+01, 1.25447136e+01, 1.26389897e+01,\n 1.27332658e+01, 1.28275419e+01, 1.29218180e+01, 1.30160941e+01,\n 1.31103701e+01, 1.32046462e+01, 1.32989223e+01, 1.33931984e+01,\n 1.34874745e+01, 1.35817506e+01, 1.36760267e+01, 1.37703027e+01,\n 1.38645788e+01, 1.39588549e+01, 1.40531310e+01, 1.41474071e+01,\n 1.42416832e+01, 1.43359593e+01, 1.44302353e+01, 1.45245114e+01,\n 1.46187875e+01, 1.47130636e+01, 1.48073397e+01, 1.49016158e+01,\n 1.49958919e+01, 1.50901679e+01, 1.51844440e+01, 1.52787201e+01,\n 1.53729962e+01, 1.54672723e+01, 1.55615484e+01, 1.56558245e+01,\n 1.57501005e+01, 1.58443766e+01, 1.59386527e+01, 1.60329288e+01,\n 1.61272049e+01, 1.62214810e+01, 1.63157571e+01, 1.64100331e+01,\n 1.65043092e+01, 1.65985853e+01, 1.66928614e+01, 1.67871375e+01,\n 1.68814136e+01, 1.69756897e+01, 1.70699657e+01, 1.71642418e+01,\n 1.72585179e+01, 1.73527940e+01, 1.74470701e+01, 1.75413462e+01,\n 1.76356223e+01]),\n 'total_dos': array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 3.17526949e-04, 1.35171618e-03, 2.50831797e-03,\n 3.78733233e-03, 5.26373813e-03, 6.90328284e-03, 8.78451412e-03,\n 1.08845716e-02, 1.31202482e-02, 1.58239881e-02, 1.84817583e-02,\n 2.14099537e-02, 2.44295300e-02, 2.78000795e-02, 3.14939706e-02,\n 3.52413320e-02, 3.92909859e-02, 4.36423577e-02, 4.83495504e-02,\n 5.31903107e-02, 5.81462801e-02, 6.35669356e-02, 6.94844360e-02,\n 7.55171874e-02, 8.19720137e-02, 8.86760193e-02, 9.58023138e-02,\n 1.03099606e-01, 1.11366958e-01, 1.19969573e-01, 1.28656383e-01,\n 1.38210214e-01, 1.48087177e-01, 1.58993039e-01, 1.70577194e-01,\n 1.82773665e-01, 1.96102840e-01, 2.10318186e-01, 2.25609695e-01,\n 2.42775583e-01, 2.61718244e-01, 2.82966510e-01, 3.07071183e-01,\n 3.35572804e-01, 3.71503640e-01, 4.23538191e-01, 5.01245367e-01,\n 5.06757340e-01, 5.10673514e-01, 5.13884731e-01, 5.18635687e-01,\n 5.22215630e-01, 5.26790868e-01, 5.30317993e-01, 5.33703746e-01,\n 5.38149099e-01, 5.41609848e-01, 5.45017573e-01, 5.48177732e-01,\n 5.52308667e-01, 5.54935999e-01, 5.58609041e-01, 5.61624143e-01,\n 5.64469403e-01, 5.68022742e-01, 5.70890330e-01, 5.72980739e-01,\n 5.77439994e-01, 5.83268678e-01, 5.49870464e-01, 4.81961887e-01,\n 4.49243839e-01, 4.26254220e-01, 4.10187378e-01, 3.95199652e-01,\n 3.98624284e-01, 4.05995249e-01, 4.25103229e-01, 4.54252120e-01,\n 4.65563502e-01, 3.65773926e-01, 2.85541037e-01, 2.23526600e-01,\n 1.44473263e-01, 1.04439534e-01, 1.08917911e-01, 1.13417776e-01,\n 1.18953226e-01, 1.24441198e-01, 1.29621905e-01, 1.36164980e-01,\n 1.42605861e-01, 1.49045426e-01, 1.56851391e-01, 1.64582559e-01,\n 1.72682584e-01, 1.82141611e-01, 1.91321788e-01, 2.02261449e-01,\n 2.13762731e-01, 2.26135950e-01, 2.40393404e-01, 2.55442497e-01,\n 2.74046636e-01, 2.93902607e-01, 3.19085171e-01, 3.48960866e-01,\n 3.91473391e-01, 4.54354038e-01, 5.99226889e-01, 6.56603266e-01,\n 4.43486451e-01, 3.58148235e-01, 2.92612110e-01, 2.34458733e-01,\n 1.57664249e-01, 9.44996839e-02, 7.64989495e-02, 6.21782198e-02,\n 7.46273535e-02, 8.86461614e-02, 1.06333999e-01, 1.36147948e-01,\n 1.87831258e-01, 2.67221370e-01, 2.89615750e-01, 3.09688343e-01,\n 3.30425521e-01, 3.30668402e-01, 3.40062237e-01, 3.45284499e-01,\n 3.55917538e-01, 3.60077500e-01, 3.69186627e-01, 3.71502854e-01,\n 3.72120651e-01, 3.48181936e-01, 3.16317708e-01, 2.98435672e-01,\n 2.84862196e-01, 2.74096441e-01, 2.64721157e-01, 2.56360104e-01,\n 2.48761334e-01, 2.41852996e-01, 2.35018844e-01, 2.28859604e-01,\n 2.22571780e-01, 2.16655364e-01, 2.10807826e-01, 2.04860365e-01,\n 1.99221497e-01, 1.93100666e-01, 1.87355107e-01, 2.53244401e-01,\n 8.43177422e-01, 1.43196664e+00, 3.18170027e+00, 2.79552678e+00,\n 3.13543115e+00, 4.55809708e+00, 2.72396129e+00, 1.52338820e+00,\n 1.06733102e+00, 7.67955185e-01, 5.18138351e-01, 2.28096624e-01,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00])},\n 'dynamical_matrix': array([[ 5.50912534e-01-0.00000000e+00j, 1.87768043e-17-4.38872430e-34j,\n 1.92709307e-17+5.81987920e-18j, -3.23420540e-17+4.98906381e-17j,\n -1.68412801e-30+5.84523400e-17j, -3.95652763e-17-3.56372327e-01j],\n [ 1.87768043e-17+4.38872430e-34j, 6.08181944e-01-0.00000000e+00j,\n -1.56143951e-16-1.15555797e-33j, -7.84788746e-30+5.84523400e-17j,\n -3.23420540e-17+2.45450096e-18j, 4.20932852e-30+1.58872850e-17j],\n [ 1.92709307e-17-5.81987920e-18j, -1.56143951e-16+1.15555797e-33j,\n 5.50912534e-01-0.00000000e+00j, -3.95652763e-17-3.56372327e-01j,\n 8.83023845e-30+1.58872850e-17j, -3.23420540e-17-3.36800318e-19j],\n [-3.23420540e-17-4.98906381e-17j, -7.84788746e-30-5.84523400e-17j,\n -3.95652763e-17+3.56372327e-01j, 5.50912534e-01-0.00000000e+00j,\n -9.24016421e-17-9.32340591e-30j, -8.30132400e-17-1.39858661e-29j],\n [-1.68412801e-30-5.84523400e-17j, -3.23420540e-17-2.45450096e-18j,\n 8.83023845e-30-1.58872850e-17j, -9.24016421e-17+9.32340591e-30j,\n 6.08181944e-01-0.00000000e+00j, -1.49226181e-16+4.66355445e-30j],\n [-3.95652763e-17+3.56372327e-01j, 4.20932852e-30-1.58872850e-17j,\n -3.23420540e-17+3.36800318e-19j, -8.30132400e-17+1.39858661e-29j,\n -1.49226181e-16-4.66355445e-30j, 5.50912534e-01-0.00000000e+00j]]),\n 'force_constants': array([[[[ 1.57151912e+01, 9.62277932e-16, 9.62277932e-16],\n [ 2.01508898e-31, 1.57151912e+01, -3.56057418e-15],\n [-6.31781728e-30, -4.83151945e-15, 1.57151912e+01]],\n \n [[-8.88178420e-13, -2.31481372e-29, -6.32321319e-29],\n [ 8.33886532e-31, 1.11022302e-12, -2.01086934e-28],\n [ 3.91666326e-46, -3.53409686e-28, 1.11022302e-12]],\n \n [[ 1.11022302e-12, 7.59032102e-29, 1.18329136e-28],\n [-1.78078948e-29, -8.88178420e-13, -4.17598292e-28],\n [ 5.04870979e-29, 2.72945873e-28, 1.11022302e-12]],\n \n ...,\n \n [[-6.32890635e-13, 5.20587829e-13, -5.20587829e-13],\n [-1.25573862e-13, -5.61838490e-13, -2.31561886e-13],\n [ 1.25573862e-13, -2.31561886e-13, -5.61838490e-13]],\n \n [[-5.61838490e-13, -1.25573862e-13, -2.31561886e-13],\n [ 5.20587829e-13, -6.32890635e-13, -5.20587829e-13],\n [-2.31561886e-13, 1.25573862e-13, -5.61838490e-13]],\n \n [[-1.15412764e-12, -4.39732284e-13, 3.10095250e-14],\n [-4.39732284e-13, -1.15412764e-12, 3.10095250e-14],\n [ 1.56993370e-13, 1.56993370e-13, -7.37047351e-13]]],\n \n \n [[[-8.88178420e-13, -2.31481372e-29, -6.32321319e-29],\n [ 8.33886532e-31, 1.11022302e-12, -2.01086934e-28],\n [ 1.63734993e-45, -3.53409686e-28, 1.11022302e-12]],\n \n [[ 1.57151912e+01, 9.62277932e-16, 9.62277932e-16],\n [ 2.19141532e-31, 1.57151912e+01, -3.56057418e-15],\n [-6.30018465e-30, -4.83151945e-15, 1.57151912e+01]],\n \n [[ 1.59872116e-12, 7.17863424e-29, 1.13595970e-28],\n [ 2.73057674e-29, 1.59872116e-12, -1.11175775e-27],\n [ 5.04870979e-29, -4.03896783e-28, 4.08562073e-12]],\n \n ...,\n \n [[-3.70859075e+00, -2.50222375e+00, 2.50222375e+00],\n [-2.50222375e+00, -3.70859075e+00, 2.50222375e+00],\n [ 2.50222375e+00, 2.50222375e+00, -3.70859075e+00]],\n \n [[-1.15412764e-12, -4.39732284e-13, 3.10095250e-14],\n [-4.39732284e-13, -1.15412764e-12, 3.10095250e-14],\n [ 1.56993370e-13, 1.56993370e-13, -7.37047351e-13]],\n \n [[-5.61838490e-13, -1.25573862e-13, -2.31561886e-13],\n [ 5.20587829e-13, -6.32890635e-13, -5.20587829e-13],\n [-2.31561886e-13, 1.25573862e-13, -5.61838490e-13]]],\n \n \n [[[ 1.11022302e-12, 7.59032102e-29, 1.18329136e-28],\n [-1.78078948e-29, -8.88178420e-13, -4.17598292e-28],\n [ 5.04870979e-29, 2.72945873e-28, 1.11022302e-12]],\n \n [[ 1.59872116e-12, 7.17863424e-29, 1.13595970e-28],\n [ 2.73057674e-29, 1.59872116e-12, -1.11175775e-27],\n [ 5.04870979e-29, -4.03896783e-28, 4.08562073e-12]],\n \n [[ 1.57151912e+01, 9.62277932e-16, 9.62277932e-16],\n [ 2.19141532e-31, 1.57151912e+01, -3.56057418e-15],\n [-6.30018465e-30, -4.83151945e-15, 1.57151912e+01]],\n \n ...,\n \n [[-1.15412764e-12, -4.39732284e-13, 3.10095250e-14],\n [-4.39732284e-13, -1.15412764e-12, 3.10095250e-14],\n [ 1.56993370e-13, 1.56993370e-13, -7.37047351e-13]],\n \n [[-3.70859075e+00, -2.50222375e+00, 2.50222375e+00],\n [-2.50222375e+00, -3.70859075e+00, 2.50222375e+00],\n [ 2.50222375e+00, 2.50222375e+00, -3.70859075e+00]],\n \n [[-6.32890635e-13, 5.20587829e-13, -5.20587829e-13],\n [-1.25573862e-13, -5.61838490e-13, -2.31561886e-13],\n [ 1.25573862e-13, -2.31561886e-13, -5.61838490e-13]]],\n \n \n ...,\n \n \n [[[-6.32890635e-13, 5.20587829e-13, -5.20587829e-13],\n [-1.25573862e-13, -5.61838490e-13, -2.31561886e-13],\n [ 1.25573862e-13, -2.31561886e-13, -5.61838490e-13]],\n \n [[-3.70859075e+00, -2.50222375e+00, 2.50222375e+00],\n [-2.50222375e+00, -3.70859075e+00, 2.50222375e+00],\n [ 2.50222375e+00, 2.50222375e+00, -3.70859075e+00]],\n \n [[-1.15412764e-12, -4.39732284e-13, 3.10095250e-14],\n [-4.39732284e-13, -1.15412764e-12, 3.10095250e-14],\n [ 1.56993370e-13, 1.56993370e-13, -7.37047351e-13]],\n \n ...,\n \n [[ 1.57151912e+01, -2.88683380e-15, -2.88683380e-15],\n [-1.92455586e-15, 1.57151912e+01, -4.83151945e-15],\n [-1.92455586e-15, -3.56057418e-15, 1.57151912e+01]],\n \n [[ 1.59872116e-12, -2.84139296e-28, -6.91248574e-28],\n [-1.83165100e-28, 1.59872116e-12, -1.36396903e-27],\n [-4.81749809e-28, -2.63475263e-28, 4.08562073e-12]],\n \n [[ 1.11022302e-12, 4.85458861e-29, -1.58051213e-28],\n [ 9.61487114e-29, -8.88178420e-13, -4.50532933e-28],\n [-1.17892900e-28, 2.33671810e-28, 1.11022302e-12]]],\n \n \n [[[-5.61838490e-13, -1.25573862e-13, -2.31561886e-13],\n [ 5.20587829e-13, -6.32890635e-13, -5.20587829e-13],\n [-2.31561886e-13, 1.25573862e-13, -5.61838490e-13]],\n \n [[-1.15412764e-12, -4.39732284e-13, 3.10095250e-14],\n [-4.39732284e-13, -1.15412764e-12, 3.10095250e-14],\n [ 1.56993370e-13, 1.56993370e-13, -7.37047351e-13]],\n \n [[-3.70859075e+00, -2.50222375e+00, 2.50222375e+00],\n [-2.50222375e+00, -3.70859075e+00, 2.50222375e+00],\n [ 2.50222375e+00, 2.50222375e+00, -3.70859075e+00]],\n \n ...,\n \n [[ 1.59872116e-12, -2.84139296e-28, -6.91248574e-28],\n [-1.83165100e-28, 1.59872116e-12, -1.36396903e-27],\n [-4.81749809e-28, -2.63475263e-28, 4.08562073e-12]],\n \n [[ 1.57151912e+01, -2.88683380e-15, -2.88683380e-15],\n [-1.92455586e-15, 1.57151912e+01, -4.83151945e-15],\n [-1.92455586e-15, -3.56057418e-15, 1.57151912e+01]],\n \n [[-8.88178420e-13, -7.27309754e-29, -1.12814970e-28],\n [-1.35963107e-28, 1.11022302e-12, -3.53409686e-28],\n [-1.36796994e-28, -2.01086934e-28, 1.11022302e-12]]],\n \n \n [[[-1.15412764e-12, -4.39732284e-13, 3.10095250e-14],\n [-4.39732284e-13, -1.15412764e-12, 3.10095250e-14],\n [ 1.56993370e-13, 1.56993370e-13, -7.37047351e-13]],\n \n [[-5.61838490e-13, -1.25573862e-13, -2.31561886e-13],\n [ 5.20587829e-13, -6.32890635e-13, -5.20587829e-13],\n [-2.31561886e-13, 1.25573862e-13, -5.61838490e-13]],\n \n [[-6.32890635e-13, 5.20587829e-13, -5.20587829e-13],\n [-1.25573862e-13, -5.61838490e-13, -2.31561886e-13],\n [ 1.25573862e-13, -2.31561886e-13, -5.61838490e-13]],\n \n ...,\n \n [[ 1.11022302e-12, 4.85458861e-29, -1.58051213e-28],\n [ 9.61487114e-29, -8.88178420e-13, -4.50532933e-28],\n [-1.17892900e-28, 2.33671810e-28, 1.11022302e-12]],\n \n [[-8.88178420e-13, -7.27309754e-29, -1.12814970e-28],\n [-1.35963107e-28, 1.11022302e-12, -3.53409686e-28],\n [-1.36796994e-28, -2.01086934e-28, 1.11022302e-12]],\n \n [[ 1.57151912e+01, -2.88683380e-15, -2.88683380e-15],\n [-1.92455586e-15, 1.57151912e+01, -4.83151945e-15],\n [-1.92455586e-15, -3.56057418e-15, 1.57151912e+01]]]])}"},"metadata":{}}],"id":"b7532997-2cc3-4404-b108-3c599e4f92e8"},{"cell_type":"markdown","source":"The calcualtion of the finite temperature phonons starts by computing the molecular dynamics trajectory using the \n`calc_molecular_dynamics_phonons_with_lammps()` function. This function is internally linked to [DynaPhoPy](https://abelcarreras.github.io/DynaPhoPy/)\nto return an `dynaphopy.dynamics.Dynamics` object: ","metadata":{},"id":"9080af2d-65ef-4710-80c3-66fd5bad9a76"},{"cell_type":"code","source":"trajectory = calc_molecular_dynamics_phonons_with_lammps(\n structure_ase=structure_ase,\n potential_dataframe=potential_dataframe,\n force_constants=workflow.phonopy.get_force_constants(), \n phonopy_unitcell=workflow.phonopy.get_unitcell(),\n phonopy_primitive_matrix=workflow.phonopy.get_primitive_matrix(),\n phonopy_supercell_matrix=workflow.phonopy.get_supercell_matrix(),\n total_time=2, # ps\n time_step=0.001, # ps\n relaxation_time=5, # ps\n silent=True,\n supercell=[2, 2, 2],\n memmap=False,\n velocity_only=True,\n temperature=600,\n)","metadata":{"trusted":true},"execution_count":14,"outputs":[],"id":"f2aada6d-89de-4fc0-a93d-f6fb43e33e8c"},{"cell_type":"markdown","source":"When a total of 2 picoseconds is selected to compute the finite temperature phonons with a timestep of 1 femto second\nthen this results in a total of 2000 molecular dynamics steps. While more molecular dynamics steps result in more precise\npredictions they also require more computational resources. ","metadata":{},"id":"5b533910-8e65-4c57-91bc-ccfa1e49d4ce"},{"cell_type":"markdown","source":"The postprocessing is executed using the [DynaPhoPy](https://abelcarreras.github.io/DynaPhoPy/) package: ","metadata":{},"id":"58cbd845-ad6e-41e1-b37c-dcc426e110c1"},{"cell_type":"code","source":"calculation = Quasiparticle(trajectory)\ncalculation.select_power_spectra_algorithm(2) # select FFT algorithm\ncalculation.get_renormalized_phonon_dispersion_bands()\nrenormalized_force_constants = calculation.get_renormalized_force_constants().get_array()\nrenormalized_force_constants","metadata":{"trusted":true},"execution_count":15,"outputs":[{"name":"stdout","text":"Using 2000 steps\nUsing Fast Fourier transform (Numpy) function\nset frequency range: 0.0 - 21.200000000000003\n\nQ-point: 1 / 32 [ 0.00000 0.00000 0.00000 ]\nHarmonic frequencies (THz):\n[2.18910938e-06 2.19854601e-06 2.20383682e-06 1.60678991e+01\n 1.60678991e+01 1.60678991e+01]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nMD cell size relation: [2 2 2]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\n\nPeak # 1\n----------------------------------------------\nWidth 0.472941 THz\nPosition 0.032545 THz\nArea () (Lorentzian) 0.000000 eV\nArea () (Total) 0.000000 eV\n<|dQ/dt|^2> 0.000000 eV\nOccupation number -0.500000\nFit temperature nan K\nBase line -0.000000 eV * ps\nMaximum height 0.000000 eV * ps\nFitting global error 534601240663.551514\nFrequency shift 0.032543 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.472941 THz\nPosition 0.032545 THz\nArea () (Lorentzian) 0.000000 eV\nArea () (Total) 0.000000 eV\n<|dQ/dt|^2> 0.000000 eV\nOccupation number -0.500000\nFit temperature nan K\nBase line -0.000000 eV * ps\nMaximum height 0.000000 eV * ps\nFitting global error 534601240663.551514\nFrequency shift 0.032543 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.472941 THz\nPosition 0.032545 THz\nArea () (Lorentzian) 0.000000 eV\nArea () (Total) 0.000000 eV\n<|dQ/dt|^2> 0.000000 eV\nOccupation number -0.500000\nFit temperature nan K\nBase line -0.000000 eV * ps\nMaximum height 0.000000 eV * ps\nFitting global error 534601240663.551514\nFrequency shift 0.032543 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.786715 THz\nPosition 15.561772 THz\nArea () (Lorentzian) 0.014497 eV\nArea () (Total) 0.013722 eV\n<|dQ/dt|^2> 0.028993 eV\nOccupation number 2.330539\nFit temperature 332.921392 K\nBase line -0.000016 eV * ps\nMaximum height 0.011731 eV * ps\nFitting global error 0.033291\nFrequency shift -0.506127 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.786715 THz\nPosition 15.561772 THz\nArea () (Lorentzian) 0.014497 eV\nArea () (Total) 0.013722 eV\n<|dQ/dt|^2> 0.028993 eV\nOccupation number 2.330539\nFit temperature 332.921392 K\nBase line -0.000016 eV * ps\nMaximum height 0.011731 eV * ps\nFitting global error 0.033291\nFrequency shift -0.506127 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.786715 THz\nPosition 15.561772 THz\nArea () (Lorentzian) 0.014497 eV\nArea () (Total) 0.013722 eV\n<|dQ/dt|^2> 0.028993 eV\nOccupation number 2.330539\nFit temperature 332.921392 K\nBase line -0.000016 eV * ps\nMaximum height 0.011731 eV * ps\nFitting global error 0.033291\nFrequency shift -0.506127 THz\nFixing gamma point 0 frequencies\n\nQ-point: 2 / 32 [ 0.00000 0.25000 0.25000 ]\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\n\nPeak # 1\n----------------------------------------------\nWidth 0.520799 THz\nPosition 4.512511 THz\nArea () (Lorentzian) 0.018113 eV\nArea () (Total) 0.016786 eV\n<|dQ/dt|^2> 0.036226 eV\nOccupation number 11.696398\nFit temperature 420.145058 K\nBase line -0.000042 eV * ps\nMaximum height 0.022141 eV * ps\nFitting global error 0.016919\nFrequency shift -0.151463 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.520799 THz\nPosition 4.512511 THz\nArea () (Lorentzian) 0.018113 eV\nArea () (Total) 0.016786 eV\n<|dQ/dt|^2> 0.036226 eV\nOccupation number 11.696398\nFit temperature 420.145058 K\nBase line -0.000042 eV * ps\nMaximum height 0.022141 eV * ps\nFitting global error 0.016919\nFrequency shift -0.151463 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.884643 THz\nPosition 6.802090 THz\nArea () (Lorentzian) 0.034381 eV\nArea () (Total) 0.042075 eV\n<|dQ/dt|^2> 0.068762 eV\nOccupation number 14.858240\nFit temperature 797.669964 K\nBase line 0.000413 eV * ps\nMaximum height 0.024742 eV * ps\nFitting global error 0.034947\nFrequency shift -0.096079 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.816224 THz\nPosition 14.710909 THz\nArea () (Lorentzian) 0.050561 eV\nArea () (Total) 0.056117 eV\n<|dQ/dt|^2> 0.101122 eV\nOccupation number 9.943370\nFit temperature 1172.575784 K\nBase line 0.000331 eV * ps\nMaximum height 0.039435 eV * ps\nFitting global error 0.029537\nFrequency shift -0.459579 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.906396 THz\nPosition 15.069443 THz\nArea () (Lorentzian) 0.021839 eV\nArea () (Total) 0.023547 eV\n<|dQ/dt|^2> 0.043678 eV\nOccupation number 3.903565\nFit temperature 504.681860 K\nBase line 0.000115 eV * ps\nMaximum height 0.015339 eV * ps\nFitting global error 0.023072\nFrequency shift -0.486236 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.906396 THz\nPosition 15.069443 THz\nArea () (Lorentzian) 0.021839 eV\nArea () (Total) 0.023547 eV\n<|dQ/dt|^2> 0.043678 eV\nOccupation number 3.903565\nFit temperature 504.681860 K\nBase line 0.000115 eV * ps\nMaximum height 0.015339 eV * ps\nFitting global error 0.023072\nFrequency shift -0.486236 THz\n\nQ-point: 3 / 32 [ 0.00000 0.50000 0.50000 ]\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\n\nPeak # 1\n----------------------------------------------\nWidth 0.579259 THz\nPosition 6.561490 THz\nArea () (Lorentzian) 0.025327 eV\nArea () (Total) 0.027369 eV\n<|dQ/dt|^2> 0.050654 eV\nOccupation number 11.228659\nFit temperature 587.462942 K\nBase line 0.000121 eV * ps\nMaximum height 0.027835 eV * ps\nFitting global error 0.025639\nFrequency shift -0.333845 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.579259 THz\nPosition 6.561490 THz\nArea () (Lorentzian) 0.025327 eV\nArea () (Total) 0.027369 eV\n<|dQ/dt|^2> 0.050654 eV\nOccupation number 11.228659\nFit temperature 587.462942 K\nBase line 0.000121 eV * ps\nMaximum height 0.027835 eV * ps\nFitting global error 0.025639\nFrequency shift -0.333845 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.605260 THz\nPosition 11.933579 THz\nArea () (Lorentzian) 0.030516 eV\nArea () (Total) 0.034730 eV\n<|dQ/dt|^2> 0.061032 eV\nOccupation number 7.270035\nFit temperature 707.271378 K\nBase line 0.000225 eV * ps\nMaximum height 0.032097 eV * ps\nFitting global error 0.023688\nFrequency shift -0.258211 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.605260 THz\nPosition 11.933579 THz\nArea () (Lorentzian) 0.030516 eV\nArea () (Total) 0.034730 eV\n<|dQ/dt|^2> 0.061032 eV\nOccupation number 7.270035\nFit temperature 707.271378 K\nBase line 0.000225 eV * ps\nMaximum height 0.032097 eV * ps\nFitting global error 0.023688\nFrequency shift -0.258211 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.634083 THz\nPosition 14.446261 THz\nArea () (Lorentzian) 0.042334 eV\nArea () (Total) 0.048339 eV\n<|dQ/dt|^2> 0.084669 eV\nOccupation number 8.404323\nFit temperature 981.504236 K\nBase line 0.000327 eV * ps\nMaximum height 0.042504 eV * ps\nFitting global error 0.015367\nFrequency shift -0.444694 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.634083 THz\nPosition 14.446261 THz\nArea () (Lorentzian) 0.042334 eV\nArea () (Total) 0.048339 eV\n<|dQ/dt|^2> 0.084669 eV\nOccupation number 8.404323\nFit temperature 981.504236 K\nBase line 0.000327 eV * ps\nMaximum height 0.042504 eV * ps\nFitting global error 0.015367\nFrequency shift -0.444694 THz\n\nQ-point: 4 / 32 [ 0.00000 0.75000 0.75000 ]\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\n\nPeak # 1\n----------------------------------------------\nWidth 0.513715 THz\nPosition 4.501773 THz\nArea () (Lorentzian) 0.024073 eV\nArea () (Total) 0.021107 eV\n<|dQ/dt|^2> 0.048147 eV\nOccupation number 15.748632\nFit temperature 558.542395 K\nBase line -0.000113 eV * ps\nMaximum height 0.029833 eV * ps\nFitting global error 0.014530\nFrequency shift -0.162201 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.513715 THz\nPosition 4.501773 THz\nArea () (Lorentzian) 0.024073 eV\nArea () (Total) 0.021107 eV\n<|dQ/dt|^2> 0.048147 eV\nOccupation number 15.748632\nFit temperature 558.542395 K\nBase line -0.000113 eV * ps\nMaximum height 0.029833 eV * ps\nFitting global error 0.014530\nFrequency shift -0.162201 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.840450 THz\nPosition 6.833587 THz\nArea () (Lorentzian) 0.047750 eV\nArea () (Total) 0.056965 eV\n<|dQ/dt|^2> 0.095499 eV\nOccupation number 20.731750\nFit temperature 1108.018836 K\nBase line 0.000500 eV * ps\nMaximum height 0.036169 eV * ps\nFitting global error 0.027488\nFrequency shift -0.064582 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.864892 THz\nPosition 14.761576 THz\nArea () (Lorentzian) 0.036911 eV\nArea () (Total) 0.042399 eV\n<|dQ/dt|^2> 0.073823 eV\nOccupation number 7.097870\nFit temperature 855.439740 K\nBase line 0.000312 eV * ps\nMaximum height 0.027169 eV * ps\nFitting global error 0.033172\nFrequency shift -0.408912 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.690963 THz\nPosition 15.047965 THz\nArea () (Lorentzian) 0.029989 eV\nArea () (Total) 0.029744 eV\n<|dQ/dt|^2> 0.059977 eV\nOccupation number 5.555378\nFit temperature 694.419722 K\nBase line 0.000024 eV * ps\nMaximum height 0.027630 eV * ps\nFitting global error 0.016899\nFrequency shift -0.507714 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.690963 THz\nPosition 15.047965 THz\nArea () (Lorentzian) 0.029989 eV\nArea () (Total) 0.029744 eV\n<|dQ/dt|^2> 0.059977 eV\nOccupation number 5.555378\nFit temperature 694.419722 K\nBase line 0.000024 eV * ps\nMaximum height 0.027630 eV * ps\nFitting global error 0.016899\nFrequency shift -0.507714 THz\n\nQ-point: 5 / 32 [ 0.25000 0.00000 0.25000 ]\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nSkipped, equivalent to [0. 0.25 0.25]\n\nQ-point: 6 / 32 [ 0.25000 0.25000 0.50000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\n\nPeak # 1\n----------------------------------------------\nWidth 0.528069 THz\nPosition 4.477183 THz\nArea () (Lorentzian) 0.042227 eV\nArea () (Total) 0.040708 eV\n<|dQ/dt|^2> 0.084453 eV\nOccupation number 28.158070\nFit temperature 979.942696 K\nBase line -0.000024 eV * ps\nMaximum height 0.050907 eV * ps\nFitting global error 0.012211\nFrequency shift -0.190696 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.890764 THz\nPosition 6.695151 THz\nArea () (Lorentzian) 0.080890 eV\nArea () (Total) 0.093342 eV\n<|dQ/dt|^2> 0.161780 eV\nOccupation number 36.211198\nFit temperature 1877.262480 K\nBase line 0.000706 eV * ps\nMaximum height 0.057811 eV * ps\nFitting global error 0.020823\nFrequency shift -0.265939 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.879866 THz\nPosition 8.803246 THz\nArea () (Lorentzian) 0.043886 eV\nArea () (Total) 0.052217 eV\n<|dQ/dt|^2> 0.087772 eV\nOccupation number 14.647678\nFit temperature 1018.178741 K\nBase line 0.000449 eV * ps\nMaximum height 0.031753 eV * ps\nFitting global error 0.028094\nFrequency shift -0.202601 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.757650 THz\nPosition 13.371395 THz\nArea () (Lorentzian) 0.021906 eV\nArea () (Total) 0.026391 eV\n<|dQ/dt|^2> 0.043812 eV\nOccupation number 4.477924\nFit temperature 506.700041 K\nBase line 0.000237 eV * ps\nMaximum height 0.018407 eV * ps\nFitting global error 0.037761\nFrequency shift -0.353521 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.668122 THz\nPosition 14.983805 THz\nArea () (Lorentzian) 0.023784 eV\nArea () (Total) 0.024310 eV\n<|dQ/dt|^2> 0.047568 eV\nOccupation number 4.323155\nFit temperature 550.026025 K\nBase line 0.000052 eV * ps\nMaximum height 0.022663 eV * ps\nFitting global error 0.013903\nFrequency shift -0.442641 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.793991 THz\nPosition 15.147433 THz\nArea () (Lorentzian) 0.067893 eV\nArea () (Total) 0.078771 eV\n<|dQ/dt|^2> 0.135785 eV\nOccupation number 13.119087\nFit temperature 1575.015042 K\nBase line 0.000607 eV * ps\nMaximum height 0.054436 eV * ps\nFitting global error 0.022076\nFrequency shift -0.435323 THz\n\nQ-point: 7 / 32 [ 0.25000 0.50000 0.75000 ]\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\n\nPeak # 1\n----------------------------------------------\nWidth 0.907126 THz\nPosition 7.246330 THz\nArea () (Lorentzian) 0.086024 eV\nArea () (Total) 0.104037 eV\n<|dQ/dt|^2> 0.172047 eV\nOccupation number 35.571453\nFit temperature 1996.396673 K\nBase line 0.000973 eV * ps\nMaximum height 0.060371 eV * ps\nFitting global error 0.020717\nFrequency shift -0.296166 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.907126 THz\nPosition 7.246330 THz\nArea () (Lorentzian) 0.086024 eV\nArea () (Total) 0.104037 eV\n<|dQ/dt|^2> 0.172047 eV\nOccupation number 35.571453\nFit temperature 1996.396673 K\nBase line 0.000973 eV * ps\nMaximum height 0.060371 eV * ps\nFitting global error 0.020717\nFrequency shift -0.296166 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.639111 THz\nPosition 11.064519 THz\nArea () (Lorentzian) 0.021923 eV\nArea () (Total) 0.025269 eV\n<|dQ/dt|^2> 0.043847 eV\nOccupation number 5.520612\nFit temperature 507.650279 K\nBase line 0.000178 eV * ps\nMaximum height 0.021838 eV * ps\nFitting global error 0.024793\nFrequency shift -0.285801 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.639111 THz\nPosition 11.064519 THz\nArea () (Lorentzian) 0.021923 eV\nArea () (Total) 0.025269 eV\n<|dQ/dt|^2> 0.043847 eV\nOccupation number 5.520612\nFit temperature 507.650279 K\nBase line 0.000178 eV * ps\nMaximum height 0.021838 eV * ps\nFitting global error 0.024793\nFrequency shift -0.285801 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.828868 THz\nPosition 14.801411 THz\nArea () (Lorentzian) 0.039716 eV\nArea () (Total) 0.043893 eV\n<|dQ/dt|^2> 0.079432 eV\nOccupation number 7.653201\nFit temperature 920.616703 K\nBase line 0.000252 eV * ps\nMaximum height 0.030504 eV * ps\nFitting global error 0.031513\nFrequency shift -0.436927 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.828868 THz\nPosition 14.801411 THz\nArea () (Lorentzian) 0.039716 eV\nArea () (Total) 0.043893 eV\n<|dQ/dt|^2> 0.079432 eV\nOccupation number 7.653201\nFit temperature 920.616703 K\nBase line 0.000252 eV * ps\nMaximum height 0.030504 eV * ps\nFitting global error 0.031513\nFrequency shift -0.436927 THz\n\nQ-point: 8 / 32 [ 0.25000 0.75000 0.00000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\n\nPeak # 1\n----------------------------------------------\nWidth 0.522556 THz\nPosition 4.483775 THz\nArea () (Lorentzian) 0.037188 eV\nArea () (Total) 0.034635 eV\n<|dQ/dt|^2> 0.074376 eV\nOccupation number 24.701308\nFit temperature 862.984199 K\nBase line -0.000079 eV * ps\nMaximum height 0.045305 eV * ps\nFitting global error 0.012393\nFrequency shift -0.184104 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.898262 THz\nPosition 6.707279 THz\nArea () (Lorentzian) 0.067887 eV\nArea () (Total) 0.079212 eV\n<|dQ/dt|^2> 0.135775 eV\nOccupation number 30.254428\nFit temperature 1575.464581 K\nBase line 0.000635 eV * ps\nMaximum height 0.048114 eV * ps\nFitting global error 0.023773\nFrequency shift -0.253812 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.835420 THz\nPosition 8.803037 THz\nArea () (Lorentzian) 0.013150 eV\nArea () (Total) 0.016324 eV\n<|dQ/dt|^2> 0.026301 eV\nOccupation number 4.039095\nFit temperature 303.968669 K\nBase line 0.000166 eV * ps\nMaximum height 0.010021 eV * ps\nFitting global error 0.059276\nFrequency shift -0.202810 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.730369 THz\nPosition 13.368389 THz\nArea () (Lorentzian) 0.016678 eV\nArea () (Total) 0.021238 eV\n<|dQ/dt|^2> 0.033357 eV\nOccupation number 3.290872\nFit temperature 384.834117 K\nBase line 0.000234 eV * ps\nMaximum height 0.014538 eV * ps\nFitting global error 0.045590\nFrequency shift -0.356527 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.674322 THz\nPosition 14.951363 THz\nArea () (Lorentzian) 0.036155 eV\nArea () (Total) 0.038613 eV\n<|dQ/dt|^2> 0.072311 eV\nOccupation number 6.847775\nFit temperature 837.833762 K\nBase line 0.000157 eV * ps\nMaximum height 0.034134 eV * ps\nFitting global error 0.014619\nFrequency shift -0.475083 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.902049 THz\nPosition 15.073779 THz\nArea () (Lorentzian) 0.021209 eV\nArea () (Total) 0.022490 eV\n<|dQ/dt|^2> 0.042418 eV\nOccupation number 3.775244\nFit temperature 489.986369 K\nBase line 0.000094 eV * ps\nMaximum height 0.014968 eV * ps\nFitting global error 0.022499\nFrequency shift -0.508977 THz\n\nQ-point: 9 / 32 [ 0.50000 0.00000 0.50000 ]\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\nSkipped, equivalent to [0. 0.5 0.5]\n\nQ-point: 10 / 32 [ 0.50000 0.25000 0.75000 ]\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nSkipped, equivalent to [0.25 0.5 0.75]\n\nQ-point: 11 / 32 [ 0.50000 0.50000 0.00000 ]\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\nSkipped, equivalent to [0. 0.5 0.5]\n\nQ-point: 12 / 32 [ 0.50000 0.75000 0.25000 ]\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nSkipped, equivalent to [0.25 0.5 0.75]\n\nQ-point: 13 / 32 [ 0.75000 0.00000 0.75000 ]\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nSkipped, equivalent to [0. 0.75 0.75]\n\nQ-point: 14 / 32 [ 0.75000 0.25000 0.00000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\n\nPeak # 1\n----------------------------------------------\nWidth 0.521991 THz\nPosition 4.484158 THz\nArea () (Lorentzian) 0.036566 eV\nArea () (Total) 0.033926 eV\n<|dQ/dt|^2> 0.073131 eV\nOccupation number 24.277431\nFit temperature 848.537722 K\nBase line -0.000083 eV * ps\nMaximum height 0.044595 eV * ps\nFitting global error 0.012530\nFrequency shift -0.183721 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.899617 THz\nPosition 6.704187 THz\nArea () (Lorentzian) 0.061915 eV\nArea () (Total) 0.071943 eV\n<|dQ/dt|^2> 0.123830 eV\nOccupation number 27.561609\nFit temperature 1436.830957 K\nBase line 0.000565 eV * ps\nMaximum height 0.043814 eV * ps\nFitting global error 0.025259\nFrequency shift -0.256903 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.840794 THz\nPosition 8.777709 THz\nArea () (Lorentzian) 0.009473 eV\nArea () (Total) 0.011919 eV\n<|dQ/dt|^2> 0.018945 eV\nOccupation number 2.779076\nFit temperature 218.134959 K\nBase line 0.000127 eV * ps\nMaximum height 0.007172 eV * ps\nFitting global error 0.078651\nFrequency shift -0.228137 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.814357 THz\nPosition 13.294667 THz\nArea () (Lorentzian) 0.012215 eV\nArea () (Total) 0.016240 eV\n<|dQ/dt|^2> 0.024429 eV\nOccupation number 2.291679\nFit temperature 280.431129 K\nBase line 0.000205 eV * ps\nMaximum height 0.009549 eV * ps\nFitting global error 0.061800\nFrequency shift -0.430249 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.706639 THz\nPosition 14.920962 THz\nArea () (Lorentzian) 0.033379 eV\nArea () (Total) 0.034927 eV\n<|dQ/dt|^2> 0.066758 eV\nOccupation number 6.297384\nFit temperature 773.297146 K\nBase line 0.000113 eV * ps\nMaximum height 0.030072 eV * ps\nFitting global error 0.021423\nFrequency shift -0.505484 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.901748 THz\nPosition 15.110122 THz\nArea () (Lorentzian) 0.021178 eV\nArea () (Total) 0.023049 eV\n<|dQ/dt|^2> 0.042356 eV\nOccupation number 3.758704\nFit temperature 489.249960 K\nBase line 0.000121 eV * ps\nMaximum height 0.014951 eV * ps\nFitting global error 0.028888\nFrequency shift -0.472634 THz\n\nQ-point: 15 / 32 [ 0.75000 0.50000 0.25000 ]\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nSkipped, equivalent to [0.25 0.5 0.75]\n\nQ-point: 16 / 32 [ 0.75000 0.75000 0.50000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\n\nPeak # 1\n----------------------------------------------\nWidth 0.521626 THz\nPosition 4.484270 THz\nArea () (Lorentzian) 0.040369 eV\nArea () (Total) 0.037483 eV\n<|dQ/dt|^2> 0.080738 eV\nOccupation number 26.853838\nFit temperature 936.816651 K\nBase line -0.000091 eV * ps\nMaximum height 0.049268 eV * ps\nFitting global error 0.011912\nFrequency shift -0.183609 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.898998 THz\nPosition 6.706088 THz\nArea () (Lorentzian) 0.060155 eV\nArea () (Total) 0.069989 eV\n<|dQ/dt|^2> 0.120310 eV\nOccupation number 26.756362\nFit temperature 1395.986799 K\nBase line 0.000553 eV * ps\nMaximum height 0.042598 eV * ps\nFitting global error 0.025425\nFrequency shift -0.255003 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.847729 THz\nPosition 8.762397 THz\nArea () (Lorentzian) 0.009423 eV\nArea () (Total) 0.011871 eV\n<|dQ/dt|^2> 0.018846 eV\nOccupation number 2.767683\nFit temperature 216.985862 K\nBase line 0.000127 eV * ps\nMaximum height 0.007077 eV * ps\nFitting global error 0.078128\nFrequency shift -0.243450 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.822505 THz\nPosition 13.296042 THz\nArea () (Lorentzian) 0.012441 eV\nArea () (Total) 0.016789 eV\n<|dQ/dt|^2> 0.024882 eV\nOccupation number 2.343156\nFit temperature 285.744350 K\nBase line 0.000221 eV * ps\nMaximum height 0.009629 eV * ps\nFitting global error 0.060141\nFrequency shift -0.428874 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.692941 THz\nPosition 14.927237 THz\nArea () (Lorentzian) 0.037140 eV\nArea () (Total) 0.038953 eV\n<|dQ/dt|^2> 0.074280 eV\nOccupation number 7.060040\nFit temperature 860.720270 K\nBase line 0.000129 eV * ps\nMaximum height 0.034121 eV * ps\nFitting global error 0.019502\nFrequency shift -0.499209 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.873800 THz\nPosition 15.089642 THz\nArea () (Lorentzian) 0.020289 eV\nArea () (Total) 0.022192 eV\n<|dQ/dt|^2> 0.040578 eV\nOccupation number 3.585462\nFit temperature 468.522604 K\nBase line 0.000120 eV * ps\nMaximum height 0.014782 eV * ps\nFitting global error 0.026540\nFrequency shift -0.493114 THz\n\nQ-point: 17 / 32 [ 0.25000 0.25000 0.00000 ]\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nSkipped, equivalent to [0.25 0. 0.25]\n\nQ-point: 18 / 32 [ 0.25000 0.50000 0.25000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.25 0.25 0.5 ]\n\nQ-point: 19 / 32 [ 0.25000 0.75000 0.50000 ]\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nSkipped, equivalent to [0.25 0.5 0.75]\n\nQ-point: 20 / 32 [ 0.25000 0.00000 0.75000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.75 0.75 0.5 ]\n\nQ-point: 21 / 32 [ 0.50000 0.25000 0.25000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.25 0.5 0.25]\n\nQ-point: 22 / 32 [ 0.50000 0.50000 0.50000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\n\nPeak # 1\n----------------------------------------------\nWidth 0.531374 THz\nPosition 4.473540 THz\nArea () (Lorentzian) 0.029343 eV\nArea () (Total) 0.027597 eV\n<|dQ/dt|^2> 0.058686 eV\nOccupation number 19.430578\nFit temperature 680.883835 K\nBase line -0.000049 eV * ps\nMaximum height 0.035155 eV * ps\nFitting global error 0.015967\nFrequency shift -0.194339 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.531374 THz\nPosition 4.473540 THz\nArea () (Lorentzian) 0.029343 eV\nArea () (Total) 0.027597 eV\n<|dQ/dt|^2> 0.058686 eV\nOccupation number 19.430578\nFit temperature 680.883835 K\nBase line -0.000049 eV * ps\nMaximum height 0.035155 eV * ps\nFitting global error 0.015967\nFrequency shift -0.194339 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.538267 THz\nPosition 10.993312 THz\nArea () (Lorentzian) 0.062518 eV\nArea () (Total) 0.058145 eV\n<|dQ/dt|^2> 0.125036 eV\nOccupation number 16.779904\nFit temperature 1450.579488 K\nBase line -0.000158 eV * ps\nMaximum height 0.073941 eV * ps\nFitting global error 0.008088\nFrequency shift -0.317902 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.776728 THz\nPosition 12.855329 THz\nArea () (Lorentzian) 0.017087 eV\nArea () (Total) 0.019549 eV\n<|dQ/dt|^2> 0.034174 eV\nOccupation number 3.538695\nFit temperature 394.533163 K\nBase line 0.000136 eV * ps\nMaximum height 0.014005 eV * ps\nFitting global error 0.044153\nFrequency shift -0.299509 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.629022 THz\nPosition 14.951429 THz\nArea () (Lorentzian) 0.062984 eV\nArea () (Total) 0.068437 eV\n<|dQ/dt|^2> 0.125967 eV\nOccupation number 12.300000\nFit temperature 1461.048221 K\nBase line 0.000325 eV * ps\nMaximum height 0.063744 eV * ps\nFitting global error 0.012067\nFrequency shift -0.475017 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.629022 THz\nPosition 14.951429 THz\nArea () (Lorentzian) 0.062984 eV\nArea () (Total) 0.068437 eV\n<|dQ/dt|^2> 0.125967 eV\nOccupation number 12.300000\nFit temperature 1461.048221 K\nBase line 0.000325 eV * ps\nMaximum height 0.063744 eV * ps\nFitting global error 0.012067\nFrequency shift -0.475017 THz\n\nQ-point: 23 / 32 [ 0.50000 0.75000 0.75000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.25 0. 0.75]\n\nQ-point: 24 / 32 [ 0.50000 0.00000 0.00000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nSkipped, equivalent to [0.5 0.5 0.5]\n\nQ-point: 25 / 32 [ 0.75000 0.25000 0.50000 ]\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nSkipped, equivalent to [0.25 0.5 0.75]\n\nQ-point: 26 / 32 [ 0.75000 0.50000 0.75000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.25 0. 0.75]\n\nQ-point: 27 / 32 [ 0.75000 0.75000 0.00000 ]\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nSkipped, equivalent to [0. 0.75 0.75]\n\nQ-point: 28 / 32 [ 0.75000 0.00000 0.25000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.75 0.5 0.75]\n\nQ-point: 29 / 32 [ 0.00000 0.25000 0.75000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.75 0.5 0.75]\n\nQ-point: 30 / 32 [ 0.00000 0.50000 0.00000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nSkipped, equivalent to [0.5 0.5 0.5]\n\nQ-point: 31 / 32 [ 0.00000 0.75000 0.25000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.75 0.5 0.75]\n\nQ-point: 32 / 32 [ 0.00000 0.00000 0.50000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nSkipped, equivalent to [0.5 0.5 0.5]\n","output_type":"stream"},{"execution_count":15,"output_type":"execute_result","data":{"text/plain":"array([[[[ 1.47903370e+01, -7.27856464e-04, 8.95058148e-04],\n [-7.27856464e-04, 1.47903370e+01, 8.95058148e-04],\n [ 8.95058148e-04, 8.95058148e-04, 1.47889684e+01]],\n\n [[-8.53720262e-03, 7.27856464e-04, -8.95058148e-04],\n [ 7.27856464e-04, 7.22093450e-03, 8.95058148e-04],\n [-8.95058148e-04, 8.95058148e-04, 8.58955541e-03]],\n\n [[ 7.22093450e-03, 7.27856464e-04, 8.95058148e-04],\n [ 7.27856464e-04, -8.53720262e-03, -8.95058148e-04],\n [ 8.95058148e-04, -8.95058148e-04, 8.58955541e-03]],\n\n ...,\n\n [[-4.44967060e-03, 1.03899911e-04, -2.92254418e-03],\n [ 1.03899911e-04, 3.86955298e-03, 9.18164273e-03],\n [-2.92254418e-03, 9.18164273e-03, 2.64253878e-03]],\n\n [[ 3.86955298e-03, 1.03899911e-04, 9.18164273e-03],\n [ 1.03899911e-04, -4.44967060e-03, -2.92254418e-03],\n [ 9.18164273e-03, -2.92254418e-03, 2.64253878e-03]],\n\n [[ 4.35320043e-03, -8.69200588e-04, 7.43830393e-03],\n [-8.69200588e-04, 4.35320043e-03, 7.43830393e-03],\n [ 7.43830393e-03, 7.43830393e-03, 1.98168743e-03]]],\n\n\n [[[-8.53720262e-03, 7.27856464e-04, -8.95058148e-04],\n [ 7.27856464e-04, 7.22093450e-03, 8.95058148e-04],\n [-8.95058148e-04, 8.95058148e-04, 8.58955541e-03]],\n\n [[ 1.47903370e+01, -7.27856464e-04, 8.95058148e-04],\n [-7.27856464e-04, 1.47903370e+01, 8.95058148e-04],\n [ 8.95058148e-04, 8.95058148e-04, 1.47889684e+01]],\n\n [[ 5.72248779e-03, -7.27856464e-04, -8.95058148e-04],\n [-7.27856464e-04, 5.72248779e-03, -8.95058148e-04],\n [-8.95058148e-04, -8.95058148e-04, 1.30276827e-02]],\n\n ...,\n\n [[-3.48139117e+00, -2.36186546e+00, 2.36468410e+00],\n [-2.36186546e+00, -3.48139117e+00, 2.36468410e+00],\n [ 2.36468410e+00, 2.36468410e+00, -3.48016416e+00]],\n\n [[ 4.35320043e-03, -8.69200588e-04, 7.43830393e-03],\n [-8.69200588e-04, 4.35320043e-03, 7.43830393e-03],\n [ 7.43830393e-03, 7.43830393e-03, 1.98168743e-03]],\n\n [[ 3.86955298e-03, 1.03899911e-04, 9.18164273e-03],\n [ 1.03899911e-04, -4.44967060e-03, -2.92254418e-03],\n [ 9.18164273e-03, -2.92254418e-03, 2.64253878e-03]]],\n\n\n [[[ 7.22093450e-03, 7.27856464e-04, 8.95058148e-04],\n [ 7.27856464e-04, -8.53720262e-03, -8.95058148e-04],\n [ 8.95058148e-04, -8.95058148e-04, 8.58955541e-03]],\n\n [[ 5.72248779e-03, -7.27856464e-04, -8.95058148e-04],\n [-7.27856464e-04, 5.72248779e-03, -8.95058148e-04],\n [-8.95058148e-04, -8.95058148e-04, 1.30276827e-02]],\n\n [[ 1.47903370e+01, -7.27856464e-04, 8.95058148e-04],\n [-7.27856464e-04, 1.47903370e+01, 8.95058148e-04],\n [ 8.95058148e-04, 8.95058148e-04, 1.47889684e+01]],\n\n ...,\n\n [[ 4.35320043e-03, -8.69200588e-04, 7.43830393e-03],\n [-8.69200588e-04, 4.35320043e-03, 7.43830393e-03],\n [ 7.43830393e-03, 7.43830393e-03, 1.98168743e-03]],\n\n [[-3.48139117e+00, -2.36186546e+00, 2.36468410e+00],\n [-2.36186546e+00, -3.48139117e+00, 2.36468410e+00],\n [ 2.36468410e+00, 2.36468410e+00, -3.48016416e+00]],\n\n [[-4.44967060e-03, 1.03899911e-04, -2.92254418e-03],\n [ 1.03899911e-04, 3.86955298e-03, 9.18164273e-03],\n [-2.92254418e-03, 9.18164273e-03, 2.64253878e-03]]],\n\n\n ...,\n\n\n [[[-4.44967060e-03, 1.03899911e-04, -2.92254418e-03],\n [ 1.03899911e-04, 3.86955298e-03, 9.18164273e-03],\n [-2.92254418e-03, 9.18164273e-03, 2.64253878e-03]],\n\n [[-3.48139117e+00, -2.36186546e+00, 2.36468410e+00],\n [-2.36186546e+00, -3.48139117e+00, 2.36468410e+00],\n [ 2.36468410e+00, 2.36468410e+00, -3.48016416e+00]],\n\n [[ 4.35320043e-03, -8.69200588e-04, 7.43830393e-03],\n [-8.69200588e-04, 4.35320043e-03, 7.43830393e-03],\n [ 7.43830393e-03, 7.43830393e-03, 1.98168743e-03]],\n\n ...,\n\n [[ 1.47903370e+01, -7.27856464e-04, 8.95058148e-04],\n [-7.27856464e-04, 1.47903370e+01, 8.95058148e-04],\n [ 8.95058148e-04, 8.95058148e-04, 1.47889684e+01]],\n\n [[ 5.72248779e-03, -7.27856464e-04, -8.95058148e-04],\n [-7.27856464e-04, 5.72248779e-03, -8.95058148e-04],\n [-8.95058148e-04, -8.95058148e-04, 1.30276827e-02]],\n\n [[ 7.22093450e-03, 7.27856464e-04, 8.95058148e-04],\n [ 7.27856464e-04, -8.53720262e-03, -8.95058148e-04],\n [ 8.95058148e-04, -8.95058148e-04, 8.58955541e-03]]],\n\n\n [[[ 3.86955298e-03, 1.03899911e-04, 9.18164273e-03],\n [ 1.03899911e-04, -4.44967060e-03, -2.92254418e-03],\n [ 9.18164273e-03, -2.92254418e-03, 2.64253878e-03]],\n\n [[ 4.35320043e-03, -8.69200588e-04, 7.43830393e-03],\n [-8.69200588e-04, 4.35320043e-03, 7.43830393e-03],\n [ 7.43830393e-03, 7.43830393e-03, 1.98168743e-03]],\n\n [[-3.48139117e+00, -2.36186546e+00, 2.36468410e+00],\n [-2.36186546e+00, -3.48139117e+00, 2.36468410e+00],\n [ 2.36468410e+00, 2.36468410e+00, -3.48016416e+00]],\n\n ...,\n\n [[ 5.72248779e-03, -7.27856464e-04, -8.95058148e-04],\n [-7.27856464e-04, 5.72248779e-03, -8.95058148e-04],\n [-8.95058148e-04, -8.95058148e-04, 1.30276827e-02]],\n\n [[ 1.47903370e+01, -7.27856464e-04, 8.95058148e-04],\n [-7.27856464e-04, 1.47903370e+01, 8.95058148e-04],\n [ 8.95058148e-04, 8.95058148e-04, 1.47889684e+01]],\n\n [[-8.53720262e-03, 7.27856464e-04, -8.95058148e-04],\n [ 7.27856464e-04, 7.22093450e-03, 8.95058148e-04],\n [-8.95058148e-04, 8.95058148e-04, 8.58955541e-03]]],\n\n\n [[[ 4.35320043e-03, -8.69200588e-04, 7.43830393e-03],\n [-8.69200588e-04, 4.35320043e-03, 7.43830393e-03],\n [ 7.43830393e-03, 7.43830393e-03, 1.98168743e-03]],\n\n [[ 3.86955298e-03, 1.03899911e-04, 9.18164273e-03],\n [ 1.03899911e-04, -4.44967060e-03, -2.92254418e-03],\n [ 9.18164273e-03, -2.92254418e-03, 2.64253878e-03]],\n\n [[-4.44967060e-03, 1.03899911e-04, -2.92254418e-03],\n [ 1.03899911e-04, 3.86955298e-03, 9.18164273e-03],\n [-2.92254418e-03, 9.18164273e-03, 2.64253878e-03]],\n\n ...,\n\n [[ 7.22093450e-03, 7.27856464e-04, 8.95058148e-04],\n [ 7.27856464e-04, -8.53720262e-03, -8.95058148e-04],\n [ 8.95058148e-04, -8.95058148e-04, 8.58955541e-03]],\n\n [[-8.53720262e-03, 7.27856464e-04, -8.95058148e-04],\n [ 7.27856464e-04, 7.22093450e-03, 8.95058148e-04],\n [-8.95058148e-04, 8.95058148e-04, 8.58955541e-03]],\n\n [[ 1.47903370e+01, -7.27856464e-04, 8.95058148e-04],\n [-7.27856464e-04, 1.47903370e+01, 8.95058148e-04],\n [ 8.95058148e-04, 8.95058148e-04, 1.47889684e+01]]]])"},"metadata":{}}],"id":"54169376-3978-4c25-b1d6-509030a4cea7"},{"cell_type":"markdown","source":"It calculates the re-normalized force constants which can then be used to calculate the finite temperature properties. ","metadata":{},"id":"2eb26d68-9d7e-45de-9b97-013a8e7e11bb"},{"cell_type":"markdown","source":"In addition the [DynaPhoPy](https://abelcarreras.github.io/DynaPhoPy/) package can be used to directly compare the \nfinite temperature phonon spectrum with the 0K phonon spectrum calulated with the finite displacement method: ","metadata":{},"id":"30bdcd29-a41b-4781-a2cd-6af0ba290883"},{"cell_type":"code","source":"calculation.plot_renormalized_phonon_dispersion_bands()","metadata":{"trusted":true},"execution_count":16,"outputs":[{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}],"id":"8d8239ad-30eb-4f7a-a5aa-91e5030fa74d"},{"cell_type":"markdown","source":"### Langevin Thermostat \nIn addition to the molecular dynamics implemented in the LAMMPS simulation code, the `atomistics` package also provides\nthe `LangevinWorkflow` which implements molecular dynamics independent of the specific simulation code. \n","metadata":{},"id":"c5bada5c-706c-4d5c-9141-1d6bd146d445"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import evaluate_with_lammps_library, get_potential_by_name\nfrom atomistics.workflows import LangevinWorkflow\nfrom pylammpsmpi import LammpsASELibrary\n\nsteps = 300\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\nworkflow = LangevinWorkflow(\n structure=bulk(\"Al\", cubic=True).repeat([2, 2, 2]), \n temperature=1000.0,\n overheat_fraction=2.0,\n damping_timescale=100.0,\n time_step=1,\n)\nlmp = LammpsASELibrary(\n working_directory=None,\n cores=1,\n comm=None,\n logger=None,\n log_file=None,\n library=None,\n diable_log_file=True,\n)\neng_pot_lst, eng_kin_lst = [], []\nfor i in range(steps):\n task_dict = workflow.generate_structures()\n result_dict = evaluate_with_lammps_library(\n task_dict=task_dict,\n potential_dataframe=potential_dataframe,\n lmp=lmp,\n )\n eng_pot, eng_kin = workflow.analyse_structures(output_dict=result_dict)\n eng_pot_lst.append(eng_pot)\n eng_kin_lst.append(eng_kin)\nlmp.close()","metadata":{"trusted":true},"execution_count":17,"outputs":[],"id":"fa69a7f8-940a-4fb9-aae3-1ac68d4255f2"},{"cell_type":"markdown","source":"The advantage of this implementation is that the user can directly interact with the simulation between the individual\nmolecular dynamics simulation steps. This provides a lot of flexibility to prototype new simulation methods. The input\nparameters of the `LangevinWorkflow` are:\n\n* `structure` the `ase.atoms.Atoms` object which is used as initial structure for the molecular dynamics calculation \n* `temperature` the temperature of the molecular dynamics calculation given in Kelvin\n* `overheat_fraction` the over heating fraction of the Langevin thermostat\n* `damping_timescale` the damping timescale of the Langevin thermostat \n* `time_step` the time steps of the Langevin thermostat\n","metadata":{},"id":"d77f71c6-7afd-496d-a3bf-db517623d159"},{"cell_type":"markdown","source":"## Harmonic Approximation \nThe harmonic approximation is implemented in two variations, once with constant volume and once including the volume \nexpansion at finite temperature also known as quasi-harmonic approximation. Both of these are based on the [phonopy](https://phonopy.github.io/phonopy/)\npackage. ","metadata":{},"id":"6944d8c5-718d-4d87-956c-d456c151c331"},{"cell_type":"markdown","source":"### Phonons \nTo calculate the phonons at a fixed volume the `PhonopyWorkflow` is used:","metadata":{},"id":"4f699026-d1a8-47a3-b354-6c8572550a50"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import evaluate_with_lammps, get_potential_by_name\nfrom atomistics.workflows import PhonopyWorkflow\nfrom phonopy.units import VaspToTHz\n\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\nworkflow = PhonopyWorkflow(\n structure=bulk(\"Al\", cubic=True), \n interaction_range=10,\n factor=VaspToTHz,\n displacement=0.01,\n dos_mesh=20,\n primitive_matrix=None,\n number_of_snapshots=None,\n)\ntask_dict = workflow.generate_structures()\nresult_dict = evaluate_with_lammps(\n task_dict=task_dict,\n potential_dataframe=potential_dataframe,\n)\nphonopy_dict = workflow.analyse_structures(output_dict=result_dict)","metadata":{"trusted":true},"execution_count":18,"outputs":[],"id":"7ac74f80-d613-4a96-b841-5a2973b949a9"},{"cell_type":"markdown","source":"The `PhonopyWorkflow` takes the following inputs: \n\n* `structure` the `ase.atoms.Atoms` object to calculate the phonon spectrum\n* `interaction_range` the cutoff radius to consider for identifying the interaction between the atoms\n* `factor` conversion factor, typically just `phonopy.units.VaspToTHz` \n* `displacement` displacement to calculate the forces \n* `dos_mesh` mesh for the density of states \n* `primitive_matrix` primitive matrix\n* `number_of_snapshots` number of snapshots to calculate\n\nIn addition to the phonon properties, the `PhonopyWorkflow` also enables the calculation of thermal properties: ","metadata":{},"id":"0528bcb2-55ea-4df0-a0b6-71c99dbd9f57"},{"cell_type":"code","source":"tp_dict = workflow.get_thermal_properties(\n t_min=1, \n t_max=1500, \n t_step=50, \n temperatures=None,\n cutoff_frequency=None,\n pretend_real=False,\n band_indices=None,\n is_projection=False,\n)\nprint(tp_dict)","metadata":{"trusted":true},"execution_count":19,"outputs":[{"name":"stdout","text":"{'temperatures': array([1.000e+00, 5.100e+01, 1.010e+02, 1.510e+02, 2.010e+02, 2.510e+02,\n 3.010e+02, 3.510e+02, 4.010e+02, 4.510e+02, 5.010e+02, 5.510e+02,\n 6.010e+02, 6.510e+02, 7.010e+02, 7.510e+02, 8.010e+02, 8.510e+02,\n 9.010e+02, 9.510e+02, 1.001e+03, 1.051e+03, 1.101e+03, 1.151e+03,\n 1.201e+03, 1.251e+03, 1.301e+03, 1.351e+03, 1.401e+03, 1.451e+03,\n 1.501e+03]), 'volumes': array([66.430125, 66.430125, 66.430125, 66.430125, 66.430125, 66.430125,\n 66.430125, 66.430125, 66.430125, 66.430125, 66.430125, 66.430125,\n 66.430125, 66.430125, 66.430125, 66.430125, 66.430125, 66.430125,\n 66.430125, 66.430125, 66.430125, 66.430125, 66.430125, 66.430125,\n 66.430125, 66.430125, 66.430125, 66.430125, 66.430125, 66.430125,\n 66.430125]), 'free_energy': array([ 0.14914132, 0.14837894, 0.13954171, 0.11738723, 0.08264779,\n 0.03712237, -0.01759836, -0.08025513, -0.14986079, -0.22563203,\n -0.30693668, -0.39325592, -0.48415731, -0.57927552, -0.67829812,\n -0.78095507, -0.88701079, -0.99625805, -1.10851315, -1.22361223,\n -1.3414082 , -1.46176834, -1.58457228, -1.70971039, -1.8370824 ,\n -1.96659625, -2.09816715, -2.23171671, -2.3671723 , -2.5044664 ,\n -2.64353611]), 'entropy': array([1.10364016e-08, 5.98829810e+00, 2.96478195e+01, 5.54593816e+01,\n 7.80099308e+01, 9.71787932e+01, 1.13608521e+02, 1.27894607e+02,\n 1.40492150e+02, 1.51738264e+02, 1.61883985e+02, 1.71119149e+02,\n 1.79589851e+02, 1.87410480e+02, 1.94672040e+02, 2.01447985e+02,\n 2.07798389e+02, 2.13772961e+02, 2.19413270e+02, 2.24754417e+02,\n 2.29826293e+02, 2.34654555e+02, 2.39261386e+02, 2.43666089e+02,\n 2.47885561e+02, 2.51934678e+02, 2.55826598e+02, 2.59573021e+02,\n 2.63184393e+02, 2.66670075e+02, 2.70038493e+02]), 'heat_capacity': array([1.78544597e-07, 1.73410821e+01, 5.37349237e+01, 7.35976295e+01,\n 8.34733324e+01, 8.87978444e+01, 9.19287453e+01, 9.39060819e+01,\n 9.52277477e+01, 9.61520364e+01, 9.68225162e+01, 9.73237288e+01,\n 9.77079209e+01, 9.80087218e+01, 9.82485402e+01, 9.84427587e+01,\n 9.86022130e+01, 9.87347097e+01, 9.88459861e+01, 9.89403338e+01,\n 9.90210141e+01, 9.90905402e+01, 9.91508741e+01, 9.92035655e+01,\n 9.92498509e+01, 9.92907269e+01, 9.93270039e+01, 9.93593459e+01,\n 9.93883017e+01, 9.94143276e+01, 9.94378055e+01])}\n","output_type":"stream"}],"id":"467a9752-e842-43ef-9233-96663b7086dd"},{"cell_type":"markdown","source":"The calculation of the thermal properties takes additional inputs: \n\n* `t_min` minimum temperature\n* `t_max` maximum temperature\n* `t_step` temperature step \n* `temperatures` alternative to `t_min`, `t_max` and `t_step` the array of temperatures can be defined directly\n* `cutoff_frequency` cutoff frequency to exclude the contributions of frequencies below a certain cut off\n* `pretend_real` use the absolute values of the phonon frequencies\n* `band_indices` select bands based on their indices \n* `is_projection` multiplies the squared eigenvectors - not recommended\n\nFurthermore, also the dynamical matrix can be directly calculated with the `PhonopyWorkflow`:\n","metadata":{},"id":"d8c4ac48-293a-45f9-bf77-cca3cc275e52"},{"cell_type":"code","source":"mat = workflow.get_dynamical_matrix()\nmat","metadata":{"trusted":true},"execution_count":20,"outputs":[{"execution_count":20,"output_type":"execute_result","data":{"text/plain":"array([[ 1.72794621e-01, 6.42929783e-20, -6.22838227e-20,\n -1.55150365e-18, 1.42759084e-35, -1.50515236e-19,\n 4.11475061e-18, 4.82197337e-20, 9.98736570e-02,\n 8.87128656e-18, -1.02675017e-33, -1.50493730e-19],\n [ 6.42929783e-20, 1.40379905e-01, 6.83112895e-20,\n 2.05216191e-35, 8.80589092e-18, 1.94854949e-33,\n 1.60732446e-20, 1.02868765e-18, -1.60732446e-20,\n -1.10192213e-34, 8.80589092e-18, 2.23061078e-36],\n [-6.22838227e-20, 6.83112895e-20, 1.72794621e-01,\n -1.50493730e-19, 1.25694783e-34, 8.87128656e-18,\n 9.98736570e-02, 3.21464892e-20, 0.00000000e+00,\n -1.50515236e-19, 1.47219713e-35, -1.55150365e-18],\n [-1.55150365e-18, 2.05216191e-35, -1.50493730e-19,\n 1.72794621e-01, -6.63021339e-20, 6.42929783e-20,\n 8.87128656e-18, -1.03065371e-33, -1.50493730e-19,\n 1.85163778e-17, 8.03662229e-20, 9.98736570e-02],\n [ 1.42759084e-35, 8.80589092e-18, 1.25694783e-34,\n -6.63021339e-20, 1.40379905e-01, 6.42929783e-20,\n -2.28392231e-33, 8.80589092e-18, 2.67635707e-36,\n 0.00000000e+00, 0.00000000e+00, -1.60732446e-20],\n [-1.50515236e-19, 1.94854949e-33, 8.87128656e-18,\n 6.42929783e-20, 6.42929783e-20, 1.72794621e-01,\n -1.50515236e-19, -4.46122155e-37, -1.55150365e-18,\n 9.98736570e-02, 0.00000000e+00, -1.85163778e-17],\n [ 4.11475061e-18, 1.60732446e-20, 9.98736570e-02,\n 8.87128656e-18, -2.28392231e-33, -1.50515236e-19,\n 1.72794621e-01, 6.63021339e-20, -6.42929783e-20,\n -1.55150365e-18, 6.24500783e-36, -1.50493730e-19],\n [ 4.82197337e-20, 1.02868765e-18, 3.21464892e-20,\n -1.03065371e-33, 8.80589092e-18, -4.46122155e-37,\n 6.63021339e-20, 1.40379905e-01, 6.83112895e-20,\n 1.07069317e-35, 8.80589092e-18, -6.89481791e-34],\n [ 9.98736570e-02, -1.60732446e-20, 0.00000000e+00,\n -1.50493730e-19, 2.67635707e-36, -1.55150365e-18,\n -6.42929783e-20, 6.83112895e-20, 1.72794621e-01,\n -1.50515236e-19, 1.81950725e-33, 8.87128656e-18],\n [ 8.87128656e-18, -1.10192213e-34, -1.50515236e-19,\n 1.85163778e-17, 0.00000000e+00, 9.98736570e-02,\n -1.55150365e-18, 1.07069317e-35, -1.50515236e-19,\n 1.72794621e-01, 6.42929783e-20, -6.22838227e-20],\n [-1.02675017e-33, 8.80589092e-18, 1.47219713e-35,\n 8.03662229e-20, 0.00000000e+00, 0.00000000e+00,\n 6.24500783e-36, 8.80589092e-18, 1.81950725e-33,\n 6.42929783e-20, 1.40379905e-01, 6.83112895e-20],\n [-1.50493730e-19, 2.23061078e-36, -1.55150365e-18,\n 9.98736570e-02, -1.60732446e-20, -1.85163778e-17,\n -1.50493730e-19, -6.89481791e-34, 8.87128656e-18,\n -6.22838227e-20, 6.83112895e-20, 1.72794621e-01]])"},"metadata":{}}],"id":"0856938b-b1cd-40ce-95b7-4605f10ee7a4"},{"cell_type":"markdown","source":"Or alternatively the hesse matrix:","metadata":{},"id":"93bc3fbe-fe43-42d4-aaf9-12ef9994e923"},{"cell_type":"code","source":"mat = workflow.get_hesse_matrix()\nmat","metadata":{"trusted":true},"execution_count":21,"outputs":[{"execution_count":21,"output_type":"execute_result","data":{"text/plain":"array([[ 4.50127147e-02, -1.92714960e-33, 8.52306995e-33, ...,\n -6.63514216e-05, 8.82979633e-06, 5.93920137e-05],\n [-5.07378488e-34, 4.50127147e-02, 5.07378488e-34, ...,\n 8.82979633e-06, -6.63514216e-05, 5.93920137e-05],\n [ 5.07378488e-34, -5.07378488e-34, 4.50127147e-02, ...,\n 5.93659141e-05, 5.93659141e-05, 1.73512126e-05],\n ...,\n [-6.63514216e-05, 8.82979633e-06, 5.93920137e-05, ...,\n 4.50127147e-02, -1.92714960e-33, 8.52306995e-33],\n [ 8.82979633e-06, -6.63514216e-05, 5.93920137e-05, ...,\n -5.07378488e-34, 4.50127147e-02, 5.07378488e-34],\n [ 5.93659141e-05, 5.93659141e-05, 1.73512126e-05, ...,\n 5.07378488e-34, -5.07378488e-34, 4.50127147e-02]])"},"metadata":{}}],"id":"c3154b6d-50c1-4327-b7cc-00f48b31fd37"},{"cell_type":"markdown","source":"Finally, also the function to calculate the band structure is directly available on the `PhonopyWorkflow`: ","metadata":{},"id":"ebc0a064-af95-42e4-854e-67bdb1065ac6"},{"cell_type":"code","source":"band_structure = workflow.get_band_structure(\n npoints=101, \n with_eigenvectors=False, \n with_group_velocities=False\n)","metadata":{"trusted":true},"execution_count":22,"outputs":[],"id":"a9655fa5-bf39-47f2-ae30-0450b40bf252"},{"cell_type":"markdown","source":"This band structure can also be visualised using the built-in plotting function: ","metadata":{},"id":"e8d2dcce-a5c6-4301-8c0e-bf0ca11043e9"},{"cell_type":"code","source":"workflow.plot_band_structure()","metadata":{"trusted":true},"execution_count":23,"outputs":[{"execution_count":23,"output_type":"execute_result","data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}],"id":"4ad1f1e4-9496-4e99-afa0-fd67c72c26f4"},{"cell_type":"markdown","source":"Just like the desnsity of states which can be plotted using:","metadata":{},"id":"ae251474-875a-4af2-9290-74e9785490cd"},{"cell_type":"code","source":"workflow.plot_dos()","metadata":{"trusted":true},"execution_count":24,"outputs":[{"execution_count":24,"output_type":"execute_result","data":{"text/plain":""},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}],"id":"82da60b3-3930-4ff1-879e-65895112aecb"},{"cell_type":"markdown","source":"### Quasi-harmonic Approximation \nTo include the volume expansion with finite temperature the `atomistics` package implements the `QuasiHarmonicWorkflow`:","metadata":{},"id":"93e6fb35-cc50-4235-9885-406c41c6a486"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import evaluate_with_lammps, get_potential_by_name\nfrom atomistics.workflows import QuasiHarmonicWorkflow\n\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\nworkflow = QuasiHarmonicWorkflow(\n structure=bulk(\"Al\", cubic=True), \n num_points=11,\n vol_range=0.05,\n interaction_range=10,\n factor=VaspToTHz,\n displacement=0.01,\n dos_mesh=20,\n primitive_matrix=None,\n number_of_snapshots=None,\n)\ntask_dict = workflow.generate_structures()\nresult_dict = evaluate_with_lammps(\n task_dict=task_dict,\n potential_dataframe=potential_dataframe,\n)\nfit_dict = workflow.analyse_structures(output_dict=result_dict)","metadata":{"trusted":true},"execution_count":25,"outputs":[],"id":"9387e3aa-b349-49a9-b7b9-0ac1d7f209d5"},{"cell_type":"markdown","source":"The `QuasiHarmonicWorkflow` is a combination of the `EnergyVolumeCurveWorkflow` and the `PhonopyWorkflow`. Consequently, \nthe inputs are a superset of the inputs of these two workflows. ","metadata":{},"id":"b5167f8d-c90f-4bf0-a7c0-fd4dfdd35667"},{"cell_type":"markdown","source":"Based on the `QuasiHarmonicWorkflow` the thermal properties can be calculated:","metadata":{},"id":"169ddaf9-7f5d-4126-babf-9f2de3793128"},{"cell_type":"code","source":"tp_dict = workflow.get_thermal_properties(\n t_min=1, \n t_max=1500, \n t_step=50, \n temperatures=None,\n cutoff_frequency=None,\n pretend_real=False,\n band_indices=None,\n is_projection=False,\n quantum_mechanical=True,\n)\nprint(tp_dict)","metadata":{"trusted":true},"execution_count":26,"outputs":[{"name":"stdout","text":"{'temperatures': array([1.000e+00, 5.100e+01, 1.010e+02, 1.510e+02, 2.010e+02, 2.510e+02,\n 3.010e+02, 3.510e+02, 4.010e+02, 4.510e+02, 5.010e+02, 5.510e+02,\n 6.010e+02, 6.510e+02, 7.010e+02, 7.510e+02, 8.010e+02, 8.510e+02,\n 9.010e+02, 9.510e+02, 1.001e+03, 1.051e+03, 1.101e+03, 1.151e+03,\n 1.201e+03, 1.251e+03, 1.301e+03, 1.351e+03, 1.401e+03, 1.451e+03,\n 1.501e+03]), 'volumes': [66.71710763927429, 66.7217721669909, 66.7588030456557, 66.82252047263532, 66.89849494958942, 66.9796340113892, 67.06260790999332, 67.14571406293086, 67.22800412575396, 67.30891433769602, 67.38809533263267, 67.46532691223801, 67.54047194450261, 67.61344961442688, 67.68421888050003, 67.7527676376025, 67.81910525012583, 67.88325718224746, 67.94526099996934, 68.00516331349996, 68.06301739227649, 68.11888127927111, 68.1728162874363, 68.22488579579438, 68.27515428480372, 68.32368656530063, 68.3705471654382, 68.41579984727981, 68.45950723009813, 68.50173050155158, 68.54252920118272], 'free_energy': array([ 0.14903662, 0.14826796, 0.13934608, 0.1169922 , 0.08193524,\n 0.03597463, -0.01929655, -0.08261538, -0.15299036, -0.22963345,\n -0.31190757, -0.39928889, -0.49134004, -0.5876908 , -0.68802399,\n -0.79206502, -0.89957393, -1.01033927, -1.12417341, -1.24090869,\n -1.36039449, -1.48249475, -1.60708597, -1.73405557, -1.86330055,\n -1.99472628, -2.12824554, -2.26377775, -2.40124816, -2.54058732,\n -2.6817305 ]), 'entropy': array([1.02970750e-08, 5.98072651e+00, 2.96865053e+01, 5.55852668e+01,\n 7.82409727e+01, 9.75218995e+01, 1.14065625e+02, 1.28465273e+02,\n 1.41174728e+02, 1.52530436e+02, 1.62783056e+02, 1.72122199e+02,\n 1.80693841e+02, 1.88612312e+02, 1.95968600e+02, 2.02836175e+02,\n 2.09275150e+02, 2.15335286e+02, 2.21058222e+02, 2.26479132e+02,\n 2.31627991e+02, 2.36530543e+02, 2.41209060e+02, 2.45682935e+02,\n 2.49969156e+02, 2.54082691e+02, 2.58036788e+02, 2.61843234e+02,\n 2.65512561e+02, 2.69054215e+02, 2.72476702e+02]), 'heat_capacity': array([1.67065980e-07, 1.73540235e+01, 5.38037700e+01, 7.36871465e+01,\n 8.35644372e+01, 8.88841670e+01, 9.20085315e+01, 9.39792227e+01,\n 9.52946945e+01, 9.62133951e+01, 9.68788951e+01, 9.73756862e+01,\n 9.77559504e+01, 9.80532534e+01, 9.82899463e+01, 9.84813619e+01,\n 9.86382931e+01, 9.87685101e+01, 9.88777197e+01, 9.89701872e+01,\n 9.90491516e+01, 9.91171073e+01, 9.91760000e+01, 9.92273651e+01,\n 9.92724273e+01, 9.93121724e+01, 9.93474017e+01, 9.93787712e+01,\n 9.94068224e+01, 9.94320054e+01, 9.94546967e+01])}\n","output_type":"stream"}],"id":"07cc0818-15a8-4508-ba97-c3a95eaa72b1"},{"cell_type":"markdown","source":"This requires the same inputs as the calculation of the thermal properties `get_thermal_properties()` with the \n`PhonopyWorkflow`. The additional parameter `quantum_mechanical` specifies whether the classical harmonic oscillator or \nthe quantum mechanical harmonic oscillator is used to calculate the free energy. ","metadata":{},"id":"1fb5c6e3-83a4-4503-a0f1-4958ebc6361c"},{"cell_type":"markdown","source":"And finally also the thermal expansion can be calculated:","metadata":{},"id":"3e6cc3bd-5f7c-4462-8083-5111dc5d4577"},{"cell_type":"code","source":"tp_dict = workflow.get_thermal_properties(\n t_min=1, \n t_max=1500, \n t_step=50, \n temperatures=None,\n cutoff_frequency=None,\n pretend_real=False,\n band_indices=None,\n is_projection=False,\n quantum_mechanical=True,\n output_keys=[\"free_energy\", \"temperatures\", \"volumes\"],\n)\ntemperatures, volumes = tp_dict[\"temperatures\"], tp_dict[\"volumes\"]","metadata":{"trusted":true},"execution_count":27,"outputs":[],"id":"76426cc0-38c8-480e-9fd1-fbcb41c8afec"},{"cell_type":"markdown","source":"## Structure Optimization \nIn analogy to the molecular dynamics calculation also the structure optimization could in principle be defined inside \nthe simulation code or on the python level. Still currently the `atomistics` package only supports the structure \noptimization defined inside the simulation codes. ","metadata":{},"id":"3cf34091-d7f5-464a-b386-9b81c1fa853a"},{"cell_type":"markdown","source":"### Volume and Positions \nTo optimize both the volume of the supercell as well as the positions inside the supercell the `atomistics` package\nimplements the `optimize_positions_and_volume()` workflow:","metadata":{},"id":"e58b5d2e-8839-48c6-b72e-0fa09ace20ce"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import evaluate_with_lammps, get_potential_by_name\nfrom atomistics.workflows import optimize_positions_and_volume\n\nstructure = bulk(\"Al\", a=4.0, cubic=True)\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\nresult_dict = evaluate_with_lammps(\n task_dict=optimize_positions_and_volume(structure=structure),\n potential_dataframe=potential_dataframe,\n)\nstructure_opt = result_dict[\"structure_with_optimized_positions_and_volume\"]\nstructure_opt","metadata":{"trusted":true},"execution_count":28,"outputs":[{"execution_count":28,"output_type":"execute_result","data":{"text/plain":"Atoms(symbols='Al4', pbc=True, cell=[[4.05000466219724, 2.4799126230458533e-16, 2.4799126230458533e-16], [0.0, 4.05000466219724, 2.4799126230458533e-16], [0.0, 0.0, 4.05000466219724]])"},"metadata":{}}],"id":"a7f38a78-11b9-41c2-82c9-7c30b3a9b005"},{"cell_type":"markdown","source":"The result is the optimized atomistic structure as part of the result dictionary. ","metadata":{},"id":"c375f310-78c2-426a-8f77-669e9bec855f"},{"cell_type":"markdown","source":"### Positions \nThe optimization of the positions inside the supercell without the optimization of the supercell volume is possible with\nthe `optimize_positions()` workflow:","metadata":{},"id":"6d4ef070-f0f1-4f56-afff-ff6322d3729a"},{"cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import evaluate_with_lammps, get_potential_by_name\nfrom atomistics.workflows import optimize_positions\n\nstructure = bulk(\"Al\", a=4.0, cubic=True)\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\nresult_dict = evaluate_with_lammps(\n task_dict=optimize_positions(structure=structure),\n potential_dataframe=potential_dataframe,\n)\nstructure_opt = result_dict[\"structure_with_optimized_positions\"]\nstructure_opt","metadata":{"trusted":true},"execution_count":29,"outputs":[{"execution_count":29,"output_type":"execute_result","data":{"text/plain":"Atoms(symbols='Al4', pbc=True, cell=[4.0, 4.0, 4.0])"},"metadata":{}}],"id":"9a50125b-a97a-4445-b140-b8019c035902"},{"cell_type":"markdown","source":"The result is the optimized atomistic structure as part of the result dictionary. ","metadata":{},"id":"d027161c-abd3-4267-a10f-cb404c3ebbfd"},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[],"id":"a84ef4fc-a9a7-4386-921f-7b77af81a166"}]} +{ + "cells": [ + { + "cell_type": "markdown", + "id": "29680e01-8658-4085-aada-eaaa9d8705be", + "metadata": {}, + "source": "# Workflows\nTo demonstrate the workflows implemented in the `atomistics` package, the [LAMMPS](https://www.lammps.org/) molecular \ndynamics simulation code is used in the following demonstrations. Still the same `workflows` can also be used with other\nsimulation codes:" + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "76ec535d-d9cb-4d68-9208-c9b0c029c402", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pyiron-2datomistics-2dloteusr2:00647] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + } + ], + "source": [ + "from atomistics.calculators import evaluate_with_lammps, get_potential_by_name\n", + "\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "result_dict = evaluate_with_lammps(\n", + " task_dict={},\n", + " potential_dataframe=potential_dataframe,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "d813a092-a7d8-49e6-8914-02c1b9e105f6", + "metadata": {}, + "source": "The interatomic potential for Aluminium from Mishin named `1999--Mishin-Y--Al--LAMMPS--ipr1` is used in the evaluation\nwith [LAMMPS](https://www.lammps.org/) `evaluate_with_lammps()`. " + }, + { + "cell_type": "markdown", + "id": "70bac169-3b94-486f-afa9-efe5005f1cf0", + "metadata": {}, + "source": "## Elastic Matrix \nThe elastic constants and elastic moduli can be calculated using the `ElasticMatrixWorkflow`: " + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "f26f2645-e1c7-4b7e-8414-e4632b1439f9", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "{'elastic_matrix': array([[114.10393023, 60.51098897, 60.51098897, 0. ,\n 0. , 0. ],\n [ 60.51098897, 114.10393023, 60.51098897, 0. ,\n 0. , 0. ],\n [ 60.51098897, 60.51098897, 114.10393023, 0. ,\n 0. , 0. ],\n [ 0. , 0. , 0. , 51.23931149,\n 0. , 0. ],\n [ 0. , 0. , 0. , 0. ,\n 51.23931149, 0. ],\n [ 0. , 0. , 0. , 0. ,\n 0. , 51.23931149]]), 'elastic_matrix_inverse': array([[ 0.01385713, -0.00480204, -0.00480204, 0. , 0. ,\n 0. ],\n [-0.00480204, 0.01385713, -0.00480204, 0. , 0. ,\n 0. ],\n [-0.00480204, -0.00480204, 0.01385713, 0. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0.01951627, 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0.01951627,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0. ,\n 0.01951627]]), 'bulkmodul_voigt': 78.37530272473929, 'bulkmodul_reuss': 78.37530272473931, 'bulkmodul_hill': 78.3753027247393, 'shearmodul_voigt': 41.462175146677424, 'shearmodul_reuss': 37.54162684596518, 'shearmodul_hill': 39.501900996321304, 'youngsmodul_voigt': 105.74025607889799, 'youngsmodul_reuss': 97.1183728107761, 'youngsmodul_hill': 101.46008564559224, 'poissonsratio_voigt': 0.2751412064710683, 'poissonsratio_reuss': 0.29347581564934205, 'poissonsratio_hill': 0.2842430754793411, 'AVR': 4.962480541224269, 'elastic_matrix_eigval': EigResult(eigenvalues=array([ 53.59294126, 235.12590817, 53.59294126, 51.23931149,\n 51.23931149, 51.23931149]), eigenvectors=array([[-0.81649658, 0.57735027, 0.11541902, 0. , 0. ,\n 0. ],\n [ 0.40824829, 0.57735027, -0.75771582, 0. , 0. ,\n 0. ],\n [ 0.40824829, 0.57735027, 0.6422968 , 0. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 1. , 0. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 1. ,\n 0. ],\n [ 0. , 0. , 0. , 0. , 0. ,\n 1. ]]))}\n" + } + ], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import evaluate_with_lammps, get_potential_by_name\n", + "from atomistics.workflows import ElasticMatrixWorkflow\n", + "\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "workflow = ElasticMatrixWorkflow(\n", + " structure=bulk(\"Al\", cubic=True),\n", + " num_of_point=5,\n", + " eps_range=0.005,\n", + " sqrt_eta=True,\n", + " fit_order=2,\n", + ")\n", + "task_dict = workflow.generate_structures()\n", + "result_dict = evaluate_with_lammps(\n", + " task_dict=task_dict,\n", + " potential_dataframe=potential_dataframe,\n", + ")\n", + "fit_dict = workflow.analyse_structures(output_dict=result_dict)\n", + "print(fit_dict)" + ] + }, + { + "cell_type": "markdown", + "id": "262aefd1-9cf9-4b35-8d94-03996b21166b", + "metadata": {}, + "source": "The `ElasticMatrixWorkflow` takes an `ase.atoms.Atoms` object as `structure` input as well as the number of points \n`num_of_point` for each compression direction. Depending on the symmetry of the input `structure` the number of \ncalculations required to calculate the elastic matrix changes. The compression and elongation range is defined by the\n`eps_range` parameter. Furthermore, `sqrt_eta` and `fit_order` describe how the change in energy over compression and\nelongation is fitted to calculate the resulting pressure. " + }, + { + "cell_type": "markdown", + "id": "dc5356a8-0b07-4a0a-a549-9a20cf3c64cc", + "metadata": {}, + "source": "## Energy Volume Curve\nThe `EnergyVolumeCurveWorkflow` can be used to calculate the equilibrium properties: equilibrium volume, equilibrium \nenergy, equilibrium bulk modulus and the pressure derivative of the equilibrium bulk modulus. " + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "720a7662-fdee-496d-b355-ff4881f5c633", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "{'b_prime_eq': 1.279502459079921, 'bulkmodul_eq': 77.7250135953191, 'volume_eq': 66.43019853103964, 'energy_eq': -13.43996804374383, 'fit_dict': {'fit_type': 'polynomial', 'least_square_error': 3.225313797039607e-10, 'poly_fit': array([-4.17645808e-05, 1.19746500e-02, -1.03803906e+00, 1.49168639e+01]), 'fit_order': 3}, 'energy': [-13.398169481534445, -13.413389552957456, -13.425112589013958, -13.433411420804067, -13.438357630783006, -13.439999952539933, -13.438383476946305, -13.433607982916406, -13.425774537190858, -13.414961805921427, -13.401233093668836], 'volume': [63.10861874999998, 63.77291999999998, 64.43722124999998, 65.1015225, 65.76582375000004, 66.43012500000002, 67.09442624999994, 67.75872750000002, 68.42302874999999, 69.08732999999997, 69.75163125000002]}\n" + } + ], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import evaluate_with_lammps, get_potential_by_name\n", + "from atomistics.workflows import EnergyVolumeCurveWorkflow\n", + "\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "workflow = EnergyVolumeCurveWorkflow(\n", + " structure=bulk(\"Al\", cubic=True),\n", + " num_points=11,\n", + " fit_type=\"polynomial\",\n", + " fit_order=3,\n", + " vol_range=0.05,\n", + " axes=(\"x\", \"y\", \"z\"),\n", + " strains=None,\n", + ")\n", + "task_dict = workflow.generate_structures()\n", + "result_dict = evaluate_with_lammps(\n", + " task_dict=task_dict,\n", + " potential_dataframe=potential_dataframe,\n", + ")\n", + "fit_dict = workflow.analyse_structures(output_dict=result_dict)\n", + "print(fit_dict)" + ] + }, + { + "cell_type": "markdown", + "id": "13c95c80-137d-49bf-8016-b3c15279fbcf", + "metadata": {}, + "source": "The input parameters for the `EnergyVolumeCurveWorkflow` in addition to the `ase.atoms.Atoms` object defined \nas `structure` are: \n\n* `num_points` the number of strains to calculate energies and volumes. \n* `fit_type` the type of the fit which should be used to calculate the equilibrium properties. This can either be a \n `polynomial` fit or a specific equation of state like the Birch equation (`birch`), the Birch-Murnaghan equation \n (`birchmurnaghan`) the Murnaghan equation (`murnaghan`), the Pourier Tarnatola eqaution (`pouriertarantola`) or the\n Vinet equation (`vinet`). \n* `fit_order` for the `polynomial` fit type the order of the polynomial can be set, for the other fit types this \n parameter is ignored. \n* `vol_range` specifies the amount of compression and elongation to be applied relative to the absolute volume. \n* `axes` specifies the axes which are compressed, typically a uniform compression is applied. \n* `strains` specifies the strains directly rather than deriving them from the range of volume compression `vol_range`. \n\nBeyond calculating the equilibrium properties the `EnergyVolumeCurveWorkflow` can also be used to calculate the thermal\nproperties using the [Moruzzi, V. L. et al.](https://link.aps.org/doi/10.1103/PhysRevB.37.790) model: " + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "8a9a8e77-a6f0-4466-8c3d-fc1ca6ebbaf0", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "{'temperatures': array([ 1, 51, 101, 151, 201, 251, 301, 351, 401, 451, 501,\n 551, 601, 651, 701, 751, 801, 851, 901, 951, 1001, 1051,\n 1101, 1151, 1201, 1251, 1301, 1351, 1401, 1451, 1501]), 'volumes': array([66.48459155, 66.48492729, 66.48841343, 66.49613572, 66.50654263,\n 66.51846055, 66.53126421, 66.5446199 , 66.55833931, 66.57230985,\n 66.58646057, 66.6007448 , 66.61513063, 66.6295956 , 66.64412341,\n 66.65870199, 66.6733222 , 66.68797701, 66.70266093, 66.71736958,\n 66.73209946, 66.74684773, 66.76161205, 66.77639048, 66.79118142,\n 66.8059835 , 66.82079558, 66.83561668, 66.85044595, 66.86528267,\n 66.88012622]), 'free_energy': array([ 0.18879418, 0.18840183, 0.18352524, 0.16909367, 0.1440755 ,\n 0.10931095, 0.06593656, 0.01498215, -0.04269081, -0.1063728 ,\n -0.1754776 , -0.24951635, -0.328077 , -0.41080851, -0.49740877,\n -0.58761537, -0.68119851, -0.77795536, -0.87770572, -0.98028844,\n -1.08555864, -1.19338539, -1.3036498 , -1.41624343, -1.53106703,\n -1.6480294 , -1.76704645, -1.88804043, -2.01093923, -2.13567578,\n -2.26218757]), 'entropy': array([ 0.75685476, 5.08219062, 18.62461552, 38.05446426,\n 57.6693229 , 75.37710506, 90.99476554, 104.78762778,\n 117.06473011, 128.09164494, 138.08127289, 147.20167195,\n 155.58579193, 163.33970927, 170.54896552, 177.28330938,\n 183.60022562, 189.54757244, 195.16556897, 200.48830826,\n 205.54492122, 210.36048158, 214.95671661, 219.35257076,\n 223.56465688, 227.60762034, 231.49443548, 235.23664867,\n 238.84457908, 242.32748555, 244.0403182 ]), 'heat_capacity': array([8.65067172e-02, 9.11255799e+00, 3.33019964e+01, 5.89575081e+01,\n 7.50185080e+01, 8.36468610e+01, 8.85256734e+01, 9.15055757e+01,\n 9.34491088e+01, 9.47846079e+01, 9.57412353e+01, 9.64498999e+01,\n 9.69896043e+01, 9.74102601e+01, 9.77446368e+01, 9.80149634e+01,\n 9.82367471e+01, 9.84210719e+01, 9.85760297e+01, 9.87076399e+01,\n 9.88204550e+01, 9.89179695e+01, 9.90029019e+01, 9.90773926e+01,\n 9.91431454e+01, 9.92015302e+01, 9.92536586e+01, 9.93004401e+01,\n 9.93426247e+01, nan, nan])}\n" + } + ], + "source": [ + "tp_dict = workflow.get_thermal_properties(\n", + " t_min=1,\n", + " t_max=1500,\n", + " t_step=50,\n", + " temperatures=None,\n", + " constant_volume=False,\n", + ")\n", + "print(tp_dict)" + ] + }, + { + "cell_type": "markdown", + "id": "ebebb63f-3897-4028-ad23-708aaaf9cc26", + "metadata": {}, + "source": "Or alternatively directly calculate the thermal expansion:" + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "6e963779-cd59-4985-9a72-9652dd1f1408", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "thermal_properties_dict = workflow.get_thermal_properties(\n", + " t_min=1,\n", + " t_max=1500,\n", + " t_step=50,\n", + " constant_volume=False,\n", + " output_keys=[\"temperatures\", \"volumes\"],\n", + ")\n", + "temperatures, volumes = (\n", + " thermal_properties_dict[\"temperatures\"],\n", + " thermal_properties_dict[\"volumes\"],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "e3f4357d-8b81-41bd-a90b-556f231b9766", + "metadata": {}, + "source": "The [Moruzzi, V. L. et al.](https://link.aps.org/doi/10.1103/PhysRevB.37.790) model is a quantum mechanical approximation, so the equilibrium volume at 0K is not\nthe same as the equilibrium volume calculated by fitting the equation of state. " + }, + { + "cell_type": "markdown", + "id": "ac4095fb-0e11-46bc-8c8d-54bc97ddfe18", + "metadata": {}, + "source": "## Molecular Dynamics \nJust like the structure optimization also the molecular dynamics calculation can either be implemented inside the\nsimulation code or in the `atomistics` package. The latter has the advantage that it is the same implementation for all\ndifferent simulation codes, while the prior has the advantage that it is usually faster and computationally more efficient." + }, + { + "cell_type": "markdown", + "id": "1cfe604e-1e02-4a64-a49b-eccd1b32c9fc", + "metadata": {}, + "source": "### Implemented in Simulation Code \nThe [LAMMPS](https://lammps.org/) simulation code implements a wide range of different simulation workflows, this \nincludes molecular dynamics. In the `atomistics` package these can be directly accessed via the python interface. " + }, + { + "cell_type": "markdown", + "id": "0e52ed95-1510-4944-a5a6-8ea9d49c906f", + "metadata": {}, + "source": "#### Langevin Thermostat\nThe Langevin thermostat is currently the only thermostat which is available as both a stand-alone python interface and\nan integrated interface inside the [LAMMPS](https://lammps.org/) simulation code. The latter is introduced here:" + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2e0c22ea-562b-4669-a34b-1d60a8bd1e2c", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import (\n", + " calc_molecular_dynamics_langevin_with_lammps,\n", + " get_potential_by_name,\n", + ")\n", + "\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "result_dict = calc_molecular_dynamics_langevin_with_lammps(\n", + " structure=bulk(\"Al\", cubic=True).repeat([10, 10, 10]),\n", + " potential_dataframe=potential_dataframe,\n", + " Tstart=100,\n", + " Tstop=100,\n", + " Tdamp=0.1,\n", + " run=100,\n", + " thermo=10,\n", + " timestep=0.001,\n", + " seed=4928459,\n", + " dist=\"gaussian\",\n", + " output_keys=(\n", + " \"positions\",\n", + " \"cell\",\n", + " \"forces\",\n", + " \"temperature\",\n", + " \"energy_pot\",\n", + " \"energy_tot\",\n", + " \"pressure\",\n", + " \"velocities\",\n", + " ),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "e21267cb-9fb6-4c1f-8912-c281dc899323", + "metadata": {}, + "source": "In addition to the typical LAMMPS input parameters like the atomistic structure `structure` as `ase.atoms.Atoms` object\nand the `pandas.DataFrame` for the interatomic potential `potential_dataframe` are: \n\n* `Tstart` start temperature \n* `Tstop` end temperature\n* `Tdamp` temperature damping parameter \n* `run` number of molecular dynamics steps to be executed during one temperature step\n* `thermo` refresh rate for the thermo dynamic properties, this should typically be the same as the number of molecular\n dynamics steps. \n* `timestep` time step - typically 1fs defined as `0.001`.\n* `seed` random seed for the molecular dynamics \n* `dist` initial velocity distribution \n* `lmp` Lammps library instance as `pylammpsmpi.LammpsASELibrary` object \n* `output` the output quantities which are extracted from the molecular dynamics simulation" + }, + { + "cell_type": "markdown", + "id": "be5d582d-9952-4a5b-b704-1a9acdb8b306", + "metadata": {}, + "source": "#### Nose Hoover Thermostat\nCanonical ensemble (nvt) - volume and temperature constraints molecular dynamics:" + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "9717893e-4dea-46f7-9317-bb314bc5bbdd", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import (\n", + " calc_molecular_dynamics_nvt_with_lammps,\n", + " get_potential_by_name,\n", + ")\n", + "\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "result_dict = calc_molecular_dynamics_nvt_with_lammps(\n", + " structure=bulk(\"Al\", cubic=True).repeat([10, 10, 10]),\n", + " potential_dataframe=potential_dataframe,\n", + " Tstart=100,\n", + " Tstop=100,\n", + " Tdamp=0.1,\n", + " run=100,\n", + " thermo=10,\n", + " timestep=0.001,\n", + " seed=4928459,\n", + " dist=\"gaussian\",\n", + " output_keys=(\n", + " \"positions\",\n", + " \"cell\",\n", + " \"forces\",\n", + " \"temperature\",\n", + " \"energy_pot\",\n", + " \"energy_tot\",\n", + " \"pressure\",\n", + " ),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "72797e59-72f5-4d32-b7cf-5ad806b91909", + "metadata": {}, + "source": "In addition to the typical LAMMPS input parameters like the atomistic structure `structure` as `ase.atoms.Atoms` object\nand the `pandas.DataFrame` for the interatomic potential `potential_dataframe` are: \n\n* `Tstart` start temperature \n* `Tstop` end temperature\n* `Tdamp` temperature damping parameter \n* `run` number of molecular dynamics steps to be executed during one temperature step\n* `thermo` refresh rate for the thermo dynamic properties, this should typically be the same as the number of molecular\n dynamics steps. \n* `timestep` time step - typically 1fs defined as `0.001`.\n* `seed` random seed for the molecular dynamics \n* `dist` initial velocity distribution \n* `lmp` Lammps library instance as `pylammpsmpi.LammpsASELibrary` object \n* `output` the output quantities which are extracted from the molecular dynamics simulation" + }, + { + "cell_type": "markdown", + "id": "8356bf7f-bf7d-40e0-8f3c-02309cd74d92", + "metadata": {}, + "source": "Isothermal-isobaric ensemble (npt) - pressure and temperature constraints molecular dynamics:" + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "1327d554-0df1-45fa-b35c-ec4955ce756f", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import (\n", + " calc_molecular_dynamics_npt_with_lammps,\n", + " get_potential_by_name,\n", + ")\n", + "\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "result_dict = calc_molecular_dynamics_npt_with_lammps(\n", + " structure=bulk(\"Al\", cubic=True).repeat([10, 10, 10]),\n", + " potential_dataframe=potential_dataframe,\n", + " Tstart=100,\n", + " Tstop=100,\n", + " Tdamp=0.1,\n", + " run=100,\n", + " thermo=100,\n", + " timestep=0.001,\n", + " Pstart=0.0,\n", + " Pstop=0.0,\n", + " Pdamp=1.0,\n", + " seed=4928459,\n", + " dist=\"gaussian\",\n", + " output_keys=(\n", + " \"positions\",\n", + " \"cell\",\n", + " \"forces\",\n", + " \"temperature\",\n", + " \"energy_pot\",\n", + " \"energy_tot\",\n", + " \"pressure\",\n", + " ),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "e6aeb0fe-ace6-4e55-a3c2-06be85aaf05e", + "metadata": {}, + "source": "The input parameters for the isothermal-isobaric ensemble (npt) are the same as for the canonical ensemble (nvt) plus:\n\n* `Pstart` start pressure \n* `Pstop` end pressure \n* `Pdamp` pressure damping parameter " + }, + { + "cell_type": "markdown", + "id": "04f5854b-d803-4023-af04-55efc22ee1e3", + "metadata": {}, + "source": "Isenthalpic ensemble (nph) - pressure and helmholtz-energy constraints molecular dynamics:" + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "5f64f60c-89ce-423b-a487-ea96780b1c20", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import (\n", + " calc_molecular_dynamics_nph_with_lammps,\n", + " get_potential_by_name,\n", + ")\n", + "\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "result_dict = calc_molecular_dynamics_nph_with_lammps(\n", + " structure=bulk(\"Al\", cubic=True).repeat([10, 10, 10]),\n", + " potential_dataframe=potential_dataframe,\n", + " run=100,\n", + " thermo=100,\n", + " timestep=0.001,\n", + " Tstart=100,\n", + " Pstart=0.0,\n", + " Pstop=0.0,\n", + " Pdamp=1.0,\n", + " seed=4928459,\n", + " dist=\"gaussian\",\n", + " output_keys=(\n", + " \"positions\",\n", + " \"cell\",\n", + " \"forces\",\n", + " \"temperature\",\n", + " \"energy_pot\",\n", + " \"energy_tot\",\n", + " \"pressure\",\n", + " ),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "3b4c6022-e1d5-467b-ac1b-d3617670fe67", + "metadata": {}, + "source": "#### Thermal Expansion\nOne example of a molecular dynamics calculation with the LAMMPS simulation code is the calculation of the thermal \nexpansion: " + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "d3e4bda7-9aa4-4a82-8c51-9606b0e77f75", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "100%|██████████| 10/10 [00:05<00:00, 1.69it/s]\n" + } + ], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import (\n", + " calc_molecular_dynamics_thermal_expansion_with_lammps,\n", + " evaluate_with_lammps,\n", + " get_potential_by_name,\n", + ")\n", + "\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "temperatures_md, volumes_md = calc_molecular_dynamics_thermal_expansion_with_lammps(\n", + " structure=bulk(\"Al\", cubic=True).repeat([10, 10, 10]),\n", + " potential_dataframe=potential_dataframe,\n", + " Tstart=100,\n", + " Tstop=1000,\n", + " Tstep=100,\n", + " Tdamp=0.1,\n", + " run=100,\n", + " thermo=100,\n", + " timestep=0.001,\n", + " Pstart=0.0,\n", + " Pstop=0.0,\n", + " Pdamp=1.0,\n", + " seed=4928459,\n", + " dist=\"gaussian\",\n", + " lmp=None,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "08c20c91-9e7c-4770-b01f-1765064797dd", + "metadata": {}, + "source": "In addition to the typical LAMMPS input parameters like the atomistic structure `structure` as `ase.atoms.Atoms` object\nand the `pandas.DataFrame` for the interatomic potential `potential_dataframe` are: \n\n* `Tstart` start temperature \n* `Tstop` end temperature \n* `Tstep` temperature step \n* `Tdamp` temperature damping parameter \n* `run` number of molecular dynamics steps to be executed during one temperature step\n* `thermo` refresh rate for the thermo dynamic properties, this should typically be the same as the number of molecular\n dynamics steps. \n* `timestep` time step - typically 1fs defined as `0.001`.\n* `Pstart` start pressure \n* `Pstop` end pressure \n* `Pdamp` pressure damping parameter \n* `seed` random seed for the molecular dynamics \n* `dist` initial velocity distribution \n* `lmp` Lammps library instance as `pylammpsmpi.LammpsASELibrary` object \n\nThese input parameters are based on the LAMMPS fix `nvt/npt`, you can read more about the specific implementation on the\n[LAMMPS website](https://docs.lammps.org/fix_nh.html). \n" + }, + { + "cell_type": "markdown", + "id": "e57a6740-8546-4763-a9b3-140f0cae1543", + "metadata": {}, + "source": "#### Phonons from Molecular Dynamics\nThe softening of the phonon modes is calculated for Silicon using the [Tersoff interatomic potential](https://journals.aps.org/prb/abstract/10.1103/PhysRevB.38.9902) \nwhich is available via the [NIST potentials repository](https://www.ctcms.nist.gov/potentials/entry/1988--Tersoff-J--Si-c/). \nSilicon is chosen based on its diamond crystal lattice which requires less calculation than the face centered cubic (fcc)\ncrystal of Aluminium. The simulation workflow consists of three distinct steps:\n\n* Starting with the optimization of the equilibrium structure. \n* Followed by the calculation of the 0K phonon spectrum. \n* Finally, the finite temperature phonon spectrum is calculated using molecular dynamics. \n\nThe finite temperature phonon spectrum is calculated using the [DynaPhoPy](https://abelcarreras.github.io/DynaPhoPy/)\npackage, which is integrated inside the `atomistics` package. As a prerequisite the dependencies, imported and the bulk \nsilicon diamond structure is created and the Tersoff interatomic potential is loaded: " + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "793b72ff-6b0b-46d8-a121-2c93ea6e7a32", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import (\n", + " calc_molecular_dynamics_phonons_with_lammps,\n", + " evaluate_with_lammps,\n", + ")\n", + "from atomistics.workflows import optimize_positions_and_volume, PhonopyWorkflow\n", + "from dynaphopy import Quasiparticle\n", + "import pandas\n", + "from phonopy.units import VaspToTHz\n", + "import spglib\n", + "\n", + "structure_bulk = bulk(\"Si\", cubic=True)\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1988--Tersoff-J--Si-c--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "743dce70-a4f0-4063-b353-51d26def4005", + "metadata": {}, + "source": "The first step is optimizing the Silicon diamond structure to match the lattice specifications implemented in the Tersoff \ninteratomic potential:" + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "e96fb9d9-da43-49cb-8383-5eb93eea9dc1", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "task_dict = optimize_positions_and_volume(structure=structure_bulk)\n", + "result_dict = evaluate_with_lammps(\n", + " task_dict=task_dict,\n", + " potential_dataframe=potential_dataframe,\n", + ")\n", + "structure_ase = result_dict[\"structure_with_optimized_positions_and_volume\"]" + ] + }, + { + "cell_type": "markdown", + "id": "c54c83b5-e710-405f-846b-e270267f8646", + "metadata": {}, + "source": "As a second step the 0K phonons are calculated using the `PhonopyWorkflow` which is explained in more detail below in \nthe section on [Phonons](https://atomistics.readthedocs.io/en/latest/workflows.html#phonons). " + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "b7532997-2cc3-4404-b108-3c599e4f92e8", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "{'mesh_dict': {'qpoints': array([[0.025, 0.025, 0.025],\n [0.075, 0.025, 0.025],\n [0.125, 0.025, 0.025],\n ...,\n [0.525, 0.525, 0.425],\n [0.475, 0.475, 0.475],\n [0.525, 0.475, 0.475]]),\n 'weights': array([ 2, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,\n 6, 6, 6, 6, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12,\n 12, 12, 12, 12, 12, 6, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12,\n 12, 12, 12, 12, 12, 12, 6, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12,\n 12, 12, 12, 12, 12, 12, 6, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12,\n 12, 12, 12, 12, 12, 6, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12,\n 12, 12, 12, 6, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12,\n 6, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 6, 12, 12, 12,\n 12, 12, 12, 12, 12, 12, 12, 12, 6, 12, 12, 12, 12, 12, 12, 12, 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0.53030303],\n [0.5 , 0.46590909, 0.53409091],\n [0.5 , 0.46212121, 0.53787879],\n [0.5 , 0.45833333, 0.54166667],\n [0.5 , 0.45454545, 0.54545455],\n [0.5 , 0.45075758, 0.54924242],\n [0.5 , 0.4469697 , 0.5530303 ],\n [0.5 , 0.44318182, 0.55681818],\n [0.5 , 0.43939394, 0.56060606],\n [0.5 , 0.43560606, 0.56439394],\n [0.5 , 0.43181818, 0.56818182],\n [0.5 , 0.4280303 , 0.5719697 ],\n [0.5 , 0.42424242, 0.57575758],\n [0.5 , 0.42045455, 0.57954545],\n [0.5 , 0.41666667, 0.58333333],\n [0.5 , 0.41287879, 0.58712121],\n [0.5 , 0.40909091, 0.59090909],\n [0.5 , 0.40530303, 0.59469697],\n [0.5 , 0.40151515, 0.59848485],\n [0.5 , 0.39772727, 0.60227273],\n [0.5 , 0.39393939, 0.60606061],\n [0.5 , 0.39015152, 0.60984848],\n [0.5 , 0.38636364, 0.61363636],\n [0.5 , 0.38257576, 0.61742424],\n [0.5 , 0.37878788, 0.62121212],\n [0.5 , 0.375 , 0.625 ],\n [0.5 , 0.37121212, 0.62878788],\n [0.5 , 0.36742424, 0.63257576],\n [0.5 , 0.36363636, 0.63636364],\n [0.5 , 0.35984848, 0.64015152],\n [0.5 , 0.35606061, 0.64393939],\n [0.5 , 0.35227273, 0.64772727],\n [0.5 , 0.34848485, 0.65151515],\n [0.5 , 0.34469697, 0.65530303],\n [0.5 , 0.34090909, 0.65909091],\n [0.5 , 0.33712121, 0.66287879],\n [0.5 , 0.33333333, 0.66666667],\n [0.5 , 0.32954545, 0.67045455],\n [0.5 , 0.32575758, 0.67424242],\n [0.5 , 0.3219697 , 0.6780303 ],\n [0.5 , 0.31818182, 0.68181818],\n [0.5 , 0.31439394, 0.68560606],\n [0.5 , 0.31060606, 0.68939394],\n [0.5 , 0.30681818, 0.69318182],\n [0.5 , 0.3030303 , 0.6969697 ],\n [0.5 , 0.29924242, 0.70075758],\n [0.5 , 0.29545455, 0.70454545],\n [0.5 , 0.29166667, 0.70833333],\n [0.5 , 0.28787879, 0.71212121],\n [0.5 , 0.28409091, 0.71590909],\n [0.5 , 0.28030303, 0.71969697],\n [0.5 , 0.27651515, 0.72348485],\n [0.5 , 0.27272727, 0.72727273],\n [0.5 , 0.26893939, 0.73106061],\n [0.5 , 0.26515152, 0.73484848],\n [0.5 , 0.26136364, 0.73863636],\n [0.5 , 0.25757576, 0.74242424],\n [0.5 , 0.25378788, 0.74621212],\n [0.5 , 0.25 , 0.75 ]]),\n array([[0.5 , 0.25 , 0.75 ],\n [0.5 , 0.24468085, 0.74468085],\n [0.5 , 0.2393617 , 0.7393617 ],\n [0.5 , 0.23404255, 0.73404255],\n [0.5 , 0.2287234 , 0.7287234 ],\n [0.5 , 0.22340426, 0.72340426],\n [0.5 , 0.21808511, 0.71808511],\n [0.5 , 0.21276596, 0.71276596],\n [0.5 , 0.20744681, 0.70744681],\n [0.5 , 0.20212766, 0.70212766],\n [0.5 , 0.19680851, 0.69680851],\n [0.5 , 0.19148936, 0.69148936],\n [0.5 , 0.18617021, 0.68617021],\n [0.5 , 0.18085106, 0.68085106],\n [0.5 , 0.17553191, 0.67553191],\n [0.5 , 0.17021277, 0.67021277],\n [0.5 , 0.16489362, 0.66489362],\n [0.5 , 0.15957447, 0.65957447],\n [0.5 , 0.15425532, 0.65425532],\n [0.5 , 0.14893617, 0.64893617],\n [0.5 , 0.14361702, 0.64361702],\n [0.5 , 0.13829787, 0.63829787],\n [0.5 , 0.13297872, 0.63297872],\n [0.5 , 0.12765957, 0.62765957],\n [0.5 , 0.12234043, 0.62234043],\n [0.5 , 0.11702128, 0.61702128],\n [0.5 , 0.11170213, 0.61170213],\n [0.5 , 0.10638298, 0.60638298],\n [0.5 , 0.10106383, 0.60106383],\n [0.5 , 0.09574468, 0.59574468],\n [0.5 , 0.09042553, 0.59042553],\n [0.5 , 0.08510638, 0.58510638],\n [0.5 , 0.07978723, 0.57978723],\n [0.5 , 0.07446809, 0.57446809],\n [0.5 , 0.06914894, 0.56914894],\n [0.5 , 0.06382979, 0.56382979],\n [0.5 , 0.05851064, 0.55851064],\n [0.5 , 0.05319149, 0.55319149],\n [0.5 , 0.04787234, 0.54787234],\n [0.5 , 0.04255319, 0.54255319],\n [0.5 , 0.03723404, 0.53723404],\n [0.5 , 0.03191489, 0.53191489],\n [0.5 , 0.02659574, 0.52659574],\n [0.5 , 0.0212766 , 0.5212766 ],\n [0.5 , 0.01595745, 0.51595745],\n [0.5 , 0.0106383 , 0.5106383 ],\n [0.5 , 0.00531915, 0.50531915],\n [0.5 , 0. , 0.5 ]])],\n 'distances': [array([0. , 0.00195846, 0.00391691, 0.00587537, 0.00783383,\n 0.00979229, 0.01175074, 0.0137092 , 0.01566766, 0.01762611,\n 0.01958457, 0.02154303, 0.02350149, 0.02545994, 0.0274184 ,\n 0.02937686, 0.03133531, 0.03329377, 0.03525223, 0.03721068,\n 0.03916914, 0.0411276 , 0.04308606, 0.04504451, 0.04700297,\n 0.04896143, 0.05091988, 0.05287834, 0.0548368 , 0.05679526,\n 0.05875371, 0.06071217, 0.06267063, 0.06462908, 0.06658754,\n 0.068546 , 0.07050446, 0.07246291, 0.07442137, 0.07637983,\n 0.07833828, 0.08029674, 0.0822552 , 0.08421366, 0.08617211,\n 0.08813057, 0.09008903, 0.09204748, 0.09400594, 0.0959644 ,\n 0.09792285, 0.09988131, 0.10183977, 0.10379823, 0.10575668,\n 0.10771514, 0.1096736 , 0.11163205, 0.11359051, 0.11554897,\n 0.11750743, 0.11946588, 0.12142434, 0.1233828 , 0.12534125,\n 0.12729971, 0.12925817, 0.13121663, 0.13317508, 0.13513354,\n 0.137092 , 0.13905045, 0.14100891, 0.14296737, 0.14492583,\n 0.14688428, 0.14884274, 0.1508012 , 0.15275965, 0.15471811,\n 0.15667657, 0.15863503, 0.16059348, 0.16255194, 0.1645104 ,\n 0.16646885, 0.16842731, 0.17038577, 0.17234422, 0.17430268,\n 0.17626114, 0.1782196 , 0.18017805, 0.18213651, 0.18409497]),\n array([0.18409497, 0.18606731, 0.18803966, 0.190012 , 0.19198435,\n 0.19395669, 0.19592904, 0.19790139, 0.19987373, 0.20184608,\n 0.20381842, 0.20579077, 0.20776311, 0.20973546, 0.2117078 ,\n 0.21368015, 0.21565249, 0.21762484, 0.21959719, 0.22156953,\n 0.22354188, 0.22551422, 0.22748657, 0.22945891, 0.23143126,\n 0.2334036 , 0.23537595, 0.23734829, 0.23932064, 0.24129299,\n 0.24326533, 0.24523768, 0.24721002, 0.24918237]),\n array([0.24918237, 0.25113499, 0.25308761, 0.25504023, 0.25699286,\n 0.25894548, 0.2608981 , 0.26285072, 0.26480334, 0.26675597,\n 0.26870859, 0.27066121, 0.27261383, 0.27456645, 0.27651908,\n 0.2784717 , 0.28042432, 0.28237694, 0.28432956, 0.28628219,\n 0.28823481, 0.29018743, 0.29214005, 0.29409267, 0.2960453 ,\n 0.29799792, 0.29995054, 0.30190316, 0.30385578, 0.30580841,\n 0.30776103, 0.30971365, 0.31166627, 0.31361889, 0.31557152,\n 0.31752414, 0.31947676, 0.32142938, 0.323382 , 0.32533463,\n 0.32728725, 0.32923987, 0.33119249, 0.33314511, 0.33509774,\n 0.33705036, 0.33900298, 0.3409556 , 0.34290822, 0.34486085,\n 0.34681347, 0.34876609, 0.35071871, 0.35267133, 0.35462396,\n 0.35657658, 0.3585292 , 0.36048182, 0.36243444, 0.36438707,\n 0.36633969, 0.36829231, 0.37024493, 0.37219755, 0.37415018,\n 0.3761028 , 0.37805542, 0.38000804, 0.38196066, 0.38391329,\n 0.38586591, 0.38781853, 0.38977115, 0.39172377, 0.3936764 ,\n 0.39562902, 0.39758164, 0.39953426, 0.40148688, 0.40343951,\n 0.40539213, 0.40734475, 0.40929737, 0.41124999, 0.41320262,\n 0.41515524, 0.41710786, 0.41906048, 0.4210131 , 0.42296573,\n 0.42491835, 0.42687097, 0.42882359, 0.43077621, 0.43272884,\n 0.43468146, 0.43663408, 0.4385867 , 0.44053932, 0.44249194,\n 0.44444457]),\n array([0.44444457, 0.44641285, 0.44838113, 0.45034942, 0.4523177 ,\n 0.45428598, 0.45625426, 0.45822255, 0.46019083, 0.46215911,\n 0.4641274 , 0.46609568, 0.46806396, 0.47003225, 0.47200053,\n 0.47396881, 0.47593709, 0.47790538, 0.47987366, 0.48184194,\n 0.48381023, 0.48577851, 0.48774679, 0.48971507, 0.49168336,\n 0.49365164, 0.49561992, 0.49758821, 0.49955649, 0.50152477,\n 0.50349306, 0.50546134, 0.50742962, 0.5093979 , 0.51136619,\n 0.51333447, 0.51530275, 0.51727104, 0.51923932, 0.5212076 ,\n 0.52317588, 0.52514417, 0.52711245, 0.52908073, 0.53104902,\n 0.5330173 , 0.53498558, 0.53695387, 0.53892215, 0.54089043,\n 0.54285871, 0.544827 , 0.54679528, 0.54876356, 0.55073185,\n 0.55270013, 0.55466841, 0.55663669, 0.55860498, 0.56057326,\n 0.56254154, 0.56450983, 0.56647811, 0.56844639, 0.57041468,\n 0.57238296, 0.57435124, 0.57631952, 0.57828781, 0.58025609,\n 0.58222437, 0.58419266, 0.58616094, 0.58812922, 0.5900975 ,\n 0.59206579, 0.59403407, 0.59600235, 0.59797064, 0.59993892,\n 0.6019072 , 0.60387549]),\n array([0.60387549, 0.60584783, 0.60782018, 0.60979252, 0.61176487,\n 0.61373721, 0.61570956, 0.6176819 , 0.61965425, 0.62162659,\n 0.62359894, 0.62557129, 0.62754363, 0.62951598, 0.63148832,\n 0.63346067, 0.63543301, 0.63740536, 0.6393777 , 0.64135005,\n 0.64332239, 0.64529474, 0.64726709, 0.64923943, 0.65121178,\n 0.65318412, 0.65515647, 0.65712881, 0.65910116, 0.6610735 ,\n 0.66304585, 0.66501819, 0.66699054, 0.66896289, 0.67093523,\n 0.67290758, 0.67487992, 0.67685227, 0.67882461, 0.68079696,\n 0.6827693 , 0.68474165, 0.68671399, 0.68868634, 0.69065869,\n 0.69263103, 0.69460338, 0.69657572, 0.69854807, 0.70052041,\n 0.70249276, 0.7044651 , 0.70643745, 0.70840979, 0.71038214,\n 0.71235449, 0.71432683, 0.71629918, 0.71827152, 0.72024387,\n 0.72221621, 0.72418856, 0.7261609 , 0.72813325, 0.73010559,\n 0.73207794, 0.73405029]),\n array([0.73405029, 0.73600874, 0.7379672 , 0.73992566, 0.74188411,\n 0.74384257, 0.74580103, 0.74775948, 0.74971794, 0.7516764 ,\n 0.75363486, 0.75559331, 0.75755177, 0.75951023, 0.76146868,\n 0.76342714, 0.7653856 , 0.76734406, 0.76930251, 0.77126097,\n 0.77321943, 0.77517788, 0.77713634, 0.7790948 , 0.78105326,\n 0.78301171, 0.78497017, 0.78692863, 0.78888708, 0.79084554,\n 0.792804 , 0.79476246, 0.79672091, 0.79867937, 0.80063783,\n 0.80259628, 0.80455474, 0.8065132 , 0.80847166, 0.81043011,\n 0.81238857, 0.81434703, 0.81630548, 0.81826394, 0.8202224 ,\n 0.82218085, 0.82413931, 0.82609777])],\n 'frequencies': [array([[2.18701057e-06, 2.19691522e-06, 2.20369934e-06, 1.60678991e+01,\n 1.60678991e+01, 1.60678991e+01],\n [1.06625590e-01, 1.06625590e-01, 1.53239098e-01, 1.60675081e+01,\n 1.60676418e+01, 1.60676418e+01],\n [2.13231909e-01, 2.13231909e-01, 3.06460038e-01, 1.60663351e+01,\n 1.60668701e+01, 1.60668701e+01],\n [3.19799678e-01, 3.19799678e-01, 4.59644667e-01, 1.60643797e+01,\n 1.60655844e+01, 1.60655844e+01],\n [4.26309607e-01, 4.26309607e-01, 6.12774843e-01, 1.60616416e+01,\n 1.60637853e+01, 1.60637853e+01],\n [5.32742383e-01, 5.32742383e-01, 7.65832440e-01, 1.60581201e+01,\n 1.60614737e+01, 1.60614737e+01],\n [6.39078667e-01, 6.39078667e-01, 9.18799354e-01, 1.60538144e+01,\n 1.60586506e+01, 1.60586506e+01],\n [7.45299086e-01, 7.45299086e-01, 1.07165751e+00, 1.60487235e+01,\n 1.60553175e+01, 1.60553175e+01],\n [8.51384225e-01, 8.51384225e-01, 1.22438885e+00, 1.60428463e+01,\n 1.60514759e+01, 1.60514759e+01],\n [9.57314622e-01, 9.57314622e-01, 1.37697538e+00, 1.60361814e+01,\n 1.60471277e+01, 1.60471277e+01],\n [1.06307076e+00, 1.06307076e+00, 1.52939913e+00, 1.60287272e+01,\n 1.60422751e+01, 1.60422751e+01],\n [1.16863306e+00, 1.16863306e+00, 1.68164218e+00, 1.60204822e+01,\n 1.60369205e+01, 1.60369205e+01],\n [1.27398186e+00, 1.27398186e+00, 1.83368666e+00, 1.60114444e+01,\n 1.60310665e+01, 1.60310665e+01],\n [1.37909745e+00, 1.37909745e+00, 1.98551477e+00, 1.60016119e+01,\n 1.60247161e+01, 1.60247161e+01],\n [1.48396001e+00, 1.48396001e+00, 2.13710877e+00, 1.59909824e+01,\n 1.60178724e+01, 1.60178724e+01],\n [1.58854964e+00, 1.58854964e+00, 2.28845098e+00, 1.59795536e+01,\n 1.60105390e+01, 1.60105390e+01],\n [1.69284632e+00, 1.69284632e+00, 2.43952381e+00, 1.59673229e+01,\n 1.60027197e+01, 1.60027197e+01],\n [1.79682995e+00, 1.79682995e+00, 2.59030972e+00, 1.59542878e+01,\n 1.59944185e+01, 1.59944185e+01],\n [1.90048030e+00, 1.90048030e+00, 2.74079128e+00, 1.59404453e+01,\n 1.59856398e+01, 1.59856398e+01],\n [2.00377700e+00, 2.00377700e+00, 2.89095116e+00, 1.59257926e+01,\n 1.59763882e+01, 1.59763882e+01],\n [2.10669956e+00, 2.10669956e+00, 3.04077208e+00, 1.59103264e+01,\n 1.59666687e+01, 1.59666687e+01],\n [2.20922736e+00, 2.20922736e+00, 3.19023691e+00, 1.58940435e+01,\n 1.59564867e+01, 1.59564867e+01],\n [2.31133960e+00, 2.31133960e+00, 3.33932858e+00, 1.58769405e+01,\n 1.59458477e+01, 1.59458477e+01],\n [2.41301534e+00, 2.41301534e+00, 3.48803016e+00, 1.58590139e+01,\n 1.59347578e+01, 1.59347578e+01],\n [2.51423346e+00, 2.51423346e+00, 3.63632482e+00, 1.58402599e+01,\n 1.59232232e+01, 1.59232232e+01],\n [2.61497266e+00, 2.61497266e+00, 3.78419585e+00, 1.58206748e+01,\n 1.59112506e+01, 1.59112506e+01],\n [2.71521144e+00, 2.71521144e+00, 3.93162667e+00, 1.58002545e+01,\n 1.58988470e+01, 1.58988470e+01],\n [2.81492813e+00, 2.81492813e+00, 4.07860083e+00, 1.57789952e+01,\n 1.58860198e+01, 1.58860198e+01],\n [2.91410081e+00, 2.91410081e+00, 4.22510199e+00, 1.57568925e+01,\n 1.58727768e+01, 1.58727768e+01],\n [3.01270737e+00, 3.01270737e+00, 4.37111398e+00, 1.57339422e+01,\n 1.58591262e+01, 1.58591262e+01],\n [3.11072544e+00, 3.11072544e+00, 4.51662075e+00, 1.57101400e+01,\n 1.58450764e+01, 1.58450764e+01],\n [3.20813243e+00, 3.20813243e+00, 4.66160641e+00, 1.56854812e+01,\n 1.58306367e+01, 1.58306367e+01],\n [3.30490548e+00, 3.30490548e+00, 4.80605520e+00, 1.56599614e+01,\n 1.58158162e+01, 1.58158162e+01],\n [3.40102147e+00, 3.40102147e+00, 4.94995155e+00, 1.56335759e+01,\n 1.58006249e+01, 1.58006249e+01],\n [3.49645700e+00, 3.49645700e+00, 5.09328001e+00, 1.56063199e+01,\n 1.57850732e+01, 1.57850732e+01],\n [3.59118839e+00, 3.59118839e+00, 5.23602533e+00, 1.55781885e+01,\n 1.57691716e+01, 1.57691716e+01],\n [3.68519163e+00, 3.68519163e+00, 5.37817241e+00, 1.55491768e+01,\n 1.57529316e+01, 1.57529316e+01],\n [3.77844244e+00, 3.77844244e+00, 5.51970631e+00, 1.55192800e+01,\n 1.57363649e+01, 1.57363649e+01],\n [3.87091618e+00, 3.87091618e+00, 5.66061230e+00, 1.54884928e+01,\n 1.57194835e+01, 1.57194835e+01],\n [3.96258789e+00, 3.96258789e+00, 5.80087581e+00, 1.54568102e+01,\n 1.57023004e+01, 1.57023004e+01],\n [4.05343226e+00, 4.05343226e+00, 5.94048245e+00, 1.54242271e+01,\n 1.56848288e+01, 1.56848288e+01],\n [4.14342363e+00, 4.14342363e+00, 6.07941802e+00, 1.53907382e+01,\n 1.56670824e+01, 1.56670824e+01],\n [4.23253595e+00, 4.23253595e+00, 6.21766853e+00, 1.53563383e+01,\n 1.56490757e+01, 1.56490757e+01],\n [4.32074280e+00, 4.32074280e+00, 6.35522016e+00, 1.53210221e+01,\n 1.56308235e+01, 1.56308235e+01],\n [4.40801738e+00, 4.40801738e+00, 6.49205931e+00, 1.52847843e+01,\n 1.56123413e+01, 1.56123413e+01],\n [4.49433246e+00, 4.49433246e+00, 6.62817257e+00, 1.52476196e+01,\n 1.55936453e+01, 1.55936453e+01],\n [4.57966044e+00, 4.57966044e+00, 6.76354674e+00, 1.52095227e+01,\n 1.55747520e+01, 1.55747520e+01],\n [4.66397327e+00, 4.66397327e+00, 6.89816884e+00, 1.51704881e+01,\n 1.55556788e+01, 1.55556788e+01],\n [4.74724248e+00, 4.74724248e+00, 7.03202608e+00, 1.51305106e+01,\n 1.55364436e+01, 1.55364436e+01],\n [4.82943918e+00, 4.82943918e+00, 7.16510590e+00, 1.50895847e+01,\n 1.55170649e+01, 1.55170649e+01],\n [4.91053403e+00, 4.91053403e+00, 7.29739597e+00, 1.50477052e+01,\n 1.54975617e+01, 1.54975617e+01],\n [4.99049726e+00, 4.99049726e+00, 7.42888415e+00, 1.50048667e+01,\n 1.54779540e+01, 1.54779540e+01],\n [5.06929865e+00, 5.06929865e+00, 7.55955856e+00, 1.49610639e+01,\n 1.54582620e+01, 1.54582620e+01],\n [5.14690753e+00, 5.14690753e+00, 7.68940753e+00, 1.49162915e+01,\n 1.54385069e+01, 1.54385069e+01],\n [5.22329282e+00, 5.22329282e+00, 7.81841962e+00, 1.48705443e+01,\n 1.54187103e+01, 1.54187103e+01],\n [5.29842297e+00, 5.29842297e+00, 7.94658362e+00, 1.48238171e+01,\n 1.53988946e+01, 1.53988946e+01],\n [5.37226600e+00, 5.37226600e+00, 8.07388856e+00, 1.47761047e+01,\n 1.53790827e+01, 1.53790827e+01],\n [5.44478953e+00, 5.44478953e+00, 8.20032372e+00, 1.47274020e+01,\n 1.53592983e+01, 1.53592983e+01],\n [5.51596076e+00, 5.51596076e+00, 8.32587860e+00, 1.46777039e+01,\n 1.53395654e+01, 1.53395654e+01],\n [5.58574651e+00, 5.58574651e+00, 8.45054294e+00, 1.46270056e+01,\n 1.53199089e+01, 1.53199089e+01],\n [5.65411319e+00, 5.65411319e+00, 8.57430676e+00, 1.45753020e+01,\n 1.53003542e+01, 1.53003542e+01],\n [5.72102691e+00, 5.72102691e+00, 8.69716027e+00, 1.45225884e+01,\n 1.52809272e+01, 1.52809272e+01],\n [5.78645342e+00, 5.78645342e+00, 8.81909398e+00, 1.44688599e+01,\n 1.52616544e+01, 1.52616544e+01],\n [5.85035821e+00, 5.85035821e+00, 8.94009862e+00, 1.44141121e+01,\n 1.52425628e+01, 1.52425628e+01],\n [5.91270648e+00, 5.91270648e+00, 9.06016518e+00, 1.43583401e+01,\n 1.52236797e+01, 1.52236797e+01],\n [5.97346325e+00, 5.97346325e+00, 9.17928491e+00, 1.43015397e+01,\n 1.52050331e+01, 1.52050331e+01],\n [6.03259336e+00, 6.03259336e+00, 9.29744928e+00, 1.42437065e+01,\n 1.51866511e+01, 1.51866511e+01],\n [6.09006155e+00, 6.09006155e+00, 9.41465007e+00, 1.41848361e+01,\n 1.51685625e+01, 1.51685625e+01],\n [6.14583250e+00, 6.14583250e+00, 9.53087927e+00, 1.41249246e+01,\n 1.51507959e+01, 1.51507959e+01],\n [6.19987090e+00, 6.19987090e+00, 9.64612916e+00, 1.40639678e+01,\n 1.51333805e+01, 1.51333805e+01],\n [6.25214152e+00, 6.25214152e+00, 9.76039224e+00, 1.40019619e+01,\n 1.51163455e+01, 1.51163455e+01],\n [6.30260929e+00, 6.30260929e+00, 9.87366131e+00, 1.39389032e+01,\n 1.50997202e+01, 1.50997202e+01],\n [6.35123937e+00, 6.35123937e+00, 9.98592942e+00, 1.38747880e+01,\n 1.50835337e+01, 1.50835337e+01],\n [6.39799726e+00, 6.39799726e+00, 1.00971898e+01, 1.38096130e+01,\n 1.50678154e+01, 1.50678154e+01],\n [6.44284885e+00, 6.44284885e+00, 1.02074362e+01, 1.37433748e+01,\n 1.50525941e+01, 1.50525941e+01],\n [6.48576059e+00, 6.48576059e+00, 1.03166622e+01, 1.36760703e+01,\n 1.50378985e+01, 1.50378985e+01],\n [6.52669951e+00, 6.52669951e+00, 1.04248621e+01, 1.36076964e+01,\n 1.50237569e+01, 1.50237569e+01],\n [6.56563338e+00, 6.56563338e+00, 1.05320301e+01, 1.35382504e+01,\n 1.50101972e+01, 1.50101972e+01],\n [6.60253081e+00, 6.60253081e+00, 1.06381608e+01, 1.34677297e+01,\n 1.49972465e+01, 1.49972465e+01],\n [6.63736135e+00, 6.63736135e+00, 1.07432492e+01, 1.33961316e+01,\n 1.49849313e+01, 1.49849313e+01],\n [6.67009563e+00, 6.67009563e+00, 1.08472903e+01, 1.33234540e+01,\n 1.49732773e+01, 1.49732773e+01],\n [6.70070547e+00, 6.70070547e+00, 1.09502796e+01, 1.32496947e+01,\n 1.49623091e+01, 1.49623091e+01],\n [6.72916397e+00, 6.72916397e+00, 1.10522127e+01, 1.31748518e+01,\n 1.49520504e+01, 1.49520504e+01],\n [6.75544567e+00, 6.75544567e+00, 1.11530855e+01, 1.30989236e+01,\n 1.49425237e+01, 1.49425237e+01],\n [6.77952663e+00, 6.77952663e+00, 1.12528941e+01, 1.30219085e+01,\n 1.49337500e+01, 1.49337500e+01],\n [6.80138457e+00, 6.80138457e+00, 1.13516350e+01, 1.29438053e+01,\n 1.49257493e+01, 1.49257493e+01],\n [6.82099896e+00, 6.82099896e+00, 1.14493049e+01, 1.28646126e+01,\n 1.49185396e+01, 1.49185396e+01],\n [6.83835113e+00, 6.83835113e+00, 1.15459006e+01, 1.27843298e+01,\n 1.49121375e+01, 1.49121375e+01],\n [6.85342435e+00, 6.85342435e+00, 1.16414194e+01, 1.27029559e+01,\n 1.49065581e+01, 1.49065581e+01],\n [6.86620396e+00, 6.86620396e+00, 1.17358587e+01, 1.26204906e+01,\n 1.49018144e+01, 1.49018144e+01],\n [6.87667737e+00, 6.87667737e+00, 1.18292162e+01, 1.25369336e+01,\n 1.48979177e+01, 1.48979177e+01],\n [6.88483424e+00, 6.88483424e+00, 1.19214899e+01, 1.24522848e+01,\n 1.48948771e+01, 1.48948771e+01],\n [6.89066641e+00, 6.89066641e+00, 1.20126778e+01, 1.23665443e+01,\n 1.48927000e+01, 1.48927000e+01],\n [6.89416806e+00, 6.89416806e+00, 1.21027784e+01, 1.22797127e+01,\n 1.48913917e+01, 1.48913917e+01],\n [6.89533567e+00, 6.89533567e+00, 1.21917904e+01, 1.21917904e+01,\n 1.48909552e+01, 1.48909552e+01]]),\n array([[ 6.89533567, 6.89533567, 12.19179039, 12.19179039, 14.89095524,\n 14.89095524],\n [ 6.89476599, 6.89721307, 12.19035931, 12.19131253, 14.89109076,\n 14.89177681],\n [ 6.8930571 , 6.90283616, 12.18607431, 12.18988157, 14.8914973 ,\n 14.89423361],\n [ 6.89020956, 6.91217764, 12.17895978, 12.18750534, 14.89217481,\n 14.89830206],\n [ 6.88622426, 6.92519216, 12.16905574, 12.18419693, 14.89312318,\n 14.90394357],\n [ 6.88110243, 6.9418166 , 12.15641674, 12.17997485, 14.89434227,\n 14.91110552],\n [ 6.8748457 , 6.96197032, 12.1411106 , 12.17486306, 14.89583189,\n 14.9197226 ],\n [ 6.86745601, 6.98555564, 12.1232168 , 12.16889124, 14.89759181,\n 14.92971834],\n [ 6.85893568, 7.0124582 , 12.10282475, 12.16209492, 14.89962177,\n 14.94100685],\n [ 6.84928737, 7.04254753, 12.08003199, 12.15451577, 14.90192145,\n 14.9534946 ],\n [ 6.83851409, 7.07567754, 12.05494232, 12.14620185, 14.90449047,\n 14.96708225],\n [ 6.8266192 , 7.11168706, 12.02766403, 12.13720797, 14.90732842,\n 14.98166641],\n [ 6.81360641, 7.1504004 , 11.99830825, 12.12759601, 14.91043482,\n 14.99714124],\n [ 6.79947975, 7.19162786, 11.96698741, 12.11743535, 14.91380915,\n 15.01339997],\n [ 6.78424361, 7.23516623, 11.93381387, 12.10680327, 14.91745083,\n 15.03033626],\n [ 6.7679027 , 7.28079926, 11.89889873, 12.0957854 , 14.9213592 ,\n 15.04784527],\n [ 6.75046209, 7.32829805, 11.86235086, 12.08447621, 14.92553355,\n 15.06582469],\n [ 6.73192714, 7.3774215 , 11.82427602, 12.07297947, 14.92997311,\n 15.0841755 ],\n [ 6.71230356, 7.42791658, 11.78477623, 12.06140874, 14.93467703,\n 15.1028026 ],\n [ 6.69159738, 7.47951874, 11.74394921, 12.0498878 , 14.93964437,\n 15.12161529],\n [ 6.66981492, 7.53195215, 11.701888 , 12.03855107, 14.94487413,\n 15.14052765],\n [ 6.64696284, 7.58493013, 11.65868065, 12.02754391, 14.95036522,\n 15.15945873],\n [ 6.62304809, 7.6381555 , 11.61441001, 12.01702285, 14.95611647,\n 15.17833279],\n [ 6.59807794, 7.69132112, 11.5691536 , 12.0071556 , 14.96212661,\n 15.19707928],\n [ 6.57205993, 7.74411056, 11.52298356, 11.99812092, 14.96839427,\n 15.21563293],\n [ 6.5450019 , 7.79619897, 11.47596658, 11.99010811, 14.974918 ,\n 15.23393372],\n [ 6.51691198, 7.8472543 , 11.42816396, 11.98331627, 14.98169623,\n 15.25192677],\n [ 6.48779857, 7.89693879, 11.3796316 , 11.9779531 , 14.98872728,\n 15.26956229],\n [ 6.45767036, 7.94491097, 11.33042012, 11.97423316, 14.99600936,\n 15.28679543],\n [ 6.42653627, 7.99082805, 11.28057486, 11.97237575, 15.00354058,\n 15.30358621],\n [ 6.39440553, 8.03434895, 11.23013602, 11.97260212, 15.01131889,\n 15.31989932],\n [ 6.36128757, 8.07513774, 11.17913872, 11.97513212, 15.01934216,\n 15.33570402],\n [ 6.3271921 , 8.11286763, 11.12761311, 11.98018037, 15.02760809,\n 15.35097401],\n [ 6.29212906, 8.1472254 , 11.07558447, 11.98795191, 15.03611427,\n 15.36568722]]),\n array([[6.29212906e+00, 8.14722540e+00, 1.10755845e+01, 1.19879519e+01,\n 1.50361143e+01, 1.53656872e+01],\n [6.25647352e+00, 8.17762824e+00, 1.10236007e+01, 1.19985158e+01,\n 1.50447695e+01, 1.53796873e+01],\n [6.21988972e+00, 8.20417287e+00, 1.09711594e+01, 1.20121030e+01,\n 1.50536551e+01, 1.53931105e+01],\n [6.18238794e+00, 8.22662180e+00, 1.09182714e+01, 1.20288578e+01,\n 1.50627683e+01, 1.54059471e+01],\n [6.14397867e+00, 8.24476801e+00, 1.08649436e+01, 1.20488984e+01,\n 1.50721062e+01, 1.54181907e+01],\n [6.10467261e+00, 8.25843843e+00, 1.08111782e+01, 1.20723127e+01,\n 1.50816657e+01, 1.54298385e+01],\n [6.06448062e+00, 8.26749638e+00, 1.07569737e+01, 1.20991563e+01,\n 1.50914436e+01, 1.54408909e+01],\n [6.02341375e+00, 8.27184310e+00, 1.07023245e+01, 1.21294507e+01,\n 1.51014366e+01, 1.54513515e+01],\n [5.98148322e+00, 8.27141809e+00, 1.06472210e+01, 1.21631830e+01,\n 1.51116412e+01, 1.54612269e+01],\n [5.93870041e+00, 8.26619826e+00, 1.05916501e+01, 1.22003070e+01,\n 1.51220536e+01, 1.54705266e+01],\n [5.89507685e+00, 8.25619607e+00, 1.05355947e+01, 1.22407444e+01,\n 1.51326701e+01, 1.54792629e+01],\n [5.85062423e+00, 8.24145671e+00, 1.04790345e+01, 1.22843880e+01,\n 1.51434866e+01, 1.54874505e+01],\n [5.80535435e+00, 8.22205454e+00, 1.04219458e+01, 1.23311050e+01,\n 1.51544990e+01, 1.54951070e+01],\n [5.75927918e+00, 8.19808909e+00, 1.03643013e+01, 1.23807412e+01,\n 1.51657030e+01, 1.55022519e+01],\n [5.71241078e+00, 8.16968082e+00, 1.03060712e+01, 1.24331247e+01,\n 1.51770940e+01, 1.55089071e+01],\n [5.66476132e+00, 8.13696682e+00, 1.02472222e+01, 1.24880707e+01,\n 1.51886673e+01, 1.55150965e+01],\n [5.61634311e+00, 8.10009673e+00, 1.01877186e+01, 1.25453849e+01,\n 1.52004182e+01, 1.55208458e+01],\n [5.56716850e+00, 8.05922898e+00, 1.01275221e+01, 1.26048678e+01,\n 1.52123416e+01, 1.55261825e+01],\n [5.51724999e+00, 8.01452741e+00, 1.00665919e+01, 1.26663173e+01,\n 1.52244322e+01, 1.55311356e+01],\n [5.46660010e+00, 7.96615838e+00, 1.00048851e+01, 1.27295323e+01,\n 1.52366848e+01, 1.55357354e+01],\n [5.41523147e+00, 7.91428833e+00, 9.94235680e+00, 1.27943144e+01,\n 1.52490938e+01, 1.55400135e+01],\n [5.36315676e+00, 7.85908189e+00, 9.87896026e+00, 1.28604702e+01,\n 1.52616534e+01, 1.55440024e+01],\n [5.31038872e+00, 7.80070024e+00, 9.81464731e+00, 1.29278126e+01,\n 1.52743579e+01, 1.55477354e+01],\n [5.25694012e+00, 7.73930008e+00, 9.74936842e+00, 1.29961616e+01,\n 1.52872010e+01, 1.55512465e+01],\n [5.20282376e+00, 7.67503275e+00, 9.68307301e+00, 1.30653456e+01,\n 1.53001767e+01, 1.55545700e+01],\n [5.14805250e+00, 7.60804370e+00, 9.61570966e+00, 1.31352015e+01,\n 1.53132784e+01, 1.55577406e+01],\n [5.09263918e+00, 7.53847222e+00, 9.54722637e+00, 1.32055749e+01,\n 1.53264997e+01, 1.55607929e+01],\n [5.03659669e+00, 7.46645125e+00, 9.47757079e+00, 1.32763204e+01,\n 1.53398339e+01, 1.55637613e+01],\n [4.97993788e+00, 7.39210746e+00, 9.40669052e+00, 1.33473013e+01,\n 1.53532739e+01, 1.55666801e+01],\n [4.92267563e+00, 7.31556132e+00, 9.33453328e+00, 1.34183894e+01,\n 1.53668129e+01, 1.55695827e+01],\n [4.86482279e+00, 7.23692730e+00, 9.26104725e+00, 1.34894651e+01,\n 1.53804435e+01, 1.55725021e+01],\n [4.80639218e+00, 7.15631413e+00, 9.18618123e+00, 1.35604165e+01,\n 1.53941585e+01, 1.55754701e+01],\n [4.74739660e+00, 7.07382508e+00, 9.10988493e+00, 1.36311397e+01,\n 1.54079504e+01, 1.55785176e+01],\n [4.68784882e+00, 6.98955824e+00, 9.03210916e+00, 1.37015378e+01,\n 1.54218114e+01, 1.55816741e+01],\n [4.62776153e+00, 6.90360685e+00, 8.95280611e+00, 1.37715211e+01,\n 1.54357340e+01, 1.55849678e+01],\n [4.56714742e+00, 6.81605958e+00, 8.87192951e+00, 1.38410062e+01,\n 1.54497101e+01, 1.55884254e+01],\n [4.50601906e+00, 6.72700084e+00, 8.78943483e+00, 1.39099162e+01,\n 1.54637317e+01, 1.55920716e+01],\n [4.44438898e+00, 6.63651108e+00, 8.70527953e+00, 1.39781798e+01,\n 1.54777906e+01, 1.55959297e+01],\n [4.38226965e+00, 6.54466702e+00, 8.61942314e+00, 1.40457313e+01,\n 1.54918787e+01, 1.56000208e+01],\n [4.31967342e+00, 6.45154194e+00, 8.53182751e+00, 1.41125102e+01,\n 1.55059874e+01, 1.56043639e+01],\n [4.25661258e+00, 6.35720591e+00, 8.44245688e+00, 1.41784608e+01,\n 1.55201084e+01, 1.56089764e+01],\n [4.19309930e+00, 6.26172600e+00, 8.35127806e+00, 1.42435321e+01,\n 1.55342331e+01, 1.56138729e+01],\n [4.12914566e+00, 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1.60222682e+01,\n 1.60427741e+01, 1.60488597e+01],\n [6.66810854e-01, 9.58006865e-01, 1.52967192e+00, 1.60309922e+01,\n 1.60474790e+01, 1.60524581e+01],\n [5.92815147e-01, 8.51342252e-01, 1.36098882e+00, 1.60387766e+01,\n 1.60517159e+01, 1.60556853e+01],\n [5.18785904e-01, 7.44752868e-01, 1.19185462e+00, 1.60456283e+01,\n 1.60554758e+01, 1.60585387e+01],\n [4.44727457e-01, 6.38230684e-01, 1.02232518e+00, 1.60515536e+01,\n 1.60587508e+01, 1.60610163e+01],\n [3.70644079e-01, 5.31767125e-01, 8.52456593e-01, 1.60565579e+01,\n 1.60615337e+01, 1.60631159e+01],\n [2.96540000e-01, 4.25353148e-01, 6.82305119e-01, 1.60606459e+01,\n 1.60638187e+01, 1.60648360e+01],\n [2.22419407e-01, 3.18979315e-01, 5.11927163e-01, 1.60638214e+01,\n 1.60656010e+01, 1.60661753e+01],\n [1.48286457e-01, 2.12635869e-01, 3.41379243e-01, 1.60660875e+01,\n 1.60668768e+01, 1.60671327e+01],\n [7.41452829e-02, 1.06312817e-01, 1.70717968e-01, 1.60674463e+01,\n 1.60676434e+01, 1.60677074e+01],\n [2.18701057e-06, 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1.59104255e+01,\n 1.59998074e+01, 1.59998074e+01],\n [1.62169322e+00, 1.62169322e+00, 3.34178242e+00, 1.58922716e+01,\n 1.59922907e+01, 1.59922907e+01],\n [1.70367680e+00, 1.70367680e+00, 3.51372537e+00, 1.58730998e+01,\n 1.59844254e+01, 1.59844254e+01],\n [1.78513824e+00, 1.78513824e+00, 3.68506663e+00, 1.58529049e+01,\n 1.59762205e+01, 1.59762205e+01],\n [1.86605049e+00, 1.86605049e+00, 3.85577716e+00, 1.58316813e+01,\n 1.59676856e+01, 1.59676856e+01],\n [1.94638637e+00, 1.94638637e+00, 4.02582809e+00, 1.58094236e+01,\n 1.59588308e+01, 1.59588308e+01],\n [2.02611858e+00, 2.02611858e+00, 4.19519065e+00, 1.57861259e+01,\n 1.59496667e+01, 1.59496667e+01],\n [2.10521970e+00, 2.10521970e+00, 4.36383622e+00, 1.57617825e+01,\n 1.59402042e+01, 1.59402042e+01],\n [2.18366216e+00, 2.18366216e+00, 4.53173632e+00, 1.57363875e+01,\n 1.59304548e+01, 1.59304548e+01],\n [2.26141827e+00, 2.26141827e+00, 4.69886256e+00, 1.57099349e+01,\n 1.59204304e+01, 1.59204304e+01],\n [2.33846020e+00, 2.33846020e+00, 4.86518671e+00, 1.56824189e+01,\n 1.59101434e+01, 1.59101434e+01],\n [2.41475999e+00, 2.41475999e+00, 5.03068062e+00, 1.56538334e+01,\n 1.58996067e+01, 1.58996067e+01],\n [2.49028953e+00, 2.49028953e+00, 5.19531627e+00, 1.56241727e+01,\n 1.58888336e+01, 1.58888336e+01],\n [2.56502062e+00, 2.56502062e+00, 5.35906572e+00, 1.55934309e+01,\n 1.58778377e+01, 1.58778377e+01],\n [2.63892491e+00, 2.63892491e+00, 5.52190112e+00, 1.55616024e+01,\n 1.58666334e+01, 1.58666334e+01],\n [2.71197391e+00, 2.71197391e+00, 5.68379466e+00, 1.55286816e+01,\n 1.58552351e+01, 1.58552351e+01],\n [2.78413905e+00, 2.78413905e+00, 5.84471859e+00, 1.54946631e+01,\n 1.58436580e+01, 1.58436580e+01],\n [2.85539161e+00, 2.85539161e+00, 6.00464518e+00, 1.54595418e+01,\n 1.58319175e+01, 1.58319175e+01],\n [2.92570282e+00, 2.92570282e+00, 6.16354668e+00, 1.54233130e+01,\n 1.58200294e+01, 1.58200294e+01],\n [2.99504375e+00, 2.99504375e+00, 6.32139531e+00, 1.53859722e+01,\n 1.58080101e+01, 1.58080101e+01],\n [3.06338544e+00, 3.06338544e+00, 6.47816320e+00, 1.53475153e+01,\n 1.57958762e+01, 1.57958762e+01],\n [3.13069883e+00, 3.13069883e+00, 6.63382235e+00, 1.53079386e+01,\n 1.57836448e+01, 1.57836448e+01],\n [3.19695480e+00, 3.19695480e+00, 6.78834460e+00, 1.52672393e+01,\n 1.57713331e+01, 1.57713331e+01],\n [3.26212420e+00, 3.26212420e+00, 6.94170153e+00, 1.52254148e+01,\n 1.57589589e+01, 1.57589589e+01],\n [3.32617785e+00, 3.32617785e+00, 7.09386444e+00, 1.51824635e+01,\n 1.57465403e+01, 1.57465403e+01],\n [3.38908653e+00, 3.38908653e+00, 7.24480421e+00, 1.51383844e+01,\n 1.57340955e+01, 1.57340955e+01],\n [3.45082108e+00, 3.45082108e+00, 7.39449126e+00, 1.50931777e+01,\n 1.57216433e+01, 1.57216433e+01],\n [3.51135231e+00, 3.51135231e+00, 7.54289542e+00, 1.50468445e+01,\n 1.57092025e+01, 1.57092025e+01],\n [3.57065115e+00, 3.57065115e+00, 7.68998576e+00, 1.49993872e+01,\n 1.56967922e+01, 1.56967922e+01],\n [3.62868855e+00, 3.62868855e+00, 7.83573054e+00, 1.49508094e+01,\n 1.56844317e+01, 1.56844317e+01],\n [3.68543561e+00, 3.68543561e+00, 7.98009691e+00, 1.49011166e+01,\n 1.56721405e+01, 1.56721405e+01],\n [3.74086353e+00, 3.74086353e+00, 8.12305082e+00, 1.48503158e+01,\n 1.56599383e+01, 1.56599383e+01],\n [3.79494372e+00, 3.79494372e+00, 8.26455669e+00, 1.47984162e+01,\n 1.56478448e+01, 1.56478448e+01],\n [3.84764774e+00, 3.84764774e+00, 8.40457720e+00, 1.47454295e+01,\n 1.56358798e+01, 1.56358798e+01],\n [3.89894744e+00, 3.89894744e+00, 8.54307290e+00, 1.46913700e+01,\n 1.56240633e+01, 1.56240633e+01],\n [3.94881489e+00, 3.94881489e+00, 8.68000183e+00, 1.46362550e+01,\n 1.56124152e+01, 1.56124152e+01],\n [3.99722251e+00, 3.99722251e+00, 8.81531907e+00, 1.45801056e+01,\n 1.56009552e+01, 1.56009552e+01],\n [4.04414305e+00, 4.04414305e+00, 8.94897617e+00, 1.45229472e+01,\n 1.55897031e+01, 1.55897031e+01],\n [4.08954967e+00, 4.08954967e+00, 9.08092045e+00, 1.44648099e+01,\n 1.55786787e+01, 1.55786787e+01],\n [4.13341596e+00, 4.13341596e+00, 9.21109424e+00, 1.44057295e+01,\n 1.55679014e+01, 1.55679014e+01],\n [4.17571599e+00, 4.17571599e+00, 9.33943387e+00, 1.43457486e+01,\n 1.55573906e+01, 1.55573906e+01],\n [4.21642438e+00, 4.21642438e+00, 9.46586854e+00, 1.42849178e+01,\n 1.55471651e+01, 1.55471651e+01],\n [4.25551631e+00, 4.25551631e+00, 9.59031884e+00, 1.42232967e+01,\n 1.55372439e+01, 1.55372439e+01],\n [4.29296759e+00, 4.29296759e+00, 9.71269507e+00, 1.41609564e+01,\n 1.55276452e+01, 1.55276452e+01],\n [4.32875473e+00, 4.32875473e+00, 9.83289509e+00, 1.40979808e+01,\n 1.55183871e+01, 1.55183871e+01],\n [4.36285493e+00, 4.36285493e+00, 9.95080172e+00, 1.40344699e+01,\n 1.55094870e+01, 1.55094870e+01],\n [4.39524622e+00, 4.39524622e+00, 1.00662796e+01, 1.39705427e+01,\n 1.55009619e+01, 1.55009619e+01],\n [4.42590741e+00, 4.42590741e+00, 1.01791712e+01, 1.39063409e+01,\n 1.54928283e+01, 1.54928283e+01],\n [4.45481822e+00, 4.45481822e+00, 1.02892922e+01, 1.38420341e+01,\n 1.54851020e+01, 1.54851020e+01],\n [4.48195930e+00, 4.48195930e+00, 1.03964254e+01, 1.37778256e+01,\n 1.54777983e+01, 1.54777983e+01],\n [4.50731227e+00, 4.50731227e+00, 1.05003136e+01, 1.37139594e+01,\n 1.54709315e+01, 1.54709315e+01],\n [4.53085979e+00, 4.53085979e+00, 1.06006514e+01, 1.36507288e+01,\n 1.54645154e+01, 1.54645154e+01],\n [4.55258558e+00, 4.55258558e+00, 1.06970744e+01, 1.35884865e+01,\n 1.54585629e+01, 1.54585629e+01],\n [4.57247450e+00, 4.57247450e+00, 1.07891482e+01, 1.35276567e+01,\n 1.54530860e+01, 1.54530860e+01],\n [4.59051254e+00, 4.59051254e+00, 1.08763552e+01, 1.34687473e+01,\n 1.54480960e+01, 1.54480960e+01],\n [4.60668693e+00, 4.60668693e+00, 1.09580822e+01, 1.34123627e+01,\n 1.54436029e+01, 1.54436029e+01],\n [4.62098611e+00, 4.62098611e+00, 1.10336096e+01, 1.33592147e+01,\n 1.54396162e+01, 1.54396162e+01],\n [4.63339981e+00, 4.63339981e+00, 1.11021066e+01, 1.33101273e+01,\n 1.54361441e+01, 1.54361441e+01],\n [4.64391906e+00, 4.64391906e+00, 1.11626377e+01, 1.32660299e+01,\n 1.54331937e+01, 1.54331937e+01],\n [4.65253622e+00, 4.65253622e+00, 1.12141885e+01, 1.32279317e+01,\n 1.54307713e+01, 1.54307713e+01],\n [4.65924501e+00, 4.65924501e+00, 1.12557173e+01, 1.31968704e+01,\n 1.54288819e+01, 1.54288819e+01],\n [4.66404052e+00, 4.66404052e+00, 1.12862369e+01, 1.31738300e+01,\n 1.54275295e+01, 1.54275295e+01],\n [4.66691923e+00, 4.66691923e+00, 1.13049205e+01, 1.31596347e+01,\n 1.54267169e+01, 1.54267169e+01],\n [4.66787904e+00, 4.66787904e+00, 1.13112137e+01, 1.31548379e+01,\n 1.54264459e+01, 1.54264459e+01]]),\n array([[ 4.66787904, 4.66787904, 11.31121369, 13.15483786, 15.42644585,\n 15.42644585],\n [ 4.66883944, 4.67093501, 11.31069683, 13.15420714, 15.42624753,\n 15.42662672],\n [ 4.6717197 , 4.68008535, 11.30914699, 13.15231706, 15.42565317,\n 15.42716712],\n [ 4.67651706, 4.69527771, 11.30656644, 13.14917383, 15.42466453,\n 15.42806041],\n [ 4.68322686, 4.71642595, 11.30295898, 13.14478769, 15.42328455,\n 15.42929564],\n [ 4.69184265, 4.74341172, 11.29832994, 13.13917277, 15.42151735,\n 15.43085774],\n [ 4.70235612, 4.77608661, 11.2926863 , 13.13234687, 15.41936818,\n 15.43272765],\n [ 4.71475714, 4.8142747 , 11.28603666, 13.12433117, 15.41684348,\n 15.43488268],\n [ 4.72903381, 4.85777545, 11.2783914 , 13.11514998, 15.4139508 ,\n 15.43729674],\n [ 4.74517241, 4.90636678, 11.26976269, 13.10483036, 15.41069884,\n 15.43994075],\n [ 4.7631575 , 4.95980823, 11.26016464, 13.09340178, 15.40709737,\n 15.44278297],\n [ 4.78297187, 5.01784414, 11.2496134 , 13.08089571, 15.40315728,\n 15.44578941],\n [ 4.80459662, 5.08020666, 11.2381273 , 13.06734527, 15.39889052,\n 15.4489242 ],\n [ 4.82801117, 5.14661861, 11.22572702, 13.0527848 , 15.39431009,\n 15.45215004],\n [ 4.85319328, 5.21679606, 11.21243575, 13.0372495 , 15.38943 ,\n 15.45542857],\n [ 4.88011907, 5.29045068, 11.1982794 , 13.02077504, 15.38426525,\n 15.45872076],\n [ 4.90876308, 5.36729169, 11.18328681, 13.00339721, 15.37883182,\n 15.46198731],\n [ 4.93909829, 5.44702758, 11.16749005, 12.98515157, 15.3731466 ,\n 15.46518895],\n [ 4.97109613, 5.5293674 , 11.15092462, 12.96607314, 15.3672274 ,\n 15.46828687],\n [ 5.00472652, 5.61402185, 11.13362983, 12.94619611, 15.36109287,\n 15.47124292],\n [ 5.03995793, 5.700704 , 11.11564913, 12.92555359, 15.35476249,\n 15.47401998],\n [ 5.07675735, 5.78912978, 11.09703046, 12.90417733, 15.34825653,\n 15.47658222],\n [ 5.11509038, 5.87901817, 11.07782674, 12.88209755, 15.34159598,\n 15.47889527],\n [ 5.15492119, 5.97009122, 11.05809624, 12.85934274, 15.33480255,\n 15.48092653],\n [ 5.19621261, 6.06207386, 11.03790317, 12.83593951, 15.32789857,\n 15.48264529],\n [ 5.23892611, 6.15469351, 11.01731817, 12.81191244, 15.32090699,\n 15.48402293],\n [ 5.28302184, 6.24767954, 10.99641896, 12.78728396, 15.3138513 ,\n 15.48503308],\n [ 5.32845864, 6.34076267, 10.9752909 , 12.76207432, 15.30675548,\n 15.48565171],\n [ 5.37519406, 6.43367414, 10.9540277 , 12.73630143, 15.29964395,\n 15.48585731],\n [ 5.42318436, 6.52614493, 10.93273212, 12.7099809 , 15.2925415 ,\n 15.48563092],\n [ 5.47238454, 6.61790486, 10.91151663, 12.68312596, 15.28547325,\n 15.48495625],\n [ 5.52274835, 6.7086817 , 10.89050415, 12.65574747, 15.27846454,\n 15.48381973],\n [ 5.57422825, 6.79820026, 10.86982865, 12.62785393, 15.27154095,\n 15.48221057],\n [ 5.62677547, 6.88618163, 10.84963575, 12.5994515 , 15.26472812,\n 15.48012081],\n [ 5.68033995, 6.97234249, 10.83008312, 12.57054404, 15.25805176,\n 15.47754532],\n [ 5.73487036, 7.05639464, 10.81134075, 12.5411332 , 15.25153756,\n 15.47448184],\n [ 5.79031407, 7.13804489, 10.7935908 , 12.51121847, 15.24521107,\n 15.47093096],\n [ 5.84661715, 7.21699523, 10.77702722, 12.4807973 , 15.23909766,\n 15.46689616],\n [ 5.90372431, 7.2929437 , 10.76185465, 12.44986521, 15.23322244,\n 15.46238371],\n [ 5.96157886, 7.36558575, 10.74828691, 12.41841593, 15.22761012,\n 15.45740272],\n [ 6.0201227 , 7.43461652, 10.73654446, 12.38644156, 15.22228498,\n 15.45196503],\n [ 6.07929625, 7.49973393, 10.72685125, 12.35393277, 15.21727073,\n 15.44608518],\n [ 6.13903837, 7.56064276, 10.71943035, 12.32087899, 15.21259043,\n 15.43978036],\n [ 6.19928628, 7.61705972, 10.71449888, 12.28726865, 15.20826641,\n 15.43307027],\n [ 6.25997552, 7.66871935, 10.71226189, 12.25308943, 15.2043201 ,\n 15.42597708],\n [ 6.32103977, 7.71538058, 10.71290574, 12.21832858, 15.20077199,\n 15.41852527],\n [ 6.3824108 , 7.75683366, 10.71659108, 12.1829732 , 15.19764149,\n 15.41074154],\n [ 6.44401828, 7.79290678, 10.72344609, 12.14701063, 15.1949468 ,\n 15.40265463],\n [ 6.50578968, 7.82347218, 10.73356042, 12.11042881, 15.19270483,\n 15.39429522],\n [ 6.56765 , 7.84845077, 10.74698037, 12.07321672, 15.19093108,\n 15.3856957 ],\n [ 6.62952167, 7.86781512, 10.76370597, 12.03536482, 15.18963947,\n 15.37689002],\n [ 6.69132422, 7.88159025, 10.78369008, 11.99686561, 15.18884231,\n 15.36791351],\n [ 6.75297411, 7.88985221, 10.80683981, 11.95771409, 15.18855011,\n 15.35880262],\n [ 6.81438433, 7.89272444, 10.83302013, 11.91790844, 15.18877153,\n 15.34959476],\n [ 6.87546417, 7.8903724 , 10.86205919, 11.87745058, 15.18951322,\n 15.34032804],\n [ 6.93611876, 7.88299691, 10.89375497, 11.83634691, 15.19077974,\n 15.33104105],\n [ 6.99624871, 7.87082671, 10.92788271, 11.79460901, 15.19257349,\n 15.32177261],\n [ 7.05574959, 7.85411092, 10.9642024 , 11.75225444, 15.19489459,\n 15.31256153],\n [ 7.11451149, 7.83311182, 11.00246595, 11.70930758, 15.1977408 ,\n 15.30344637],\n [ 7.17241836, 7.80809838, 11.04242367, 11.66580048, 15.2011075 ,\n 15.29446521],\n [ 7.22934748, 7.77934065, 11.08382976, 11.62177384, 15.2049876 ,\n 15.2856554 ],\n [ 7.28516874, 7.7471053 , 11.12644676, 11.57727795, 15.20937152,\n 15.27705331],\n [ 7.33974397, 7.7116521 , 11.17004895, 11.53237371, 15.21424716,\n 15.26869413],\n [ 7.39292613, 7.67323138, 11.21442482, 11.48713365, 15.21959992,\n 15.26061169],\n [ 7.44455862, 7.6320824 , 11.25937862, 11.44164301, 15.22541272,\n 15.25283819],\n [ 7.49447447, 7.58843228, 11.30473122, 11.39600072, 15.23166602,\n 15.24540409],\n [ 7.54249562, 7.54249562, 11.3503204 , 11.3503204 , 15.23833788,\n 15.23833788]]),\n array([[ 7.54249562, 7.54249562, 11.3503204 , 11.3503204 , 15.23833788,\n 15.23833788],\n [ 7.54166641, 7.54166641, 11.35130975, 11.35130975, 15.23801134,\n 15.23801134],\n [ 7.53918446, 7.53918446, 11.35427194, 11.35427194, 15.23703255,\n 15.23703255],\n [ 7.53506676, 7.53506676, 11.35918952, 11.35918952, 15.23540407,\n 15.23540407],\n [ 7.52934132, 7.52934132, 11.36603365, 11.36603365, 15.23313011,\n 15.23313011],\n [ 7.52204673, 7.52204673, 11.37476455, 11.37476455, 15.23021665,\n 15.23021665],\n [ 7.51323165, 7.51323165, 11.38533198, 11.38533198, 15.22667136,\n 15.22667136],\n [ 7.50295407, 7.50295407, 11.39767597, 11.39767597, 15.22250365,\n 15.22250365],\n [ 7.49128048, 7.49128048, 11.41172752, 11.41172752, 15.21772475,\n 15.21772475],\n [ 7.47828508, 7.47828508, 11.42740943, 11.42740943, 15.21234764,\n 15.21234764],\n [ 7.46404878, 7.46404878, 11.44463718, 11.44463718, 15.20638716,\n 15.20638716],\n [ 7.44865827, 7.44865827, 11.46331976, 11.46331976, 15.19986003,\n 15.19986003],\n [ 7.43220511, 7.43220511, 11.48336059, 11.48336059, 15.19278485,\n 15.19278485],\n [ 7.41478473, 7.41478473, 11.50465834, 11.50465834, 15.18518221,\n 15.18518221],\n [ 7.39649562, 7.39649562, 11.5271077 , 11.5271077 , 15.17707467,\n 15.17707467],\n [ 7.3774384 , 7.3774384 , 11.55060018, 11.55060018, 15.16848683,\n 15.16848683],\n [ 7.35771513, 7.35771513, 11.57502474, 11.57502474, 15.15944541,\n 15.15944541],\n [ 7.33742851, 7.33742851, 11.60026839, 11.60026839, 15.14997924,\n 15.14997924],\n [ 7.3166813 , 7.3166813 , 11.62621676, 11.62621676, 15.14011934,\n 15.14011934],\n [ 7.29557569, 7.29557569, 11.65275454, 11.65275454, 15.12989893,\n 15.12989893],\n [ 7.27421283, 7.27421283, 11.6797659 , 11.6797659 , 15.11935352,\n 15.11935352],\n [ 7.25269237, 7.25269237, 11.7071348 , 11.7071348 , 15.10852087,\n 15.10852087],\n [ 7.23111204, 7.23111204, 11.73474528, 11.73474528, 15.09744106,\n 15.09744106],\n [ 7.20956738, 7.20956738, 11.76248171, 11.76248171, 15.08615647,\n 15.08615647],\n [ 7.1881514 , 7.1881514 , 11.79022897, 11.79022897, 15.07471177,\n 15.07471177],\n [ 7.16695438, 7.16695438, 11.81787268, 11.81787268, 15.06315389,\n 15.06315389],\n [ 7.14606363, 7.14606363, 11.84529928, 11.84529928, 15.05153196,\n 15.05153196],\n [ 7.12556335, 7.12556335, 11.87239625, 11.87239625, 15.03989724,\n 15.03989724],\n [ 7.10553446, 7.10553446, 11.89905224, 11.89905224, 15.02830298,\n 15.02830298],\n [ 7.08605448, 7.08605448, 11.92515725, 11.92515725, 15.01680429,\n 15.01680429],\n [ 7.06719745, 7.06719745, 11.95060282, 11.95060282, 15.00545792,\n 15.00545792],\n [ 7.0490338 , 7.0490338 , 11.97528226, 11.97528226, 14.994322 ,\n 14.994322 ],\n [ 7.0316303 , 7.0316303 , 11.99909093, 11.99909093, 14.98345578,\n 14.98345578],\n [ 7.01504997, 7.01504997, 12.02192655, 12.02192655, 14.97291925,\n 14.97291925],\n [ 6.99935206, 6.99935206, 12.04368954, 12.04368954, 14.96277273,\n 14.96277273],\n [ 6.98459195, 6.98459195, 12.0642835 , 12.0642835 , 14.9530764 ,\n 14.9530764 ],\n [ 6.97082113, 6.97082113, 12.08361559, 12.08361559, 14.94388978,\n 14.94388978],\n [ 6.95808712, 6.95808712, 12.10159715, 12.10159715, 14.93527117,\n 14.93527117],\n [ 6.94643348, 6.94643348, 12.1181442 , 12.1181442 , 14.92727697,\n 14.92727697],\n [ 6.93589974, 6.93589974, 12.13317811, 12.13317811, 14.91996108,\n 14.91996108],\n [ 6.92652136, 6.92652136, 12.14662617, 12.14662617, 14.91337418,\n 14.91337418],\n [ 6.9183297 , 6.9183297 , 12.15842227, 12.15842227, 14.90756307,\n 14.90756307],\n [ 6.91135203, 6.91135203, 12.16850756, 12.16850756, 14.90256997,\n 14.90256997],\n [ 6.90561144, 6.90561144, 12.17683102, 12.17683102, 14.89843186,\n 14.89843186],\n [ 6.90112687, 6.90112687, 12.18335004, 12.18335004, 14.89517991,\n 14.89517991],\n [ 6.89791305, 6.89791305, 12.18803092, 12.18803092, 14.89283897,\n 14.89283897],\n [ 6.89598055, 6.89598055, 12.19084928, 12.19084928, 14.89142709,\n 14.89142709],\n [ 6.89533567, 6.89533567, 12.19179039, 12.19179039, 14.89095524,\n 14.89095524]])],\n 'eigenvectors': None,\n 'group_velocities': None},\n 'total_dos_dict': {'frequency_points': array([-1.21959488e+00, -1.12531879e+00, -1.03104271e+00, -9.36766620e-01,\n -8.42490534e-01, -7.48214449e-01, -6.53938363e-01, -5.59662277e-01,\n -4.65386192e-01, -3.71110106e-01, -2.76834020e-01, -1.82557935e-01,\n -8.82818488e-02, 5.99423689e-03, 1.00270323e-01, 1.94546408e-01,\n 2.88822494e-01, 3.83098580e-01, 4.77374665e-01, 5.71650751e-01,\n 6.65926837e-01, 7.60202922e-01, 8.54479008e-01, 9.48755094e-01,\n 1.04303118e+00, 1.13730727e+00, 1.23158335e+00, 1.32585944e+00,\n 1.42013552e+00, 1.51441161e+00, 1.60868769e+00, 1.70296378e+00,\n 1.79723987e+00, 1.89151595e+00, 1.98579204e+00, 2.08006812e+00,\n 2.17434421e+00, 2.26862029e+00, 2.36289638e+00, 2.45717246e+00,\n 2.55144855e+00, 2.64572464e+00, 2.74000072e+00, 2.83427681e+00,\n 2.92855289e+00, 3.02282898e+00, 3.11710506e+00, 3.21138115e+00,\n 3.30565724e+00, 3.39993332e+00, 3.49420941e+00, 3.58848549e+00,\n 3.68276158e+00, 3.77703766e+00, 3.87131375e+00, 3.96558984e+00,\n 4.05986592e+00, 4.15414201e+00, 4.24841809e+00, 4.34269418e+00,\n 4.43697026e+00, 4.53124635e+00, 4.62552244e+00, 4.71979852e+00,\n 4.81407461e+00, 4.90835069e+00, 5.00262678e+00, 5.09690286e+00,\n 5.19117895e+00, 5.28545504e+00, 5.37973112e+00, 5.47400721e+00,\n 5.56828329e+00, 5.66255938e+00, 5.75683546e+00, 5.85111155e+00,\n 5.94538764e+00, 6.03966372e+00, 6.13393981e+00, 6.22821589e+00,\n 6.32249198e+00, 6.41676806e+00, 6.51104415e+00, 6.60532024e+00,\n 6.69959632e+00, 6.79387241e+00, 6.88814849e+00, 6.98242458e+00,\n 7.07670066e+00, 7.17097675e+00, 7.26525284e+00, 7.35952892e+00,\n 7.45380501e+00, 7.54808109e+00, 7.64235718e+00, 7.73663326e+00,\n 7.83090935e+00, 7.92518544e+00, 8.01946152e+00, 8.11373761e+00,\n 8.20801369e+00, 8.30228978e+00, 8.39656586e+00, 8.49084195e+00,\n 8.58511804e+00, 8.67939412e+00, 8.77367021e+00, 8.86794629e+00,\n 8.96222238e+00, 9.05649846e+00, 9.15077455e+00, 9.24505064e+00,\n 9.33932672e+00, 9.43360281e+00, 9.52787889e+00, 9.62215498e+00,\n 9.71643106e+00, 9.81070715e+00, 9.90498323e+00, 9.99925932e+00,\n 1.00935354e+01, 1.01878115e+01, 1.02820876e+01, 1.03763637e+01,\n 1.04706397e+01, 1.05649158e+01, 1.06591919e+01, 1.07534680e+01,\n 1.08477441e+01, 1.09420202e+01, 1.10362963e+01, 1.11305723e+01,\n 1.12248484e+01, 1.13191245e+01, 1.14134006e+01, 1.15076767e+01,\n 1.16019528e+01, 1.16962289e+01, 1.17905049e+01, 1.18847810e+01,\n 1.19790571e+01, 1.20733332e+01, 1.21676093e+01, 1.22618854e+01,\n 1.23561615e+01, 1.24504375e+01, 1.25447136e+01, 1.26389897e+01,\n 1.27332658e+01, 1.28275419e+01, 1.29218180e+01, 1.30160941e+01,\n 1.31103701e+01, 1.32046462e+01, 1.32989223e+01, 1.33931984e+01,\n 1.34874745e+01, 1.35817506e+01, 1.36760267e+01, 1.37703027e+01,\n 1.38645788e+01, 1.39588549e+01, 1.40531310e+01, 1.41474071e+01,\n 1.42416832e+01, 1.43359593e+01, 1.44302353e+01, 1.45245114e+01,\n 1.46187875e+01, 1.47130636e+01, 1.48073397e+01, 1.49016158e+01,\n 1.49958919e+01, 1.50901679e+01, 1.51844440e+01, 1.52787201e+01,\n 1.53729962e+01, 1.54672723e+01, 1.55615484e+01, 1.56558245e+01,\n 1.57501005e+01, 1.58443766e+01, 1.59386527e+01, 1.60329288e+01,\n 1.61272049e+01, 1.62214810e+01, 1.63157571e+01, 1.64100331e+01,\n 1.65043092e+01, 1.65985853e+01, 1.66928614e+01, 1.67871375e+01,\n 1.68814136e+01, 1.69756897e+01, 1.70699657e+01, 1.71642418e+01,\n 1.72585179e+01, 1.73527940e+01, 1.74470701e+01, 1.75413462e+01,\n 1.76356223e+01]),\n 'total_dos': array([0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 3.17526949e-04, 1.35171618e-03, 2.50831797e-03,\n 3.78733233e-03, 5.26373813e-03, 6.90328284e-03, 8.78451412e-03,\n 1.08845716e-02, 1.31202482e-02, 1.58239881e-02, 1.84817583e-02,\n 2.14099537e-02, 2.44295300e-02, 2.78000795e-02, 3.14939706e-02,\n 3.52413320e-02, 3.92909859e-02, 4.36423577e-02, 4.83495504e-02,\n 5.31903107e-02, 5.81462801e-02, 6.35669356e-02, 6.94844360e-02,\n 7.55171874e-02, 8.19720137e-02, 8.86760193e-02, 9.58023138e-02,\n 1.03099606e-01, 1.11366958e-01, 1.19969573e-01, 1.28656383e-01,\n 1.38210214e-01, 1.48087177e-01, 1.58993039e-01, 1.70577194e-01,\n 1.82773665e-01, 1.96102840e-01, 2.10318186e-01, 2.25609695e-01,\n 2.42775583e-01, 2.61718244e-01, 2.82966510e-01, 3.07071183e-01,\n 3.35572804e-01, 3.71503640e-01, 4.23538191e-01, 5.01245367e-01,\n 5.06757340e-01, 5.10673514e-01, 5.13884731e-01, 5.18635687e-01,\n 5.22215630e-01, 5.26790868e-01, 5.30317993e-01, 5.33703746e-01,\n 5.38149099e-01, 5.41609848e-01, 5.45017573e-01, 5.48177732e-01,\n 5.52308667e-01, 5.54935999e-01, 5.58609041e-01, 5.61624143e-01,\n 5.64469403e-01, 5.68022742e-01, 5.70890330e-01, 5.72980739e-01,\n 5.77439994e-01, 5.83268678e-01, 5.49870464e-01, 4.81961887e-01,\n 4.49243839e-01, 4.26254220e-01, 4.10187378e-01, 3.95199652e-01,\n 3.98624284e-01, 4.05995249e-01, 4.25103229e-01, 4.54252120e-01,\n 4.65563502e-01, 3.65773926e-01, 2.85541037e-01, 2.23526600e-01,\n 1.44473263e-01, 1.04439534e-01, 1.08917911e-01, 1.13417776e-01,\n 1.18953226e-01, 1.24441198e-01, 1.29621905e-01, 1.36164980e-01,\n 1.42605861e-01, 1.49045426e-01, 1.56851391e-01, 1.64582559e-01,\n 1.72682584e-01, 1.82141611e-01, 1.91321788e-01, 2.02261449e-01,\n 2.13762731e-01, 2.26135950e-01, 2.40393404e-01, 2.55442497e-01,\n 2.74046636e-01, 2.93902607e-01, 3.19085171e-01, 3.48960866e-01,\n 3.91473391e-01, 4.54354038e-01, 5.99226889e-01, 6.56603266e-01,\n 4.43486451e-01, 3.58148235e-01, 2.92612110e-01, 2.34458733e-01,\n 1.57664249e-01, 9.44996839e-02, 7.64989495e-02, 6.21782198e-02,\n 7.46273535e-02, 8.86461614e-02, 1.06333999e-01, 1.36147948e-01,\n 1.87831258e-01, 2.67221370e-01, 2.89615750e-01, 3.09688343e-01,\n 3.30425521e-01, 3.30668402e-01, 3.40062237e-01, 3.45284499e-01,\n 3.55917538e-01, 3.60077500e-01, 3.69186627e-01, 3.71502854e-01,\n 3.72120651e-01, 3.48181936e-01, 3.16317708e-01, 2.98435672e-01,\n 2.84862196e-01, 2.74096441e-01, 2.64721157e-01, 2.56360104e-01,\n 2.48761334e-01, 2.41852996e-01, 2.35018844e-01, 2.28859604e-01,\n 2.22571780e-01, 2.16655364e-01, 2.10807826e-01, 2.04860365e-01,\n 1.99221497e-01, 1.93100666e-01, 1.87355107e-01, 2.53244401e-01,\n 8.43177422e-01, 1.43196664e+00, 3.18170027e+00, 2.79552678e+00,\n 3.13543115e+00, 4.55809708e+00, 2.72396129e+00, 1.52338820e+00,\n 1.06733102e+00, 7.67955185e-01, 5.18138351e-01, 2.28096624e-01,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00,\n 0.00000000e+00])},\n 'dynamical_matrix': array([[ 5.50912534e-01-0.00000000e+00j, 1.87768043e-17-4.38872430e-34j,\n 1.92709307e-17+5.81987920e-18j, -3.23420540e-17+4.98906381e-17j,\n -1.68412801e-30+5.84523400e-17j, -3.95652763e-17-3.56372327e-01j],\n [ 1.87768043e-17+4.38872430e-34j, 6.08181944e-01-0.00000000e+00j,\n -1.56143951e-16-1.15555797e-33j, -7.84788746e-30+5.84523400e-17j,\n -3.23420540e-17+2.45450096e-18j, 4.20932852e-30+1.58872850e-17j],\n [ 1.92709307e-17-5.81987920e-18j, -1.56143951e-16+1.15555797e-33j,\n 5.50912534e-01-0.00000000e+00j, -3.95652763e-17-3.56372327e-01j,\n 8.83023845e-30+1.58872850e-17j, -3.23420540e-17-3.36800318e-19j],\n [-3.23420540e-17-4.98906381e-17j, -7.84788746e-30-5.84523400e-17j,\n -3.95652763e-17+3.56372327e-01j, 5.50912534e-01-0.00000000e+00j,\n -9.24016421e-17-9.32340591e-30j, -8.30132400e-17-1.39858661e-29j],\n [-1.68412801e-30-5.84523400e-17j, -3.23420540e-17-2.45450096e-18j,\n 8.83023845e-30-1.58872850e-17j, -9.24016421e-17+9.32340591e-30j,\n 6.08181944e-01-0.00000000e+00j, -1.49226181e-16+4.66355445e-30j],\n [-3.95652763e-17+3.56372327e-01j, 4.20932852e-30-1.58872850e-17j,\n -3.23420540e-17+3.36800318e-19j, -8.30132400e-17+1.39858661e-29j,\n -1.49226181e-16-4.66355445e-30j, 5.50912534e-01-0.00000000e+00j]]),\n 'force_constants': array([[[[ 1.57151912e+01, 9.62277932e-16, 9.62277932e-16],\n [ 2.01508898e-31, 1.57151912e+01, -3.56057418e-15],\n [-6.31781728e-30, -4.83151945e-15, 1.57151912e+01]],\n \n [[-8.88178420e-13, -2.31481372e-29, -6.32321319e-29],\n [ 8.33886532e-31, 1.11022302e-12, -2.01086934e-28],\n [ 3.91666326e-46, -3.53409686e-28, 1.11022302e-12]],\n \n [[ 1.11022302e-12, 7.59032102e-29, 1.18329136e-28],\n [-1.78078948e-29, -8.88178420e-13, -4.17598292e-28],\n [ 5.04870979e-29, 2.72945873e-28, 1.11022302e-12]],\n \n ...,\n \n [[-6.32890635e-13, 5.20587829e-13, -5.20587829e-13],\n [-1.25573862e-13, -5.61838490e-13, -2.31561886e-13],\n [ 1.25573862e-13, -2.31561886e-13, -5.61838490e-13]],\n \n [[-5.61838490e-13, -1.25573862e-13, -2.31561886e-13],\n [ 5.20587829e-13, -6.32890635e-13, -5.20587829e-13],\n [-2.31561886e-13, 1.25573862e-13, -5.61838490e-13]],\n \n [[-1.15412764e-12, -4.39732284e-13, 3.10095250e-14],\n [-4.39732284e-13, -1.15412764e-12, 3.10095250e-14],\n [ 1.56993370e-13, 1.56993370e-13, -7.37047351e-13]]],\n \n \n [[[-8.88178420e-13, -2.31481372e-29, -6.32321319e-29],\n [ 8.33886532e-31, 1.11022302e-12, -2.01086934e-28],\n [ 1.63734993e-45, -3.53409686e-28, 1.11022302e-12]],\n \n [[ 1.57151912e+01, 9.62277932e-16, 9.62277932e-16],\n [ 2.19141532e-31, 1.57151912e+01, -3.56057418e-15],\n [-6.30018465e-30, -4.83151945e-15, 1.57151912e+01]],\n \n [[ 1.59872116e-12, 7.17863424e-29, 1.13595970e-28],\n [ 2.73057674e-29, 1.59872116e-12, -1.11175775e-27],\n [ 5.04870979e-29, -4.03896783e-28, 4.08562073e-12]],\n \n ...,\n \n [[-3.70859075e+00, -2.50222375e+00, 2.50222375e+00],\n [-2.50222375e+00, -3.70859075e+00, 2.50222375e+00],\n [ 2.50222375e+00, 2.50222375e+00, -3.70859075e+00]],\n \n [[-1.15412764e-12, -4.39732284e-13, 3.10095250e-14],\n [-4.39732284e-13, -1.15412764e-12, 3.10095250e-14],\n [ 1.56993370e-13, 1.56993370e-13, -7.37047351e-13]],\n \n [[-5.61838490e-13, -1.25573862e-13, -2.31561886e-13],\n [ 5.20587829e-13, -6.32890635e-13, -5.20587829e-13],\n [-2.31561886e-13, 1.25573862e-13, -5.61838490e-13]]],\n \n \n [[[ 1.11022302e-12, 7.59032102e-29, 1.18329136e-28],\n [-1.78078948e-29, -8.88178420e-13, -4.17598292e-28],\n [ 5.04870979e-29, 2.72945873e-28, 1.11022302e-12]],\n \n [[ 1.59872116e-12, 7.17863424e-29, 1.13595970e-28],\n [ 2.73057674e-29, 1.59872116e-12, -1.11175775e-27],\n [ 5.04870979e-29, -4.03896783e-28, 4.08562073e-12]],\n \n [[ 1.57151912e+01, 9.62277932e-16, 9.62277932e-16],\n [ 2.19141532e-31, 1.57151912e+01, -3.56057418e-15],\n [-6.30018465e-30, -4.83151945e-15, 1.57151912e+01]],\n \n ...,\n \n [[-1.15412764e-12, -4.39732284e-13, 3.10095250e-14],\n [-4.39732284e-13, -1.15412764e-12, 3.10095250e-14],\n [ 1.56993370e-13, 1.56993370e-13, -7.37047351e-13]],\n \n [[-3.70859075e+00, -2.50222375e+00, 2.50222375e+00],\n [-2.50222375e+00, -3.70859075e+00, 2.50222375e+00],\n [ 2.50222375e+00, 2.50222375e+00, -3.70859075e+00]],\n \n [[-6.32890635e-13, 5.20587829e-13, -5.20587829e-13],\n [-1.25573862e-13, -5.61838490e-13, -2.31561886e-13],\n [ 1.25573862e-13, -2.31561886e-13, -5.61838490e-13]]],\n \n \n ...,\n \n \n [[[-6.32890635e-13, 5.20587829e-13, -5.20587829e-13],\n [-1.25573862e-13, -5.61838490e-13, -2.31561886e-13],\n [ 1.25573862e-13, -2.31561886e-13, -5.61838490e-13]],\n \n [[-3.70859075e+00, -2.50222375e+00, 2.50222375e+00],\n [-2.50222375e+00, -3.70859075e+00, 2.50222375e+00],\n [ 2.50222375e+00, 2.50222375e+00, -3.70859075e+00]],\n \n [[-1.15412764e-12, -4.39732284e-13, 3.10095250e-14],\n [-4.39732284e-13, -1.15412764e-12, 3.10095250e-14],\n [ 1.56993370e-13, 1.56993370e-13, -7.37047351e-13]],\n \n ...,\n \n [[ 1.57151912e+01, -2.88683380e-15, -2.88683380e-15],\n [-1.92455586e-15, 1.57151912e+01, -4.83151945e-15],\n [-1.92455586e-15, -3.56057418e-15, 1.57151912e+01]],\n \n [[ 1.59872116e-12, -2.84139296e-28, -6.91248574e-28],\n [-1.83165100e-28, 1.59872116e-12, -1.36396903e-27],\n [-4.81749809e-28, -2.63475263e-28, 4.08562073e-12]],\n \n [[ 1.11022302e-12, 4.85458861e-29, -1.58051213e-28],\n [ 9.61487114e-29, -8.88178420e-13, -4.50532933e-28],\n [-1.17892900e-28, 2.33671810e-28, 1.11022302e-12]]],\n \n \n [[[-5.61838490e-13, -1.25573862e-13, -2.31561886e-13],\n [ 5.20587829e-13, -6.32890635e-13, -5.20587829e-13],\n [-2.31561886e-13, 1.25573862e-13, -5.61838490e-13]],\n \n [[-1.15412764e-12, -4.39732284e-13, 3.10095250e-14],\n [-4.39732284e-13, -1.15412764e-12, 3.10095250e-14],\n [ 1.56993370e-13, 1.56993370e-13, -7.37047351e-13]],\n \n [[-3.70859075e+00, -2.50222375e+00, 2.50222375e+00],\n [-2.50222375e+00, -3.70859075e+00, 2.50222375e+00],\n [ 2.50222375e+00, 2.50222375e+00, -3.70859075e+00]],\n \n ...,\n \n [[ 1.59872116e-12, -2.84139296e-28, -6.91248574e-28],\n [-1.83165100e-28, 1.59872116e-12, -1.36396903e-27],\n [-4.81749809e-28, -2.63475263e-28, 4.08562073e-12]],\n \n [[ 1.57151912e+01, -2.88683380e-15, -2.88683380e-15],\n [-1.92455586e-15, 1.57151912e+01, -4.83151945e-15],\n [-1.92455586e-15, -3.56057418e-15, 1.57151912e+01]],\n \n [[-8.88178420e-13, -7.27309754e-29, -1.12814970e-28],\n [-1.35963107e-28, 1.11022302e-12, -3.53409686e-28],\n [-1.36796994e-28, -2.01086934e-28, 1.11022302e-12]]],\n \n \n [[[-1.15412764e-12, -4.39732284e-13, 3.10095250e-14],\n [-4.39732284e-13, -1.15412764e-12, 3.10095250e-14],\n [ 1.56993370e-13, 1.56993370e-13, -7.37047351e-13]],\n \n [[-5.61838490e-13, -1.25573862e-13, -2.31561886e-13],\n [ 5.20587829e-13, -6.32890635e-13, -5.20587829e-13],\n [-2.31561886e-13, 1.25573862e-13, -5.61838490e-13]],\n \n [[-6.32890635e-13, 5.20587829e-13, -5.20587829e-13],\n [-1.25573862e-13, -5.61838490e-13, -2.31561886e-13],\n [ 1.25573862e-13, -2.31561886e-13, -5.61838490e-13]],\n \n ...,\n \n [[ 1.11022302e-12, 4.85458861e-29, -1.58051213e-28],\n [ 9.61487114e-29, -8.88178420e-13, -4.50532933e-28],\n [-1.17892900e-28, 2.33671810e-28, 1.11022302e-12]],\n \n [[-8.88178420e-13, -7.27309754e-29, -1.12814970e-28],\n [-1.35963107e-28, 1.11022302e-12, -3.53409686e-28],\n [-1.36796994e-28, -2.01086934e-28, 1.11022302e-12]],\n \n [[ 1.57151912e+01, -2.88683380e-15, -2.88683380e-15],\n [-1.92455586e-15, 1.57151912e+01, -4.83151945e-15],\n [-1.92455586e-15, -3.56057418e-15, 1.57151912e+01]]]])}" + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cell = (\n", + " structure_ase.cell.array,\n", + " structure_ase.get_scaled_positions(),\n", + " structure_ase.numbers,\n", + ")\n", + "primitive_matrix = spglib.standardize_cell(cell=cell, to_primitive=True)[\n", + " 0\n", + "] / structure_ase.get_volume() ** (1 / 3)\n", + "workflow = PhonopyWorkflow(\n", + " structure=structure_ase,\n", + " interaction_range=10,\n", + " factor=VaspToTHz,\n", + " displacement=0.01,\n", + " dos_mesh=20,\n", + " primitive_matrix=primitive_matrix,\n", + " number_of_snapshots=None,\n", + ")\n", + "task_dict = workflow.generate_structures()\n", + "result_dict = evaluate_with_lammps(\n", + " task_dict=task_dict,\n", + " potential_dataframe=potential_dataframe,\n", + ")\n", + "workflow.analyse_structures(output_dict=result_dict)" + ] + }, + { + "cell_type": "markdown", + "id": "9080af2d-65ef-4710-80c3-66fd5bad9a76", + "metadata": {}, + "source": "The calcualtion of the finite temperature phonons starts by computing the molecular dynamics trajectory using the \n`calc_molecular_dynamics_phonons_with_lammps()` function. This function is internally linked to [DynaPhoPy](https://abelcarreras.github.io/DynaPhoPy/)\nto return an `dynaphopy.dynamics.Dynamics` object: " + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "f2aada6d-89de-4fc0-a93d-f6fb43e33e8c", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "trajectory = calc_molecular_dynamics_phonons_with_lammps(\n", + " structure_ase=structure_ase,\n", + " potential_dataframe=potential_dataframe,\n", + " force_constants=workflow.phonopy.get_force_constants(),\n", + " phonopy_unitcell=workflow.phonopy.get_unitcell(),\n", + " phonopy_primitive_matrix=workflow.phonopy.get_primitive_matrix(),\n", + " phonopy_supercell_matrix=workflow.phonopy.get_supercell_matrix(),\n", + " total_time=2, # ps\n", + " time_step=0.001, # ps\n", + " relaxation_time=5, # ps\n", + " silent=True,\n", + " supercell=[2, 2, 2],\n", + " memmap=False,\n", + " velocity_only=True,\n", + " temperature=600,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "5b533910-8e65-4c57-91bc-ccfa1e49d4ce", + "metadata": {}, + "source": "When a total of 2 picoseconds is selected to compute the finite temperature phonons with a timestep of 1 femto second\nthen this results in a total of 2000 molecular dynamics steps. While more molecular dynamics steps result in more precise\npredictions they also require more computational resources. " + }, + { + "cell_type": "markdown", + "id": "58cbd845-ad6e-41e1-b37c-dcc426e110c1", + "metadata": {}, + "source": "The postprocessing is executed using the [DynaPhoPy](https://abelcarreras.github.io/DynaPhoPy/) package: " + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "54169376-3978-4c25-b1d6-509030a4cea7", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "Using 2000 steps\nUsing Fast Fourier transform (Numpy) function\nset frequency range: 0.0 - 21.200000000000003\n\nQ-point: 1 / 32 [ 0.00000 0.00000 0.00000 ]\nHarmonic frequencies (THz):\n[2.18910938e-06 2.19854601e-06 2.20383682e-06 1.60678991e+01\n 1.60678991e+01 1.60678991e+01]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nMD cell size relation: [2 2 2]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\n\nPeak # 1\n----------------------------------------------\nWidth 0.472941 THz\nPosition 0.032545 THz\nArea () (Lorentzian) 0.000000 eV\nArea () (Total) 0.000000 eV\n<|dQ/dt|^2> 0.000000 eV\nOccupation number -0.500000\nFit temperature nan K\nBase line -0.000000 eV * ps\nMaximum height 0.000000 eV * ps\nFitting global error 534601240663.551514\nFrequency shift 0.032543 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.472941 THz\nPosition 0.032545 THz\nArea () (Lorentzian) 0.000000 eV\nArea () (Total) 0.000000 eV\n<|dQ/dt|^2> 0.000000 eV\nOccupation number -0.500000\nFit temperature nan K\nBase line -0.000000 eV * ps\nMaximum height 0.000000 eV * ps\nFitting global error 534601240663.551514\nFrequency shift 0.032543 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.472941 THz\nPosition 0.032545 THz\nArea () (Lorentzian) 0.000000 eV\nArea () (Total) 0.000000 eV\n<|dQ/dt|^2> 0.000000 eV\nOccupation number -0.500000\nFit temperature nan K\nBase line -0.000000 eV * ps\nMaximum height 0.000000 eV * ps\nFitting global error 534601240663.551514\nFrequency shift 0.032543 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.786715 THz\nPosition 15.561772 THz\nArea () (Lorentzian) 0.014497 eV\nArea () (Total) 0.013722 eV\n<|dQ/dt|^2> 0.028993 eV\nOccupation number 2.330539\nFit temperature 332.921392 K\nBase line -0.000016 eV * ps\nMaximum height 0.011731 eV * ps\nFitting global error 0.033291\nFrequency shift -0.506127 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.786715 THz\nPosition 15.561772 THz\nArea () (Lorentzian) 0.014497 eV\nArea () (Total) 0.013722 eV\n<|dQ/dt|^2> 0.028993 eV\nOccupation number 2.330539\nFit temperature 332.921392 K\nBase line -0.000016 eV * ps\nMaximum height 0.011731 eV * ps\nFitting global error 0.033291\nFrequency shift -0.506127 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.786715 THz\nPosition 15.561772 THz\nArea () (Lorentzian) 0.014497 eV\nArea () (Total) 0.013722 eV\n<|dQ/dt|^2> 0.028993 eV\nOccupation number 2.330539\nFit temperature 332.921392 K\nBase line -0.000016 eV * ps\nMaximum height 0.011731 eV * ps\nFitting global error 0.033291\nFrequency shift -0.506127 THz\nFixing gamma point 0 frequencies\n\nQ-point: 2 / 32 [ 0.00000 0.25000 0.25000 ]\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\n\nPeak # 1\n----------------------------------------------\nWidth 0.520799 THz\nPosition 4.512511 THz\nArea () (Lorentzian) 0.018113 eV\nArea () (Total) 0.016786 eV\n<|dQ/dt|^2> 0.036226 eV\nOccupation number 11.696398\nFit temperature 420.145058 K\nBase line -0.000042 eV * ps\nMaximum height 0.022141 eV * ps\nFitting global error 0.016919\nFrequency shift -0.151463 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.520799 THz\nPosition 4.512511 THz\nArea () (Lorentzian) 0.018113 eV\nArea () (Total) 0.016786 eV\n<|dQ/dt|^2> 0.036226 eV\nOccupation number 11.696398\nFit temperature 420.145058 K\nBase line -0.000042 eV * ps\nMaximum height 0.022141 eV * ps\nFitting global error 0.016919\nFrequency shift -0.151463 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.884643 THz\nPosition 6.802090 THz\nArea () (Lorentzian) 0.034381 eV\nArea () (Total) 0.042075 eV\n<|dQ/dt|^2> 0.068762 eV\nOccupation number 14.858240\nFit temperature 797.669964 K\nBase line 0.000413 eV * ps\nMaximum height 0.024742 eV * ps\nFitting global error 0.034947\nFrequency shift -0.096079 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.816224 THz\nPosition 14.710909 THz\nArea () (Lorentzian) 0.050561 eV\nArea () (Total) 0.056117 eV\n<|dQ/dt|^2> 0.101122 eV\nOccupation number 9.943370\nFit temperature 1172.575784 K\nBase line 0.000331 eV * ps\nMaximum height 0.039435 eV * ps\nFitting global error 0.029537\nFrequency shift -0.459579 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.906396 THz\nPosition 15.069443 THz\nArea () (Lorentzian) 0.021839 eV\nArea () (Total) 0.023547 eV\n<|dQ/dt|^2> 0.043678 eV\nOccupation number 3.903565\nFit temperature 504.681860 K\nBase line 0.000115 eV * ps\nMaximum height 0.015339 eV * ps\nFitting global error 0.023072\nFrequency shift -0.486236 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.906396 THz\nPosition 15.069443 THz\nArea () (Lorentzian) 0.021839 eV\nArea () (Total) 0.023547 eV\n<|dQ/dt|^2> 0.043678 eV\nOccupation number 3.903565\nFit temperature 504.681860 K\nBase line 0.000115 eV * ps\nMaximum height 0.015339 eV * ps\nFitting global error 0.023072\nFrequency shift -0.486236 THz\n\nQ-point: 3 / 32 [ 0.00000 0.50000 0.50000 ]\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\n\nPeak # 1\n----------------------------------------------\nWidth 0.579259 THz\nPosition 6.561490 THz\nArea () (Lorentzian) 0.025327 eV\nArea () (Total) 0.027369 eV\n<|dQ/dt|^2> 0.050654 eV\nOccupation number 11.228659\nFit temperature 587.462942 K\nBase line 0.000121 eV * ps\nMaximum height 0.027835 eV * ps\nFitting global error 0.025639\nFrequency shift -0.333845 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.579259 THz\nPosition 6.561490 THz\nArea () (Lorentzian) 0.025327 eV\nArea () (Total) 0.027369 eV\n<|dQ/dt|^2> 0.050654 eV\nOccupation number 11.228659\nFit temperature 587.462942 K\nBase line 0.000121 eV * ps\nMaximum height 0.027835 eV * ps\nFitting global error 0.025639\nFrequency shift -0.333845 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.605260 THz\nPosition 11.933579 THz\nArea () (Lorentzian) 0.030516 eV\nArea () (Total) 0.034730 eV\n<|dQ/dt|^2> 0.061032 eV\nOccupation number 7.270035\nFit temperature 707.271378 K\nBase line 0.000225 eV * ps\nMaximum height 0.032097 eV * ps\nFitting global error 0.023688\nFrequency shift -0.258211 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.605260 THz\nPosition 11.933579 THz\nArea () (Lorentzian) 0.030516 eV\nArea () (Total) 0.034730 eV\n<|dQ/dt|^2> 0.061032 eV\nOccupation number 7.270035\nFit temperature 707.271378 K\nBase line 0.000225 eV * ps\nMaximum height 0.032097 eV * ps\nFitting global error 0.023688\nFrequency shift -0.258211 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.634083 THz\nPosition 14.446261 THz\nArea () (Lorentzian) 0.042334 eV\nArea () (Total) 0.048339 eV\n<|dQ/dt|^2> 0.084669 eV\nOccupation number 8.404323\nFit temperature 981.504236 K\nBase line 0.000327 eV * ps\nMaximum height 0.042504 eV * ps\nFitting global error 0.015367\nFrequency shift -0.444694 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.634083 THz\nPosition 14.446261 THz\nArea () (Lorentzian) 0.042334 eV\nArea () (Total) 0.048339 eV\n<|dQ/dt|^2> 0.084669 eV\nOccupation number 8.404323\nFit temperature 981.504236 K\nBase line 0.000327 eV * ps\nMaximum height 0.042504 eV * ps\nFitting global error 0.015367\nFrequency shift -0.444694 THz\n\nQ-point: 4 / 32 [ 0.00000 0.75000 0.75000 ]\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\n\nPeak # 1\n----------------------------------------------\nWidth 0.513715 THz\nPosition 4.501773 THz\nArea () (Lorentzian) 0.024073 eV\nArea () (Total) 0.021107 eV\n<|dQ/dt|^2> 0.048147 eV\nOccupation number 15.748632\nFit temperature 558.542395 K\nBase line -0.000113 eV * ps\nMaximum height 0.029833 eV * ps\nFitting global error 0.014530\nFrequency shift -0.162201 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.513715 THz\nPosition 4.501773 THz\nArea () (Lorentzian) 0.024073 eV\nArea () (Total) 0.021107 eV\n<|dQ/dt|^2> 0.048147 eV\nOccupation number 15.748632\nFit temperature 558.542395 K\nBase line -0.000113 eV * ps\nMaximum height 0.029833 eV * ps\nFitting global error 0.014530\nFrequency shift -0.162201 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.840450 THz\nPosition 6.833587 THz\nArea () (Lorentzian) 0.047750 eV\nArea () (Total) 0.056965 eV\n<|dQ/dt|^2> 0.095499 eV\nOccupation number 20.731750\nFit temperature 1108.018836 K\nBase line 0.000500 eV * ps\nMaximum height 0.036169 eV * ps\nFitting global error 0.027488\nFrequency shift -0.064582 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.864892 THz\nPosition 14.761576 THz\nArea () (Lorentzian) 0.036911 eV\nArea () (Total) 0.042399 eV\n<|dQ/dt|^2> 0.073823 eV\nOccupation number 7.097870\nFit temperature 855.439740 K\nBase line 0.000312 eV * ps\nMaximum height 0.027169 eV * ps\nFitting global error 0.033172\nFrequency shift -0.408912 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.690963 THz\nPosition 15.047965 THz\nArea () (Lorentzian) 0.029989 eV\nArea () (Total) 0.029744 eV\n<|dQ/dt|^2> 0.059977 eV\nOccupation number 5.555378\nFit temperature 694.419722 K\nBase line 0.000024 eV * ps\nMaximum height 0.027630 eV * ps\nFitting global error 0.016899\nFrequency shift -0.507714 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.690963 THz\nPosition 15.047965 THz\nArea () (Lorentzian) 0.029989 eV\nArea () (Total) 0.029744 eV\n<|dQ/dt|^2> 0.059977 eV\nOccupation number 5.555378\nFit temperature 694.419722 K\nBase line 0.000024 eV * ps\nMaximum height 0.027630 eV * ps\nFitting global error 0.016899\nFrequency shift -0.507714 THz\n\nQ-point: 5 / 32 [ 0.25000 0.00000 0.25000 ]\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nSkipped, equivalent to [0. 0.25 0.25]\n\nQ-point: 6 / 32 [ 0.25000 0.25000 0.50000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\n\nPeak # 1\n----------------------------------------------\nWidth 0.528069 THz\nPosition 4.477183 THz\nArea () (Lorentzian) 0.042227 eV\nArea () (Total) 0.040708 eV\n<|dQ/dt|^2> 0.084453 eV\nOccupation number 28.158070\nFit temperature 979.942696 K\nBase line -0.000024 eV * ps\nMaximum height 0.050907 eV * ps\nFitting global error 0.012211\nFrequency shift -0.190696 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.890764 THz\nPosition 6.695151 THz\nArea () (Lorentzian) 0.080890 eV\nArea () (Total) 0.093342 eV\n<|dQ/dt|^2> 0.161780 eV\nOccupation number 36.211198\nFit temperature 1877.262480 K\nBase line 0.000706 eV * ps\nMaximum height 0.057811 eV * ps\nFitting global error 0.020823\nFrequency shift -0.265939 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.879866 THz\nPosition 8.803246 THz\nArea () (Lorentzian) 0.043886 eV\nArea () (Total) 0.052217 eV\n<|dQ/dt|^2> 0.087772 eV\nOccupation number 14.647678\nFit temperature 1018.178741 K\nBase line 0.000449 eV * ps\nMaximum height 0.031753 eV * ps\nFitting global error 0.028094\nFrequency shift -0.202601 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.757650 THz\nPosition 13.371395 THz\nArea () (Lorentzian) 0.021906 eV\nArea () (Total) 0.026391 eV\n<|dQ/dt|^2> 0.043812 eV\nOccupation number 4.477924\nFit temperature 506.700041 K\nBase line 0.000237 eV * ps\nMaximum height 0.018407 eV * ps\nFitting global error 0.037761\nFrequency shift -0.353521 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.668122 THz\nPosition 14.983805 THz\nArea () (Lorentzian) 0.023784 eV\nArea () (Total) 0.024310 eV\n<|dQ/dt|^2> 0.047568 eV\nOccupation number 4.323155\nFit temperature 550.026025 K\nBase line 0.000052 eV * ps\nMaximum height 0.022663 eV * ps\nFitting global error 0.013903\nFrequency shift -0.442641 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.793991 THz\nPosition 15.147433 THz\nArea () (Lorentzian) 0.067893 eV\nArea () (Total) 0.078771 eV\n<|dQ/dt|^2> 0.135785 eV\nOccupation number 13.119087\nFit temperature 1575.015042 K\nBase line 0.000607 eV * ps\nMaximum height 0.054436 eV * ps\nFitting global error 0.022076\nFrequency shift -0.435323 THz\n\nQ-point: 7 / 32 [ 0.25000 0.50000 0.75000 ]\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\n\nPeak # 1\n----------------------------------------------\nWidth 0.907126 THz\nPosition 7.246330 THz\nArea () (Lorentzian) 0.086024 eV\nArea () (Total) 0.104037 eV\n<|dQ/dt|^2> 0.172047 eV\nOccupation number 35.571453\nFit temperature 1996.396673 K\nBase line 0.000973 eV * ps\nMaximum height 0.060371 eV * ps\nFitting global error 0.020717\nFrequency shift -0.296166 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.907126 THz\nPosition 7.246330 THz\nArea () (Lorentzian) 0.086024 eV\nArea () (Total) 0.104037 eV\n<|dQ/dt|^2> 0.172047 eV\nOccupation number 35.571453\nFit temperature 1996.396673 K\nBase line 0.000973 eV * ps\nMaximum height 0.060371 eV * ps\nFitting global error 0.020717\nFrequency shift -0.296166 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.639111 THz\nPosition 11.064519 THz\nArea () (Lorentzian) 0.021923 eV\nArea () (Total) 0.025269 eV\n<|dQ/dt|^2> 0.043847 eV\nOccupation number 5.520612\nFit temperature 507.650279 K\nBase line 0.000178 eV * ps\nMaximum height 0.021838 eV * ps\nFitting global error 0.024793\nFrequency shift -0.285801 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.639111 THz\nPosition 11.064519 THz\nArea () (Lorentzian) 0.021923 eV\nArea () (Total) 0.025269 eV\n<|dQ/dt|^2> 0.043847 eV\nOccupation number 5.520612\nFit temperature 507.650279 K\nBase line 0.000178 eV * ps\nMaximum height 0.021838 eV * ps\nFitting global error 0.024793\nFrequency shift -0.285801 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.828868 THz\nPosition 14.801411 THz\nArea () (Lorentzian) 0.039716 eV\nArea () (Total) 0.043893 eV\n<|dQ/dt|^2> 0.079432 eV\nOccupation number 7.653201\nFit temperature 920.616703 K\nBase line 0.000252 eV * ps\nMaximum height 0.030504 eV * ps\nFitting global error 0.031513\nFrequency shift -0.436927 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.828868 THz\nPosition 14.801411 THz\nArea () (Lorentzian) 0.039716 eV\nArea () (Total) 0.043893 eV\n<|dQ/dt|^2> 0.079432 eV\nOccupation number 7.653201\nFit temperature 920.616703 K\nBase line 0.000252 eV * ps\nMaximum height 0.030504 eV * ps\nFitting global error 0.031513\nFrequency shift -0.436927 THz\n\nQ-point: 8 / 32 [ 0.25000 0.75000 0.00000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\n\nPeak # 1\n----------------------------------------------\nWidth 0.522556 THz\nPosition 4.483775 THz\nArea () (Lorentzian) 0.037188 eV\nArea () (Total) 0.034635 eV\n<|dQ/dt|^2> 0.074376 eV\nOccupation number 24.701308\nFit temperature 862.984199 K\nBase line -0.000079 eV * ps\nMaximum height 0.045305 eV * ps\nFitting global error 0.012393\nFrequency shift -0.184104 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.898262 THz\nPosition 6.707279 THz\nArea () (Lorentzian) 0.067887 eV\nArea () (Total) 0.079212 eV\n<|dQ/dt|^2> 0.135775 eV\nOccupation number 30.254428\nFit temperature 1575.464581 K\nBase line 0.000635 eV * ps\nMaximum height 0.048114 eV * ps\nFitting global error 0.023773\nFrequency shift -0.253812 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.835420 THz\nPosition 8.803037 THz\nArea () (Lorentzian) 0.013150 eV\nArea () (Total) 0.016324 eV\n<|dQ/dt|^2> 0.026301 eV\nOccupation number 4.039095\nFit temperature 303.968669 K\nBase line 0.000166 eV * ps\nMaximum height 0.010021 eV * ps\nFitting global error 0.059276\nFrequency shift -0.202810 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.730369 THz\nPosition 13.368389 THz\nArea () (Lorentzian) 0.016678 eV\nArea () (Total) 0.021238 eV\n<|dQ/dt|^2> 0.033357 eV\nOccupation number 3.290872\nFit temperature 384.834117 K\nBase line 0.000234 eV * ps\nMaximum height 0.014538 eV * ps\nFitting global error 0.045590\nFrequency shift -0.356527 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.674322 THz\nPosition 14.951363 THz\nArea () (Lorentzian) 0.036155 eV\nArea () (Total) 0.038613 eV\n<|dQ/dt|^2> 0.072311 eV\nOccupation number 6.847775\nFit temperature 837.833762 K\nBase line 0.000157 eV * ps\nMaximum height 0.034134 eV * ps\nFitting global error 0.014619\nFrequency shift -0.475083 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.902049 THz\nPosition 15.073779 THz\nArea () (Lorentzian) 0.021209 eV\nArea () (Total) 0.022490 eV\n<|dQ/dt|^2> 0.042418 eV\nOccupation number 3.775244\nFit temperature 489.986369 K\nBase line 0.000094 eV * ps\nMaximum height 0.014968 eV * ps\nFitting global error 0.022499\nFrequency shift -0.508977 THz\n\nQ-point: 9 / 32 [ 0.50000 0.00000 0.50000 ]\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\nSkipped, equivalent to [0. 0.5 0.5]\n\nQ-point: 10 / 32 [ 0.50000 0.25000 0.75000 ]\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nSkipped, equivalent to [0.25 0.5 0.75]\n\nQ-point: 11 / 32 [ 0.50000 0.50000 0.00000 ]\nHarmonic frequencies (THz):\n[ 6.89533567 6.89533567 12.19179039 12.19179039 14.89095524 14.89095524]\nSkipped, equivalent to [0. 0.5 0.5]\n\nQ-point: 12 / 32 [ 0.50000 0.75000 0.25000 ]\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nSkipped, equivalent to [0.25 0.5 0.75]\n\nQ-point: 13 / 32 [ 0.75000 0.00000 0.75000 ]\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nSkipped, equivalent to [0. 0.75 0.75]\n\nQ-point: 14 / 32 [ 0.75000 0.25000 0.00000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\n\nPeak # 1\n----------------------------------------------\nWidth 0.521991 THz\nPosition 4.484158 THz\nArea () (Lorentzian) 0.036566 eV\nArea () (Total) 0.033926 eV\n<|dQ/dt|^2> 0.073131 eV\nOccupation number 24.277431\nFit temperature 848.537722 K\nBase line -0.000083 eV * ps\nMaximum height 0.044595 eV * ps\nFitting global error 0.012530\nFrequency shift -0.183721 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.899617 THz\nPosition 6.704187 THz\nArea () (Lorentzian) 0.061915 eV\nArea () (Total) 0.071943 eV\n<|dQ/dt|^2> 0.123830 eV\nOccupation number 27.561609\nFit temperature 1436.830957 K\nBase line 0.000565 eV * ps\nMaximum height 0.043814 eV * ps\nFitting global error 0.025259\nFrequency shift -0.256903 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.840794 THz\nPosition 8.777709 THz\nArea () (Lorentzian) 0.009473 eV\nArea () (Total) 0.011919 eV\n<|dQ/dt|^2> 0.018945 eV\nOccupation number 2.779076\nFit temperature 218.134959 K\nBase line 0.000127 eV * ps\nMaximum height 0.007172 eV * ps\nFitting global error 0.078651\nFrequency shift -0.228137 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.814357 THz\nPosition 13.294667 THz\nArea () (Lorentzian) 0.012215 eV\nArea () (Total) 0.016240 eV\n<|dQ/dt|^2> 0.024429 eV\nOccupation number 2.291679\nFit temperature 280.431129 K\nBase line 0.000205 eV * ps\nMaximum height 0.009549 eV * ps\nFitting global error 0.061800\nFrequency shift -0.430249 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.706639 THz\nPosition 14.920962 THz\nArea () (Lorentzian) 0.033379 eV\nArea () (Total) 0.034927 eV\n<|dQ/dt|^2> 0.066758 eV\nOccupation number 6.297384\nFit temperature 773.297146 K\nBase line 0.000113 eV * ps\nMaximum height 0.030072 eV * ps\nFitting global error 0.021423\nFrequency shift -0.505484 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.901748 THz\nPosition 15.110122 THz\nArea () (Lorentzian) 0.021178 eV\nArea () (Total) 0.023049 eV\n<|dQ/dt|^2> 0.042356 eV\nOccupation number 3.758704\nFit temperature 489.249960 K\nBase line 0.000121 eV * ps\nMaximum height 0.014951 eV * ps\nFitting global error 0.028888\nFrequency shift -0.472634 THz\n\nQ-point: 15 / 32 [ 0.75000 0.50000 0.25000 ]\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nSkipped, equivalent to [0.25 0.5 0.75]\n\nQ-point: 16 / 32 [ 0.75000 0.75000 0.50000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\n\nPeak # 1\n----------------------------------------------\nWidth 0.521626 THz\nPosition 4.484270 THz\nArea () (Lorentzian) 0.040369 eV\nArea () (Total) 0.037483 eV\n<|dQ/dt|^2> 0.080738 eV\nOccupation number 26.853838\nFit temperature 936.816651 K\nBase line -0.000091 eV * ps\nMaximum height 0.049268 eV * ps\nFitting global error 0.011912\nFrequency shift -0.183609 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.898998 THz\nPosition 6.706088 THz\nArea () (Lorentzian) 0.060155 eV\nArea () (Total) 0.069989 eV\n<|dQ/dt|^2> 0.120310 eV\nOccupation number 26.756362\nFit temperature 1395.986799 K\nBase line 0.000553 eV * ps\nMaximum height 0.042598 eV * ps\nFitting global error 0.025425\nFrequency shift -0.255003 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.847729 THz\nPosition 8.762397 THz\nArea () (Lorentzian) 0.009423 eV\nArea () (Total) 0.011871 eV\n<|dQ/dt|^2> 0.018846 eV\nOccupation number 2.767683\nFit temperature 216.985862 K\nBase line 0.000127 eV * ps\nMaximum height 0.007077 eV * ps\nFitting global error 0.078128\nFrequency shift -0.243450 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.822505 THz\nPosition 13.296042 THz\nArea () (Lorentzian) 0.012441 eV\nArea () (Total) 0.016789 eV\n<|dQ/dt|^2> 0.024882 eV\nOccupation number 2.343156\nFit temperature 285.744350 K\nBase line 0.000221 eV * ps\nMaximum height 0.009629 eV * ps\nFitting global error 0.060141\nFrequency shift -0.428874 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.692941 THz\nPosition 14.927237 THz\nArea () (Lorentzian) 0.037140 eV\nArea () (Total) 0.038953 eV\n<|dQ/dt|^2> 0.074280 eV\nOccupation number 7.060040\nFit temperature 860.720270 K\nBase line 0.000129 eV * ps\nMaximum height 0.034121 eV * ps\nFitting global error 0.019502\nFrequency shift -0.499209 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.873800 THz\nPosition 15.089642 THz\nArea () (Lorentzian) 0.020289 eV\nArea () (Total) 0.022192 eV\n<|dQ/dt|^2> 0.040578 eV\nOccupation number 3.585462\nFit temperature 468.522604 K\nBase line 0.000120 eV * ps\nMaximum height 0.014782 eV * ps\nFitting global error 0.026540\nFrequency shift -0.493114 THz\n\nQ-point: 17 / 32 [ 0.25000 0.25000 0.00000 ]\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nSkipped, equivalent to [0.25 0. 0.25]\n\nQ-point: 18 / 32 [ 0.25000 0.50000 0.25000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.25 0.25 0.5 ]\n\nQ-point: 19 / 32 [ 0.25000 0.75000 0.50000 ]\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nSkipped, equivalent to [0.25 0.5 0.75]\n\nQ-point: 20 / 32 [ 0.25000 0.00000 0.75000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.75 0.75 0.5 ]\n\nQ-point: 21 / 32 [ 0.50000 0.25000 0.25000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.25 0.5 0.25]\n\nQ-point: 22 / 32 [ 0.50000 0.50000 0.50000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nCalculating phonon projection power spectra\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nProjecting into phonon mode\nProjecting into wave vector\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nPower spectrum resolution requested unavailable, using maximum: 0.500000 THz\nIf you need higher resolution increase the number of data\nFFT: [##############################] 100.00% Done...\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\n\nPeak # 1\n----------------------------------------------\nWidth 0.531374 THz\nPosition 4.473540 THz\nArea () (Lorentzian) 0.029343 eV\nArea () (Total) 0.027597 eV\n<|dQ/dt|^2> 0.058686 eV\nOccupation number 19.430578\nFit temperature 680.883835 K\nBase line -0.000049 eV * ps\nMaximum height 0.035155 eV * ps\nFitting global error 0.015967\nFrequency shift -0.194339 THz\n\nPeak # 2\n----------------------------------------------\nWidth 0.531374 THz\nPosition 4.473540 THz\nArea () (Lorentzian) 0.029343 eV\nArea () (Total) 0.027597 eV\n<|dQ/dt|^2> 0.058686 eV\nOccupation number 19.430578\nFit temperature 680.883835 K\nBase line -0.000049 eV * ps\nMaximum height 0.035155 eV * ps\nFitting global error 0.015967\nFrequency shift -0.194339 THz\n\nPeak # 3\n----------------------------------------------\nWidth 0.538267 THz\nPosition 10.993312 THz\nArea () (Lorentzian) 0.062518 eV\nArea () (Total) 0.058145 eV\n<|dQ/dt|^2> 0.125036 eV\nOccupation number 16.779904\nFit temperature 1450.579488 K\nBase line -0.000158 eV * ps\nMaximum height 0.073941 eV * ps\nFitting global error 0.008088\nFrequency shift -0.317902 THz\n\nPeak # 4\n----------------------------------------------\nWidth 0.776728 THz\nPosition 12.855329 THz\nArea () (Lorentzian) 0.017087 eV\nArea () (Total) 0.019549 eV\n<|dQ/dt|^2> 0.034174 eV\nOccupation number 3.538695\nFit temperature 394.533163 K\nBase line 0.000136 eV * ps\nMaximum height 0.014005 eV * ps\nFitting global error 0.044153\nFrequency shift -0.299509 THz\n\nPeak # 5\n----------------------------------------------\nWidth 0.629022 THz\nPosition 14.951429 THz\nArea () (Lorentzian) 0.062984 eV\nArea () (Total) 0.068437 eV\n<|dQ/dt|^2> 0.125967 eV\nOccupation number 12.300000\nFit temperature 1461.048221 K\nBase line 0.000325 eV * ps\nMaximum height 0.063744 eV * ps\nFitting global error 0.012067\nFrequency shift -0.475017 THz\n\nPeak # 6\n----------------------------------------------\nWidth 0.629022 THz\nPosition 14.951429 THz\nArea () (Lorentzian) 0.062984 eV\nArea () (Total) 0.068437 eV\n<|dQ/dt|^2> 0.125967 eV\nOccupation number 12.300000\nFit temperature 1461.048221 K\nBase line 0.000325 eV * ps\nMaximum height 0.063744 eV * ps\nFitting global error 0.012067\nFrequency shift -0.475017 THz\n\nQ-point: 23 / 32 [ 0.50000 0.75000 0.75000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.25 0. 0.75]\n\nQ-point: 24 / 32 [ 0.50000 0.00000 0.00000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nSkipped, equivalent to [0.5 0.5 0.5]\n\nQ-point: 25 / 32 [ 0.75000 0.25000 0.50000 ]\nHarmonic frequencies (THz):\n[ 7.54249562 7.54249562 11.3503204 11.3503204 15.23833788 15.23833788]\nSkipped, equivalent to [0.25 0.5 0.75]\n\nQ-point: 26 / 32 [ 0.75000 0.50000 0.75000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.25 0. 0.75]\n\nQ-point: 27 / 32 [ 0.75000 0.75000 0.00000 ]\nHarmonic frequencies (THz):\n[ 4.66397327 4.66397327 6.89816884 15.17048811 15.55567884 15.55567884]\nSkipped, equivalent to [0. 0.75 0.75]\n\nQ-point: 28 / 32 [ 0.75000 0.00000 0.25000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.75 0.5 0.75]\n\nQ-point: 29 / 32 [ 0.00000 0.25000 0.75000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.75 0.5 0.75]\n\nQ-point: 30 / 32 [ 0.00000 0.50000 0.00000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nSkipped, equivalent to [0.5 0.5 0.5]\n\nQ-point: 31 / 32 [ 0.00000 0.75000 0.25000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 6.96109048 9.00584683 13.72491589 15.42644585 15.58275543]\nSkipped, equivalent to [0.75 0.5 0.75]\n\nQ-point: 32 / 32 [ 0.00000 0.00000 0.50000 ]\nHarmonic frequencies (THz):\n[ 4.66787904 4.66787904 11.31121369 13.15483786 15.42644585 15.42644585]\nSkipped, equivalent to [0.5 0.5 0.5]\n" + }, + { + "data": { + "text/plain": "array([[[[ 1.47903370e+01, -7.27856464e-04, 8.95058148e-04],\n [-7.27856464e-04, 1.47903370e+01, 8.95058148e-04],\n [ 8.95058148e-04, 8.95058148e-04, 1.47889684e+01]],\n\n [[-8.53720262e-03, 7.27856464e-04, -8.95058148e-04],\n [ 7.27856464e-04, 7.22093450e-03, 8.95058148e-04],\n [-8.95058148e-04, 8.95058148e-04, 8.58955541e-03]],\n\n [[ 7.22093450e-03, 7.27856464e-04, 8.95058148e-04],\n [ 7.27856464e-04, -8.53720262e-03, -8.95058148e-04],\n [ 8.95058148e-04, -8.95058148e-04, 8.58955541e-03]],\n\n ...,\n\n [[-4.44967060e-03, 1.03899911e-04, -2.92254418e-03],\n [ 1.03899911e-04, 3.86955298e-03, 9.18164273e-03],\n [-2.92254418e-03, 9.18164273e-03, 2.64253878e-03]],\n\n [[ 3.86955298e-03, 1.03899911e-04, 9.18164273e-03],\n [ 1.03899911e-04, -4.44967060e-03, -2.92254418e-03],\n [ 9.18164273e-03, -2.92254418e-03, 2.64253878e-03]],\n\n [[ 4.35320043e-03, -8.69200588e-04, 7.43830393e-03],\n [-8.69200588e-04, 4.35320043e-03, 7.43830393e-03],\n [ 7.43830393e-03, 7.43830393e-03, 1.98168743e-03]]],\n\n\n [[[-8.53720262e-03, 7.27856464e-04, -8.95058148e-04],\n [ 7.27856464e-04, 7.22093450e-03, 8.95058148e-04],\n [-8.95058148e-04, 8.95058148e-04, 8.58955541e-03]],\n\n [[ 1.47903370e+01, -7.27856464e-04, 8.95058148e-04],\n [-7.27856464e-04, 1.47903370e+01, 8.95058148e-04],\n [ 8.95058148e-04, 8.95058148e-04, 1.47889684e+01]],\n\n [[ 5.72248779e-03, -7.27856464e-04, -8.95058148e-04],\n [-7.27856464e-04, 5.72248779e-03, -8.95058148e-04],\n [-8.95058148e-04, -8.95058148e-04, 1.30276827e-02]],\n\n ...,\n\n [[-3.48139117e+00, -2.36186546e+00, 2.36468410e+00],\n [-2.36186546e+00, -3.48139117e+00, 2.36468410e+00],\n [ 2.36468410e+00, 2.36468410e+00, -3.48016416e+00]],\n\n [[ 4.35320043e-03, -8.69200588e-04, 7.43830393e-03],\n [-8.69200588e-04, 4.35320043e-03, 7.43830393e-03],\n [ 7.43830393e-03, 7.43830393e-03, 1.98168743e-03]],\n\n [[ 3.86955298e-03, 1.03899911e-04, 9.18164273e-03],\n [ 1.03899911e-04, -4.44967060e-03, -2.92254418e-03],\n [ 9.18164273e-03, -2.92254418e-03, 2.64253878e-03]]],\n\n\n [[[ 7.22093450e-03, 7.27856464e-04, 8.95058148e-04],\n [ 7.27856464e-04, -8.53720262e-03, -8.95058148e-04],\n [ 8.95058148e-04, -8.95058148e-04, 8.58955541e-03]],\n\n [[ 5.72248779e-03, -7.27856464e-04, -8.95058148e-04],\n [-7.27856464e-04, 5.72248779e-03, -8.95058148e-04],\n [-8.95058148e-04, -8.95058148e-04, 1.30276827e-02]],\n\n [[ 1.47903370e+01, -7.27856464e-04, 8.95058148e-04],\n [-7.27856464e-04, 1.47903370e+01, 8.95058148e-04],\n [ 8.95058148e-04, 8.95058148e-04, 1.47889684e+01]],\n\n ...,\n\n [[ 4.35320043e-03, -8.69200588e-04, 7.43830393e-03],\n [-8.69200588e-04, 4.35320043e-03, 7.43830393e-03],\n [ 7.43830393e-03, 7.43830393e-03, 1.98168743e-03]],\n\n [[-3.48139117e+00, -2.36186546e+00, 2.36468410e+00],\n [-2.36186546e+00, -3.48139117e+00, 2.36468410e+00],\n [ 2.36468410e+00, 2.36468410e+00, -3.48016416e+00]],\n\n [[-4.44967060e-03, 1.03899911e-04, -2.92254418e-03],\n [ 1.03899911e-04, 3.86955298e-03, 9.18164273e-03],\n [-2.92254418e-03, 9.18164273e-03, 2.64253878e-03]]],\n\n\n ...,\n\n\n [[[-4.44967060e-03, 1.03899911e-04, -2.92254418e-03],\n [ 1.03899911e-04, 3.86955298e-03, 9.18164273e-03],\n [-2.92254418e-03, 9.18164273e-03, 2.64253878e-03]],\n\n [[-3.48139117e+00, -2.36186546e+00, 2.36468410e+00],\n [-2.36186546e+00, -3.48139117e+00, 2.36468410e+00],\n [ 2.36468410e+00, 2.36468410e+00, -3.48016416e+00]],\n\n [[ 4.35320043e-03, -8.69200588e-04, 7.43830393e-03],\n [-8.69200588e-04, 4.35320043e-03, 7.43830393e-03],\n [ 7.43830393e-03, 7.43830393e-03, 1.98168743e-03]],\n\n ...,\n\n [[ 1.47903370e+01, -7.27856464e-04, 8.95058148e-04],\n [-7.27856464e-04, 1.47903370e+01, 8.95058148e-04],\n [ 8.95058148e-04, 8.95058148e-04, 1.47889684e+01]],\n\n [[ 5.72248779e-03, -7.27856464e-04, -8.95058148e-04],\n [-7.27856464e-04, 5.72248779e-03, -8.95058148e-04],\n [-8.95058148e-04, -8.95058148e-04, 1.30276827e-02]],\n\n [[ 7.22093450e-03, 7.27856464e-04, 8.95058148e-04],\n [ 7.27856464e-04, -8.53720262e-03, -8.95058148e-04],\n [ 8.95058148e-04, -8.95058148e-04, 8.58955541e-03]]],\n\n\n [[[ 3.86955298e-03, 1.03899911e-04, 9.18164273e-03],\n [ 1.03899911e-04, -4.44967060e-03, -2.92254418e-03],\n [ 9.18164273e-03, -2.92254418e-03, 2.64253878e-03]],\n\n [[ 4.35320043e-03, -8.69200588e-04, 7.43830393e-03],\n [-8.69200588e-04, 4.35320043e-03, 7.43830393e-03],\n [ 7.43830393e-03, 7.43830393e-03, 1.98168743e-03]],\n\n [[-3.48139117e+00, -2.36186546e+00, 2.36468410e+00],\n [-2.36186546e+00, -3.48139117e+00, 2.36468410e+00],\n [ 2.36468410e+00, 2.36468410e+00, -3.48016416e+00]],\n\n ...,\n\n [[ 5.72248779e-03, -7.27856464e-04, -8.95058148e-04],\n [-7.27856464e-04, 5.72248779e-03, -8.95058148e-04],\n [-8.95058148e-04, -8.95058148e-04, 1.30276827e-02]],\n\n [[ 1.47903370e+01, -7.27856464e-04, 8.95058148e-04],\n [-7.27856464e-04, 1.47903370e+01, 8.95058148e-04],\n [ 8.95058148e-04, 8.95058148e-04, 1.47889684e+01]],\n\n [[-8.53720262e-03, 7.27856464e-04, -8.95058148e-04],\n [ 7.27856464e-04, 7.22093450e-03, 8.95058148e-04],\n [-8.95058148e-04, 8.95058148e-04, 8.58955541e-03]]],\n\n\n [[[ 4.35320043e-03, -8.69200588e-04, 7.43830393e-03],\n [-8.69200588e-04, 4.35320043e-03, 7.43830393e-03],\n [ 7.43830393e-03, 7.43830393e-03, 1.98168743e-03]],\n\n [[ 3.86955298e-03, 1.03899911e-04, 9.18164273e-03],\n [ 1.03899911e-04, -4.44967060e-03, -2.92254418e-03],\n [ 9.18164273e-03, -2.92254418e-03, 2.64253878e-03]],\n\n [[-4.44967060e-03, 1.03899911e-04, -2.92254418e-03],\n [ 1.03899911e-04, 3.86955298e-03, 9.18164273e-03],\n [-2.92254418e-03, 9.18164273e-03, 2.64253878e-03]],\n\n ...,\n\n [[ 7.22093450e-03, 7.27856464e-04, 8.95058148e-04],\n [ 7.27856464e-04, -8.53720262e-03, -8.95058148e-04],\n [ 8.95058148e-04, -8.95058148e-04, 8.58955541e-03]],\n\n [[-8.53720262e-03, 7.27856464e-04, -8.95058148e-04],\n [ 7.27856464e-04, 7.22093450e-03, 8.95058148e-04],\n [-8.95058148e-04, 8.95058148e-04, 8.58955541e-03]],\n\n [[ 1.47903370e+01, -7.27856464e-04, 8.95058148e-04],\n [-7.27856464e-04, 1.47903370e+01, 8.95058148e-04],\n [ 8.95058148e-04, 8.95058148e-04, 1.47889684e+01]]]])" + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "calculation = Quasiparticle(trajectory)\n", + "calculation.select_power_spectra_algorithm(2) # select FFT algorithm\n", + "calculation.get_renormalized_phonon_dispersion_bands()\n", + "renormalized_force_constants = (\n", + " calculation.get_renormalized_force_constants().get_array()\n", + ")\n", + "renormalized_force_constants" + ] + }, + { + "cell_type": "markdown", + "id": "2eb26d68-9d7e-45de-9b97-013a8e7e11bb", + "metadata": {}, + "source": "It calculates the re-normalized force constants which can then be used to calculate the finite temperature properties. " + }, + { + "cell_type": "markdown", + "id": "30bdcd29-a41b-4781-a2cd-6af0ba290883", + "metadata": {}, + "source": "In addition the [DynaPhoPy](https://abelcarreras.github.io/DynaPhoPy/) package can be used to directly compare the \nfinite temperature phonon spectrum with the 0K phonon spectrum calulated with the finite displacement method: " + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "8d8239ad-30eb-4f7a-a5aa-91e5030fa74d", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": "
" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "calculation.plot_renormalized_phonon_dispersion_bands()" + ] + }, + { + "cell_type": "markdown", + "id": "c5bada5c-706c-4d5c-9141-1d6bd146d445", + "metadata": {}, + "source": "### Langevin Thermostat \nIn addition to the molecular dynamics implemented in the LAMMPS simulation code, the `atomistics` package also provides\nthe `LangevinWorkflow` which implements molecular dynamics independent of the specific simulation code. \n" + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "fa69a7f8-940a-4fb9-aae3-1ac68d4255f2", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import evaluate_with_lammps_library, get_potential_by_name\n", + "from atomistics.workflows import LangevinWorkflow\n", + "from pylammpsmpi import LammpsASELibrary\n", + "\n", + "steps = 300\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "workflow = LangevinWorkflow(\n", + " structure=bulk(\"Al\", cubic=True).repeat([2, 2, 2]),\n", + " temperature=1000.0,\n", + " overheat_fraction=2.0,\n", + " damping_timescale=100.0,\n", + " time_step=1,\n", + ")\n", + "lmp = LammpsASELibrary(\n", + " working_directory=None,\n", + " cores=1,\n", + " comm=None,\n", + " logger=None,\n", + " log_file=None,\n", + " library=None,\n", + " diable_log_file=True,\n", + ")\n", + "eng_pot_lst, eng_kin_lst = [], []\n", + "for i in range(steps):\n", + " task_dict = workflow.generate_structures()\n", + " result_dict = evaluate_with_lammps_library(\n", + " task_dict=task_dict,\n", + " potential_dataframe=potential_dataframe,\n", + " lmp=lmp,\n", + " )\n", + " eng_pot, eng_kin = workflow.analyse_structures(output_dict=result_dict)\n", + " eng_pot_lst.append(eng_pot)\n", + " eng_kin_lst.append(eng_kin)\n", + "lmp.close()" + ] + }, + { + "cell_type": "markdown", + "id": "d77f71c6-7afd-496d-a3bf-db517623d159", + "metadata": {}, + "source": "The advantage of this implementation is that the user can directly interact with the simulation between the individual\nmolecular dynamics simulation steps. This provides a lot of flexibility to prototype new simulation methods. The input\nparameters of the `LangevinWorkflow` are:\n\n* `structure` the `ase.atoms.Atoms` object which is used as initial structure for the molecular dynamics calculation \n* `temperature` the temperature of the molecular dynamics calculation given in Kelvin\n* `overheat_fraction` the over heating fraction of the Langevin thermostat\n* `damping_timescale` the damping timescale of the Langevin thermostat \n* `time_step` the time steps of the Langevin thermostat\n" + }, + { + "cell_type": "markdown", + "id": "6944d8c5-718d-4d87-956c-d456c151c331", + "metadata": {}, + "source": "## Harmonic Approximation \nThe harmonic approximation is implemented in two variations, once with constant volume and once including the volume \nexpansion at finite temperature also known as quasi-harmonic approximation. Both of these are based on the [phonopy](https://phonopy.github.io/phonopy/)\npackage. " + }, + { + "cell_type": "markdown", + "id": "4f699026-d1a8-47a3-b354-6c8572550a50", + "metadata": {}, + "source": "### Phonons \nTo calculate the phonons at a fixed volume the `PhonopyWorkflow` is used:" + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "7ac74f80-d613-4a96-b841-5a2973b949a9", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import evaluate_with_lammps, get_potential_by_name\n", + "from atomistics.workflows import PhonopyWorkflow\n", + "from phonopy.units import VaspToTHz\n", + "\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "workflow = PhonopyWorkflow(\n", + " structure=bulk(\"Al\", cubic=True),\n", + " interaction_range=10,\n", + " factor=VaspToTHz,\n", + " displacement=0.01,\n", + " dos_mesh=20,\n", + " primitive_matrix=None,\n", + " number_of_snapshots=None,\n", + ")\n", + "task_dict = workflow.generate_structures()\n", + "result_dict = evaluate_with_lammps(\n", + " task_dict=task_dict,\n", + " potential_dataframe=potential_dataframe,\n", + ")\n", + "phonopy_dict = workflow.analyse_structures(output_dict=result_dict)" + ] + }, + { + "cell_type": "markdown", + "id": "0528bcb2-55ea-4df0-a0b6-71c99dbd9f57", + "metadata": {}, + "source": "The `PhonopyWorkflow` takes the following inputs: \n\n* `structure` the `ase.atoms.Atoms` object to calculate the phonon spectrum\n* `interaction_range` the cutoff radius to consider for identifying the interaction between the atoms\n* `factor` conversion factor, typically just `phonopy.units.VaspToTHz` \n* `displacement` displacement to calculate the forces \n* `dos_mesh` mesh for the density of states \n* `primitive_matrix` primitive matrix\n* `number_of_snapshots` number of snapshots to calculate\n\nIn addition to the phonon properties, the `PhonopyWorkflow` also enables the calculation of thermal properties: " + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "467a9752-e842-43ef-9233-96663b7086dd", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "{'temperatures': array([1.000e+00, 5.100e+01, 1.010e+02, 1.510e+02, 2.010e+02, 2.510e+02,\n 3.010e+02, 3.510e+02, 4.010e+02, 4.510e+02, 5.010e+02, 5.510e+02,\n 6.010e+02, 6.510e+02, 7.010e+02, 7.510e+02, 8.010e+02, 8.510e+02,\n 9.010e+02, 9.510e+02, 1.001e+03, 1.051e+03, 1.101e+03, 1.151e+03,\n 1.201e+03, 1.251e+03, 1.301e+03, 1.351e+03, 1.401e+03, 1.451e+03,\n 1.501e+03]), 'volumes': array([66.430125, 66.430125, 66.430125, 66.430125, 66.430125, 66.430125,\n 66.430125, 66.430125, 66.430125, 66.430125, 66.430125, 66.430125,\n 66.430125, 66.430125, 66.430125, 66.430125, 66.430125, 66.430125,\n 66.430125, 66.430125, 66.430125, 66.430125, 66.430125, 66.430125,\n 66.430125, 66.430125, 66.430125, 66.430125, 66.430125, 66.430125,\n 66.430125]), 'free_energy': array([ 0.14914132, 0.14837894, 0.13954171, 0.11738723, 0.08264779,\n 0.03712237, -0.01759836, -0.08025513, -0.14986079, -0.22563203,\n -0.30693668, -0.39325592, -0.48415731, -0.57927552, -0.67829812,\n -0.78095507, -0.88701079, -0.99625805, -1.10851315, -1.22361223,\n -1.3414082 , -1.46176834, -1.58457228, -1.70971039, -1.8370824 ,\n -1.96659625, -2.09816715, -2.23171671, -2.3671723 , -2.5044664 ,\n -2.64353611]), 'entropy': array([1.10364016e-08, 5.98829810e+00, 2.96478195e+01, 5.54593816e+01,\n 7.80099308e+01, 9.71787932e+01, 1.13608521e+02, 1.27894607e+02,\n 1.40492150e+02, 1.51738264e+02, 1.61883985e+02, 1.71119149e+02,\n 1.79589851e+02, 1.87410480e+02, 1.94672040e+02, 2.01447985e+02,\n 2.07798389e+02, 2.13772961e+02, 2.19413270e+02, 2.24754417e+02,\n 2.29826293e+02, 2.34654555e+02, 2.39261386e+02, 2.43666089e+02,\n 2.47885561e+02, 2.51934678e+02, 2.55826598e+02, 2.59573021e+02,\n 2.63184393e+02, 2.66670075e+02, 2.70038493e+02]), 'heat_capacity': array([1.78544597e-07, 1.73410821e+01, 5.37349237e+01, 7.35976295e+01,\n 8.34733324e+01, 8.87978444e+01, 9.19287453e+01, 9.39060819e+01,\n 9.52277477e+01, 9.61520364e+01, 9.68225162e+01, 9.73237288e+01,\n 9.77079209e+01, 9.80087218e+01, 9.82485402e+01, 9.84427587e+01,\n 9.86022130e+01, 9.87347097e+01, 9.88459861e+01, 9.89403338e+01,\n 9.90210141e+01, 9.90905402e+01, 9.91508741e+01, 9.92035655e+01,\n 9.92498509e+01, 9.92907269e+01, 9.93270039e+01, 9.93593459e+01,\n 9.93883017e+01, 9.94143276e+01, 9.94378055e+01])}\n" + } + ], + "source": [ + "tp_dict = workflow.get_thermal_properties(\n", + " t_min=1,\n", + " t_max=1500,\n", + " t_step=50,\n", + " temperatures=None,\n", + " cutoff_frequency=None,\n", + " pretend_real=False,\n", + " band_indices=None,\n", + " is_projection=False,\n", + ")\n", + "print(tp_dict)" + ] + }, + { + "cell_type": "markdown", + "id": "d8c4ac48-293a-45f9-bf77-cca3cc275e52", + "metadata": {}, + "source": "The calculation of the thermal properties takes additional inputs: \n\n* `t_min` minimum temperature\n* `t_max` maximum temperature\n* `t_step` temperature step \n* `temperatures` alternative to `t_min`, `t_max` and `t_step` the array of temperatures can be defined directly\n* `cutoff_frequency` cutoff frequency to exclude the contributions of frequencies below a certain cut off\n* `pretend_real` use the absolute values of the phonon frequencies\n* `band_indices` select bands based on their indices \n* `is_projection` multiplies the squared eigenvectors - not recommended\n\nFurthermore, also the dynamical matrix can be directly calculated with the `PhonopyWorkflow`:\n" + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "0856938b-b1cd-40ce-95b7-4605f10ee7a4", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "array([[ 1.72794621e-01, 6.42929783e-20, -6.22838227e-20,\n -1.55150365e-18, 1.42759084e-35, -1.50515236e-19,\n 4.11475061e-18, 4.82197337e-20, 9.98736570e-02,\n 8.87128656e-18, -1.02675017e-33, -1.50493730e-19],\n [ 6.42929783e-20, 1.40379905e-01, 6.83112895e-20,\n 2.05216191e-35, 8.80589092e-18, 1.94854949e-33,\n 1.60732446e-20, 1.02868765e-18, -1.60732446e-20,\n -1.10192213e-34, 8.80589092e-18, 2.23061078e-36],\n [-6.22838227e-20, 6.83112895e-20, 1.72794621e-01,\n -1.50493730e-19, 1.25694783e-34, 8.87128656e-18,\n 9.98736570e-02, 3.21464892e-20, 0.00000000e+00,\n -1.50515236e-19, 1.47219713e-35, -1.55150365e-18],\n [-1.55150365e-18, 2.05216191e-35, -1.50493730e-19,\n 1.72794621e-01, -6.63021339e-20, 6.42929783e-20,\n 8.87128656e-18, -1.03065371e-33, -1.50493730e-19,\n 1.85163778e-17, 8.03662229e-20, 9.98736570e-02],\n [ 1.42759084e-35, 8.80589092e-18, 1.25694783e-34,\n -6.63021339e-20, 1.40379905e-01, 6.42929783e-20,\n -2.28392231e-33, 8.80589092e-18, 2.67635707e-36,\n 0.00000000e+00, 0.00000000e+00, -1.60732446e-20],\n [-1.50515236e-19, 1.94854949e-33, 8.87128656e-18,\n 6.42929783e-20, 6.42929783e-20, 1.72794621e-01,\n -1.50515236e-19, -4.46122155e-37, -1.55150365e-18,\n 9.98736570e-02, 0.00000000e+00, -1.85163778e-17],\n [ 4.11475061e-18, 1.60732446e-20, 9.98736570e-02,\n 8.87128656e-18, -2.28392231e-33, -1.50515236e-19,\n 1.72794621e-01, 6.63021339e-20, -6.42929783e-20,\n -1.55150365e-18, 6.24500783e-36, -1.50493730e-19],\n [ 4.82197337e-20, 1.02868765e-18, 3.21464892e-20,\n -1.03065371e-33, 8.80589092e-18, -4.46122155e-37,\n 6.63021339e-20, 1.40379905e-01, 6.83112895e-20,\n 1.07069317e-35, 8.80589092e-18, -6.89481791e-34],\n [ 9.98736570e-02, -1.60732446e-20, 0.00000000e+00,\n -1.50493730e-19, 2.67635707e-36, -1.55150365e-18,\n -6.42929783e-20, 6.83112895e-20, 1.72794621e-01,\n -1.50515236e-19, 1.81950725e-33, 8.87128656e-18],\n [ 8.87128656e-18, -1.10192213e-34, -1.50515236e-19,\n 1.85163778e-17, 0.00000000e+00, 9.98736570e-02,\n -1.55150365e-18, 1.07069317e-35, -1.50515236e-19,\n 1.72794621e-01, 6.42929783e-20, -6.22838227e-20],\n [-1.02675017e-33, 8.80589092e-18, 1.47219713e-35,\n 8.03662229e-20, 0.00000000e+00, 0.00000000e+00,\n 6.24500783e-36, 8.80589092e-18, 1.81950725e-33,\n 6.42929783e-20, 1.40379905e-01, 6.83112895e-20],\n [-1.50493730e-19, 2.23061078e-36, -1.55150365e-18,\n 9.98736570e-02, -1.60732446e-20, -1.85163778e-17,\n -1.50493730e-19, -6.89481791e-34, 8.87128656e-18,\n -6.22838227e-20, 6.83112895e-20, 1.72794621e-01]])" + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mat = workflow.get_dynamical_matrix()\n", + "mat" + ] + }, + { + "cell_type": "markdown", + "id": "93bc3fbe-fe43-42d4-aaf9-12ef9994e923", + "metadata": {}, + "source": "Or alternatively the hesse matrix:" + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "c3154b6d-50c1-4327-b7cc-00f48b31fd37", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "array([[ 4.50127147e-02, -1.92714960e-33, 8.52306995e-33, ...,\n -6.63514216e-05, 8.82979633e-06, 5.93920137e-05],\n [-5.07378488e-34, 4.50127147e-02, 5.07378488e-34, ...,\n 8.82979633e-06, -6.63514216e-05, 5.93920137e-05],\n [ 5.07378488e-34, -5.07378488e-34, 4.50127147e-02, ...,\n 5.93659141e-05, 5.93659141e-05, 1.73512126e-05],\n ...,\n [-6.63514216e-05, 8.82979633e-06, 5.93920137e-05, ...,\n 4.50127147e-02, -1.92714960e-33, 8.52306995e-33],\n [ 8.82979633e-06, -6.63514216e-05, 5.93920137e-05, ...,\n -5.07378488e-34, 4.50127147e-02, 5.07378488e-34],\n [ 5.93659141e-05, 5.93659141e-05, 1.73512126e-05, ...,\n 5.07378488e-34, -5.07378488e-34, 4.50127147e-02]])" + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mat = workflow.get_hesse_matrix()\n", + "mat" + ] + }, + { + "cell_type": "markdown", + "id": "ebc0a064-af95-42e4-854e-67bdb1065ac6", + "metadata": {}, + "source": "Finally, also the function to calculate the band structure is directly available on the `PhonopyWorkflow`: " + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "a9655fa5-bf39-47f2-ae30-0450b40bf252", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "band_structure = workflow.get_band_structure(\n", + " npoints=101, with_eigenvectors=False, with_group_velocities=False\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "e8d2dcce-a5c6-4301-8c0e-bf0ca11043e9", + "metadata": {}, + "source": "This band structure can also be visualised using the built-in plotting function: " + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "4ad1f1e4-9496-4e99-afa0-fd67c72c26f4", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "" + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": "
" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "workflow.plot_band_structure()" + ] + }, + { + "cell_type": "markdown", + "id": "ae251474-875a-4af2-9290-74e9785490cd", + "metadata": {}, + "source": "Just like the desnsity of states which can be plotted using:" + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "82da60b3-3930-4ff1-879e-65895112aecb", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "" + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": "
" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "workflow.plot_dos()" + ] + }, + { + "cell_type": "markdown", + "id": "93e6fb35-cc50-4235-9885-406c41c6a486", + "metadata": {}, + "source": "### Quasi-harmonic Approximation \nTo include the volume expansion with finite temperature the `atomistics` package implements the `QuasiHarmonicWorkflow`:" + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "9387e3aa-b349-49a9-b7b9-0ac1d7f209d5", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import evaluate_with_lammps, get_potential_by_name\n", + "from atomistics.workflows import QuasiHarmonicWorkflow\n", + "\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "workflow = QuasiHarmonicWorkflow(\n", + " structure=bulk(\"Al\", cubic=True),\n", + " num_points=11,\n", + " vol_range=0.05,\n", + " interaction_range=10,\n", + " factor=VaspToTHz,\n", + " displacement=0.01,\n", + " dos_mesh=20,\n", + " primitive_matrix=None,\n", + " number_of_snapshots=None,\n", + ")\n", + "task_dict = workflow.generate_structures()\n", + "result_dict = evaluate_with_lammps(\n", + " task_dict=task_dict,\n", + " potential_dataframe=potential_dataframe,\n", + ")\n", + "fit_dict = workflow.analyse_structures(output_dict=result_dict)" + ] + }, + { + "cell_type": "markdown", + "id": "b5167f8d-c90f-4bf0-a7c0-fd4dfdd35667", + "metadata": {}, + "source": "The `QuasiHarmonicWorkflow` is a combination of the `EnergyVolumeCurveWorkflow` and the `PhonopyWorkflow`. Consequently, \nthe inputs are a superset of the inputs of these two workflows. " + }, + { + "cell_type": "markdown", + "id": "169ddaf9-7f5d-4126-babf-9f2de3793128", + "metadata": {}, + "source": "Based on the `QuasiHarmonicWorkflow` the thermal properties can be calculated:" + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "07cc0818-15a8-4508-ba97-c3a95eaa72b1", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "{'temperatures': array([1.000e+00, 5.100e+01, 1.010e+02, 1.510e+02, 2.010e+02, 2.510e+02,\n 3.010e+02, 3.510e+02, 4.010e+02, 4.510e+02, 5.010e+02, 5.510e+02,\n 6.010e+02, 6.510e+02, 7.010e+02, 7.510e+02, 8.010e+02, 8.510e+02,\n 9.010e+02, 9.510e+02, 1.001e+03, 1.051e+03, 1.101e+03, 1.151e+03,\n 1.201e+03, 1.251e+03, 1.301e+03, 1.351e+03, 1.401e+03, 1.451e+03,\n 1.501e+03]), 'volumes': [66.71710763927429, 66.7217721669909, 66.7588030456557, 66.82252047263532, 66.89849494958942, 66.9796340113892, 67.06260790999332, 67.14571406293086, 67.22800412575396, 67.30891433769602, 67.38809533263267, 67.46532691223801, 67.54047194450261, 67.61344961442688, 67.68421888050003, 67.7527676376025, 67.81910525012583, 67.88325718224746, 67.94526099996934, 68.00516331349996, 68.06301739227649, 68.11888127927111, 68.1728162874363, 68.22488579579438, 68.27515428480372, 68.32368656530063, 68.3705471654382, 68.41579984727981, 68.45950723009813, 68.50173050155158, 68.54252920118272], 'free_energy': array([ 0.14903662, 0.14826796, 0.13934608, 0.1169922 , 0.08193524,\n 0.03597463, -0.01929655, -0.08261538, -0.15299036, -0.22963345,\n -0.31190757, -0.39928889, -0.49134004, -0.5876908 , -0.68802399,\n -0.79206502, -0.89957393, -1.01033927, -1.12417341, -1.24090869,\n -1.36039449, -1.48249475, -1.60708597, -1.73405557, -1.86330055,\n -1.99472628, -2.12824554, -2.26377775, -2.40124816, -2.54058732,\n -2.6817305 ]), 'entropy': array([1.02970750e-08, 5.98072651e+00, 2.96865053e+01, 5.55852668e+01,\n 7.82409727e+01, 9.75218995e+01, 1.14065625e+02, 1.28465273e+02,\n 1.41174728e+02, 1.52530436e+02, 1.62783056e+02, 1.72122199e+02,\n 1.80693841e+02, 1.88612312e+02, 1.95968600e+02, 2.02836175e+02,\n 2.09275150e+02, 2.15335286e+02, 2.21058222e+02, 2.26479132e+02,\n 2.31627991e+02, 2.36530543e+02, 2.41209060e+02, 2.45682935e+02,\n 2.49969156e+02, 2.54082691e+02, 2.58036788e+02, 2.61843234e+02,\n 2.65512561e+02, 2.69054215e+02, 2.72476702e+02]), 'heat_capacity': array([1.67065980e-07, 1.73540235e+01, 5.38037700e+01, 7.36871465e+01,\n 8.35644372e+01, 8.88841670e+01, 9.20085315e+01, 9.39792227e+01,\n 9.52946945e+01, 9.62133951e+01, 9.68788951e+01, 9.73756862e+01,\n 9.77559504e+01, 9.80532534e+01, 9.82899463e+01, 9.84813619e+01,\n 9.86382931e+01, 9.87685101e+01, 9.88777197e+01, 9.89701872e+01,\n 9.90491516e+01, 9.91171073e+01, 9.91760000e+01, 9.92273651e+01,\n 9.92724273e+01, 9.93121724e+01, 9.93474017e+01, 9.93787712e+01,\n 9.94068224e+01, 9.94320054e+01, 9.94546967e+01])}\n" + } + ], + "source": [ + "tp_dict = workflow.get_thermal_properties(\n", + " t_min=1,\n", + " t_max=1500,\n", + " t_step=50,\n", + " temperatures=None,\n", + " cutoff_frequency=None,\n", + " pretend_real=False,\n", + " band_indices=None,\n", + " is_projection=False,\n", + " quantum_mechanical=True,\n", + ")\n", + "print(tp_dict)" + ] + }, + { + "cell_type": "markdown", + "id": "1fb5c6e3-83a4-4503-a0f1-4958ebc6361c", + "metadata": {}, + "source": "This requires the same inputs as the calculation of the thermal properties `get_thermal_properties()` with the \n`PhonopyWorkflow`. The additional parameter `quantum_mechanical` specifies whether the classical harmonic oscillator or \nthe quantum mechanical harmonic oscillator is used to calculate the free energy. " + }, + { + "cell_type": "markdown", + "id": "3e6cc3bd-5f7c-4462-8083-5111dc5d4577", + "metadata": {}, + "source": "And finally also the thermal expansion can be calculated:" + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "76426cc0-38c8-480e-9fd1-fbcb41c8afec", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "tp_dict = workflow.get_thermal_properties(\n", + " t_min=1,\n", + " t_max=1500,\n", + " t_step=50,\n", + " temperatures=None,\n", + " cutoff_frequency=None,\n", + " pretend_real=False,\n", + " band_indices=None,\n", + " is_projection=False,\n", + " quantum_mechanical=True,\n", + " output_keys=[\"free_energy\", \"temperatures\", \"volumes\"],\n", + ")\n", + "temperatures, volumes = tp_dict[\"temperatures\"], tp_dict[\"volumes\"]" + ] + }, + { + "cell_type": "markdown", + "id": "3cf34091-d7f5-464a-b386-9b81c1fa853a", + "metadata": {}, + "source": "## Structure Optimization \nIn analogy to the molecular dynamics calculation also the structure optimization could in principle be defined inside \nthe simulation code or on the python level. Still currently the `atomistics` package only supports the structure \noptimization defined inside the simulation codes. " + }, + { + "cell_type": "markdown", + "id": "e58b5d2e-8839-48c6-b72e-0fa09ace20ce", + "metadata": {}, + "source": "### Volume and Positions \nTo optimize both the volume of the supercell as well as the positions inside the supercell the `atomistics` package\nimplements the `optimize_positions_and_volume()` workflow:" + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "a7f38a78-11b9-41c2-82c9-7c30b3a9b005", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "Atoms(symbols='Al4', pbc=True, cell=[[4.05000466219724, 2.4799126230458533e-16, 2.4799126230458533e-16], [0.0, 4.05000466219724, 2.4799126230458533e-16], [0.0, 0.0, 4.05000466219724]])" + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import evaluate_with_lammps, get_potential_by_name\n", + "from atomistics.workflows import optimize_positions_and_volume\n", + "\n", + "structure = bulk(\"Al\", a=4.0, cubic=True)\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "result_dict = evaluate_with_lammps(\n", + " task_dict=optimize_positions_and_volume(structure=structure),\n", + " potential_dataframe=potential_dataframe,\n", + ")\n", + "structure_opt = result_dict[\"structure_with_optimized_positions_and_volume\"]\n", + "structure_opt" + ] + }, + { + "cell_type": "markdown", + "id": "c375f310-78c2-426a-8f77-669e9bec855f", + "metadata": {}, + "source": "The result is the optimized atomistic structure as part of the result dictionary. " + }, + { + "cell_type": "markdown", + "id": "6d4ef070-f0f1-4f56-afff-ff6322d3729a", + "metadata": {}, + "source": "### Positions \nThe optimization of the positions inside the supercell without the optimization of the supercell volume is possible with\nthe `optimize_positions()` workflow:" + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "9a50125b-a97a-4445-b140-b8019c035902", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "Atoms(symbols='Al4', pbc=True, cell=[4.0, 4.0, 4.0])" + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import evaluate_with_lammps, get_potential_by_name\n", + "from atomistics.workflows import optimize_positions\n", + "\n", + "structure = bulk(\"Al\", a=4.0, cubic=True)\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "result_dict = evaluate_with_lammps(\n", + " task_dict=optimize_positions(structure=structure),\n", + " potential_dataframe=potential_dataframe,\n", + ")\n", + "structure_opt = result_dict[\"structure_with_optimized_positions\"]\n", + "structure_opt" + ] + }, + { + "cell_type": "markdown", + "id": "d027161c-abd3-4267-a10f-cb404c3ebbfd", + "metadata": {}, + "source": "The result is the optimized atomistic structure as part of the result dictionary. " + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a84ef4fc-a9a7-4386-921f-7b77af81a166", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/simulation_codes.ipynb b/notebooks/simulation_codes.ipynb index fce194f6..b08d76a0 100644 --- a/notebooks/simulation_codes.ipynb +++ b/notebooks/simulation_codes.ipynb @@ -1 +1,333 @@ -{"metadata":{"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.10.14","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":5,"nbformat":4,"cells":[{"id":"dcc94f22-3be1-4cd9-9f1c-e61f7e03a1f5","cell_type":"markdown","source":"# Simulation Codes","metadata":{}},{"id":"5ffec124-6252-4965-9267-cc771c79570f","cell_type":"markdown","source":"## ASE\nAt the current stage the majority of simulation codes are interfaced using the [Atomic Simulation Environment (ASE)](https://wiki.fysik.dtu.dk/ase/).\nThe limitation of the ASE based interfaces is that the simulation codes are only used to calculate energies, forces and\nstresses, while more complex computations like structure optimization or molecular dynamics are implemented in python.","metadata":{}},{"id":"ece0e223-3b49-41d7-99ab-e0518ef01c2b","cell_type":"markdown","source":"### Abinit\n[Abinit](https://www.abinit.org) - Plane wave density functional theory:","metadata":{}},{"id":"59904794-1beb-43f5-b6e2-f79404ca8b46","cell_type":"code","source":"import os \n\nfrom ase.calculators.abinit import Abinit, AbinitProfile\nfrom ase.units import Ry\nfrom atomistics.calculators import evaluate_with_ase\n\nresult_dict = evaluate_with_ase(\n task_dict={},\n ase_calculator=Abinit(\n nbands=32,\n ecut=10 * Ry,\n kpts=(3, 3, 3),\n toldfe=1.0e-2,\n profile=AbinitProfile(\n command=\"abinit\",\n pp_paths=os.path.join(os.environ[\"CONDA_PREFIX\"], \"share/abinit/LDA_FHI\"),\n ),\n )\n)","metadata":{"tags":[],"trusted":false},"outputs":[],"execution_count":1},{"id":"53687acd-cc66-470c-b88b-c4a2a7f4182c","cell_type":"markdown","source":"The full documentation of the corresponding interface is available on the [Atomic Simulation Environment](https://wiki.fysik.dtu.dk/ase/ase/calculators/abinit.html)\nwebsite. ","metadata":{}},{"id":"a765a024-fc04-4add-b6c2-eef026e4dbd2","cell_type":"markdown","source":"### EMT\n[EMT](https://wiki.fysik.dtu.dk/ase/ase/calculators/emt.html) - Effective medium theory: ","metadata":{}},{"id":"a7467756-1366-42c2-b595-e8c7893437ab","cell_type":"code","source":"from ase.calculators.emt import EMT\nfrom atomistics.calculators import evaluate_with_ase\n\nresult_dict = evaluate_with_ase(\n task_dict={}, \n ase_calculator=EMT()\n)","metadata":{"tags":[],"trusted":false},"outputs":[],"execution_count":2},{"id":"e635174f-be67-462f-a3aa-1d3103c31d97","cell_type":"markdown","source":"The full documentation of the corresponding interface is available on the [Atomic Simulation Environment](https://wiki.fysik.dtu.dk/ase/ase/calculators/emt.html)\nwebsite. ","metadata":{}},{"id":"af758cea-e4ad-475e-8fcc-2afbf497334d","cell_type":"markdown","source":"### GPAW\n[GPAW](https://wiki.fysik.dtu.dk/gpaw/) - Density functional theory Python code based on the projector-augmented wave \nmethod:","metadata":{}},{"id":"10a942f6-b4c0-4710-856f-e736a643ce17","cell_type":"code","source":"from gpaw import GPAW, PW\nfrom atomistics.calculators import evaluate_with_ase\n\nresult_dict = evaluate_with_ase(\n task_dict={}, \n ase_calculator=GPAW(\n xc=\"PBE\",\n mode=PW(300),\n kpts=(3, 3, 3)\n )\n)","metadata":{"tags":[],"trusted":false},"outputs":[{"name":"stdout","text":"\n ___ ___ ___ _ _ _ \n | | |_ | | | | \n | | | | | . | | | | \n |__ | _|___|_____| 24.1.0\n |___|_| \n\nUser: jovyan@jupyter-pyiron-2datomistics-2djetdbyfr\nDate: Wed May 1 22:47:22 2024\nArch: x86_64\nPid: 754\nCWD: /home/jovyan\nPython: 3.10.12\ngpaw: /srv/conda/envs/notebook/lib/python3.10/site-packages/gpaw\n_gpaw: /srv/conda/envs/notebook/lib/python3.10/site-packages/\n _gpaw.cpython-310-x86_64-linux-gnu.so\nase: /srv/conda/envs/notebook/lib/python3.10/site-packages/ase (version 3.22.1)\nnumpy: /srv/conda/envs/notebook/lib/python3.10/site-packages/numpy (version 1.26.4)\nscipy: /srv/conda/envs/notebook/lib/python3.10/site-packages/scipy (version 1.13.0)\nlibxc: 6.2.2\nunits: Angstrom and eV\ncores: 1\nOpenMP: True\nOMP_NUM_THREADS: 1\n\nInput parameters:\n kpts: [3 3 3]\n mode: {ecut: 300.0,\n name: pw}\n xc: PBE\n\nMemory usage: 142.86 MiB\nDate: Wed May 1 22:47:22 2024\n","output_type":"stream"},{"name":"stderr","text":"[jupyter-pyiron-2datomistics-2djetdbyfr:00754] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n","output_type":"stream"}],"execution_count":3},{"id":"a38a03dd-630c-4bff-a256-d0380da29db1","cell_type":"markdown","source":"The full documentation of the corresponding interface is available on the [GPAW](https://wiki.fysik.dtu.dk/gpaw/)\nwebsite.","metadata":{}},{"id":"f8a20ee4-153d-4c0b-b89f-a3ac64cfbcbc","cell_type":"markdown","source":"### Quantum Espresso \n[Quantum Espresso](https://www.quantum-espresso.org) - Integrated suite of Open-Source computer codes for \nelectronic-structure calculations:","metadata":{}},{"id":"40b9384e-02a0-41d8-adff-ad4dd6316a21","cell_type":"code","source":"from ase.calculators.espresso import Espresso, EspressoProfile\nfrom atomistics.calculators import evaluate_with_ase\n\nresult_dict = evaluate_with_ase(\n task_dict={}, \n ase_calculator=Espresso(\n pseudopotentials={\"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"},\n tstress=True,\n tprnfor=True,\n kpts=(3, 3, 3),\n profile=EspressoProfile(\n command=\"pw.x\",\n pseudo_dir=\"tests/static/qe\",\n ),\n )\n)","metadata":{"tags":[],"trusted":false},"outputs":[],"execution_count":4},{"id":"c7f74b95-e161-4ee6-8a9b-58c11ba3ca47","cell_type":"markdown","source":"The full documentation of the corresponding interface is available on the [Atomic Simulation Environment](https://wiki.fysik.dtu.dk/ase/ase/calculators/espresso.html)\nwebsite. ","metadata":{}},{"id":"cdc1c88c-62f8-4af1-a135-9266ba1ab1ee","cell_type":"markdown","source":"### Siesta\n[Siesta](https://siesta-project.org) - Electronic structure calculations and ab initio molecular dynamics:","metadata":{}},{"id":"5fa73a10-043f-4b46-a162-3f1da7399cba","cell_type":"code","source":"import os\nfrom ase.calculators.siesta import Siesta\nfrom ase.units import Ry\nfrom atomistics.calculators import evaluate_with_ase\n\nresult_dict = evaluate_with_ase(\n task_dict={}, \n ase_calculator=Siesta(\n label=\"siesta\",\n xc=\"PBE\",\n mesh_cutoff=200 * Ry,\n energy_shift=0.01 * Ry,\n basis_set=\"DZ\",\n kpts=(5, 5, 5),\n fdf_arguments={\"DM.MixingWeight\": 0.1, \"MaxSCFIterations\": 100},\n pseudo_path=os.path.abspath(\"tests/static/siesta\"),\n pseudo_qualifier=\"\",\n )\n)","metadata":{"tags":[],"trusted":false},"outputs":[],"execution_count":5},{"id":"ed3bba6d-8fd9-4d26-8f0d-437fb5559397","cell_type":"markdown","source":"The full documentation of the corresponding interface is available on the [Atomic Simulation Environment](https://wiki.fysik.dtu.dk/ase/ase/calculators/siesta.html)\nwebsite.","metadata":{}},{"id":"0c09855c-80ca-4fb9-9f66-458b8d145e59","cell_type":"markdown","source":"## LAMMPS\n[LAMMPS](https://www.lammps.org) - Molecular Dynamics:","metadata":{}},{"id":"a95e1c9c-1ad1-4765-aa13-790db6971dab","cell_type":"code","source":"from ase.build import bulk\nfrom atomistics.calculators import evaluate_with_lammps, get_potential_by_name\n\nstructure = bulk(\"Al\", cubic=True)\npotential_dataframe = get_potential_by_name(\n potential_name='1999--Mishin-Y--Al--LAMMPS--ipr1',\n resource_path=\"static/lammps\"\n)\n\nresult_dict = evaluate_with_lammps(\n task_dict={},\n potential_dataframe=potential_dataframe,\n)","metadata":{"tags":[],"trusted":false},"outputs":[{"name":"stderr","text":"/srv/conda/envs/notebook/lib/python3.10/site-packages/atomistics/calculators/lammps/potential.py:299: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n df_pot[\"Config\"] = config_lst\n","output_type":"stream"}],"execution_count":6},{"id":"ed5732c4-4221-4081-83d8-2c1df793d8b7","cell_type":"markdown","source":"The [LAMMPS](https://www.lammps.org) interface is based on the [pylammpsmpi](https://github.com/pyiron/pylammpsmpi)\npackage which couples a [LAMMPS](https://www.lammps.org) instance which is parallelized via the Message Passing Interface\n(MPI) with a serial python process or jupyter notebook. The challenging part about molecular dynamics simulation is \nidentifying a suitable interatomic potential. \n\nTo address this challenge the `atomistics` package is leveraging the [NIST database of interatomic potentials](https://www.ctcms.nist.gov/potentials). \nIt is recommended to install this database `iprpy-data` via the `conda` package manager, then the `resource_path` is\nautomatically set to `${CONDA_PREFIX}/share/iprpy`. Alternatively, the `resource_path` can be specified manually as an\noptional parameter of the `get_potential_by_name()` function.\n\nIn addition, the `get_potential_dataframe(structure)` function which takes an `ase.atoms.Atoms` object as input can be\nused to query the [NIST database of interatomic potentials](https://www.ctcms.nist.gov/potentials) for potentials, which\ninclude the interatomic interactions required to simulate the atomic structure defined by the `ase.atoms.Atoms` object. \nIt returns a `pandas.DataFrame` with all the available potentials and the `resource_path` can again be specified as \noptional parameter.\n\nFinally, another option to specify the interatomic potential for a LAMMPS simulation is by defining the `potential_dataframe`\ndirectly: ","metadata":{}},{"id":"4ab54444-0d8b-42dd-8a97-c0743598a7bd","cell_type":"code","source":"import pandas \n\npotential_dataframe = pandas.DataFrame({\n \"Config\": [[\n \"pair_style morse/smooth/linear 9.0\",\n \"pair_coeff * * 0.5 1.8 2.95\"\n ]],\n \"Filename\": [[]],\n \"Model\": [\"Morse\"],\n \"Name\": [\"Morse\"],\n \"Species\": [[\"Al\"]],\n})","metadata":{"tags":[],"trusted":false},"outputs":[],"execution_count":7},{"id":"0fbec738-da33-44bf-ab6f-b222f1d56186","cell_type":"markdown","source":"## Quantum Espresso\n[Quantum Espresso](https://www.quantum-espresso.org) - Integrated suite of Open-Source computer codes for \nelectronic-structure calculations:","metadata":{}},{"id":"1e7fe91e-424e-46c6-b1de-632ae9333b77","cell_type":"markdown","source":"```\nfrom atomistics.calculators import evaluate_with_qe\n\nresult_dict = evaluate_with_qe(\n task_dict={},\n calculation_name=\"espresso\",\n working_directory=\".\",\n kpts=(3, 3, 3),\n pseudopotentials={\n \"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"\n },\n tstress=True,\n tprnfor=True,\n ecutwfc=40.0, # kinetic energy cutoff (Ry) for wavefunctions\n conv_thr=1e-06, # Convergence threshold for selfconsistency\n diagonalization='david', \n electron_maxstep=100, # maximum number of iterations in a scf step. \n nstep=200, # number of molecular-dynamics or structural optimization steps performed in this run.\n etot_conv_thr=1e-4, # Convergence threshold on total energy (a.u) for ionic minimization\n forc_conv_thr=1e-3, # Convergence threshold on forces (a.u) for ionic minimization\n smearing='gaussian', # ordinary Gaussian spreading (Default)\n)\n```","metadata":{"tags":[]}},{"id":"727f824e-97a2-42ae-94f2-b8080c023e24","cell_type":"markdown","source":"This secondary interface for [Quantum Espresso](https://www.quantum-espresso.org) is based on the input writer from the\n[Atomic Simulation Environment (ASE)](https://wiki.fysik.dtu.dk/ase/) and the output is parsed using the [pwtools](https://elcorto.github.io/pwtools/).\nThe executable can be set using the `ASE_ESPRESSO_COMMAND` environment variable:","metadata":{}},{"id":"b840f3d2-a7b3-42d6-8401-e350dc905c2f","cell_type":"markdown","source":"```\nexport ASE_ESPRESSO_COMMAND=\"pw.x -in PREFIX.pwi > PREFIX.pwo\"\n```","metadata":{}},{"id":"54ee1c7b-a829-49b9-8746-d57496b339e6","cell_type":"markdown","source":"The full list of possible keyword arguments is available in the [Quantum Espresso Documentation](https://www.quantum-espresso.org/Doc/INPUT_PW.html).\nFinally, the [Standard solid-state pseudopotentials (SSSP)](https://www.materialscloud.org/discover/sssp/table/efficiency) \nfor quantum espresso are distributed via the materials cloud.","metadata":{"tags":[]}}]} \ No newline at end of file +{ + "cells": [ + { + "cell_type": "markdown", + "id": "dcc94f22-3be1-4cd9-9f1c-e61f7e03a1f5", + "metadata": {}, + "source": "# Simulation Codes" + }, + { + "cell_type": "markdown", + "id": "5ffec124-6252-4965-9267-cc771c79570f", + "metadata": {}, + "source": "## ASE\nAt the current stage the majority of simulation codes are interfaced using the [Atomic Simulation Environment (ASE)](https://wiki.fysik.dtu.dk/ase/).\nThe limitation of the ASE based interfaces is that the simulation codes are only used to calculate energies, forces and\nstresses, while more complex computations like structure optimization or molecular dynamics are implemented in python." + }, + { + "cell_type": "markdown", + "id": "ece0e223-3b49-41d7-99ab-e0518ef01c2b", + "metadata": {}, + "source": "### Abinit\n[Abinit](https://www.abinit.org) - Plane wave density functional theory:" + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "59904794-1beb-43f5-b6e2-f79404ca8b46", + "metadata": { + "tags": [], + "trusted": false + }, + "outputs": [], + "source": [ + "import os\n", + "\n", + "from ase.calculators.abinit import Abinit, AbinitProfile\n", + "from ase.units import Ry\n", + "from atomistics.calculators import evaluate_with_ase\n", + "\n", + "result_dict = evaluate_with_ase(\n", + " task_dict={},\n", + " ase_calculator=Abinit(\n", + " nbands=32,\n", + " ecut=10 * Ry,\n", + " kpts=(3, 3, 3),\n", + " toldfe=1.0e-2,\n", + " profile=AbinitProfile(\n", + " command=\"abinit\",\n", + " pp_paths=os.path.join(os.environ[\"CONDA_PREFIX\"], \"share/abinit/LDA_FHI\"),\n", + " ),\n", + " ),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "53687acd-cc66-470c-b88b-c4a2a7f4182c", + "metadata": {}, + "source": "The full documentation of the corresponding interface is available on the [Atomic Simulation Environment](https://wiki.fysik.dtu.dk/ase/ase/calculators/abinit.html)\nwebsite. " + }, + { + "cell_type": "markdown", + "id": "a765a024-fc04-4add-b6c2-eef026e4dbd2", + "metadata": {}, + "source": "### EMT\n[EMT](https://wiki.fysik.dtu.dk/ase/ase/calculators/emt.html) - Effective medium theory: " + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "a7467756-1366-42c2-b595-e8c7893437ab", + "metadata": { + "tags": [], + "trusted": false + }, + "outputs": [], + "source": [ + "from ase.calculators.emt import EMT\n", + "from atomistics.calculators import evaluate_with_ase\n", + "\n", + "result_dict = evaluate_with_ase(task_dict={}, ase_calculator=EMT())" + ] + }, + { + "cell_type": "markdown", + "id": "e635174f-be67-462f-a3aa-1d3103c31d97", + "metadata": {}, + "source": "The full documentation of the corresponding interface is available on the [Atomic Simulation Environment](https://wiki.fysik.dtu.dk/ase/ase/calculators/emt.html)\nwebsite. " + }, + { + "cell_type": "markdown", + "id": "af758cea-e4ad-475e-8fcc-2afbf497334d", + "metadata": {}, + "source": "### GPAW\n[GPAW](https://wiki.fysik.dtu.dk/gpaw/) - Density functional theory Python code based on the projector-augmented wave \nmethod:" + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "10a942f6-b4c0-4710-856f-e736a643ce17", + "metadata": { + "tags": [], + "trusted": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": "\n ___ ___ ___ _ _ _ \n | | |_ | | | | \n | | | | | . | | | | \n |__ | _|___|_____| 24.1.0\n |___|_| \n\nUser: jovyan@jupyter-pyiron-2datomistics-2djetdbyfr\nDate: Wed May 1 22:47:22 2024\nArch: x86_64\nPid: 754\nCWD: /home/jovyan\nPython: 3.10.12\ngpaw: /srv/conda/envs/notebook/lib/python3.10/site-packages/gpaw\n_gpaw: /srv/conda/envs/notebook/lib/python3.10/site-packages/\n _gpaw.cpython-310-x86_64-linux-gnu.so\nase: /srv/conda/envs/notebook/lib/python3.10/site-packages/ase (version 3.22.1)\nnumpy: /srv/conda/envs/notebook/lib/python3.10/site-packages/numpy (version 1.26.4)\nscipy: /srv/conda/envs/notebook/lib/python3.10/site-packages/scipy (version 1.13.0)\nlibxc: 6.2.2\nunits: Angstrom and eV\ncores: 1\nOpenMP: True\nOMP_NUM_THREADS: 1\n\nInput parameters:\n kpts: [3 3 3]\n mode: {ecut: 300.0,\n name: pw}\n xc: PBE\n\nMemory usage: 142.86 MiB\nDate: Wed May 1 22:47:22 2024\n" + }, + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pyiron-2datomistics-2djetdbyfr:00754] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n" + } + ], + "source": [ + "from gpaw import GPAW, PW\n", + "from atomistics.calculators import evaluate_with_ase\n", + "\n", + "result_dict = evaluate_with_ase(\n", + " task_dict={}, ase_calculator=GPAW(xc=\"PBE\", mode=PW(300), kpts=(3, 3, 3))\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "a38a03dd-630c-4bff-a256-d0380da29db1", + "metadata": {}, + "source": "The full documentation of the corresponding interface is available on the [GPAW](https://wiki.fysik.dtu.dk/gpaw/)\nwebsite." + }, + { + "cell_type": "markdown", + "id": "f8a20ee4-153d-4c0b-b89f-a3ac64cfbcbc", + "metadata": {}, + "source": "### Quantum Espresso \n[Quantum Espresso](https://www.quantum-espresso.org) - Integrated suite of Open-Source computer codes for \nelectronic-structure calculations:" + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "40b9384e-02a0-41d8-adff-ad4dd6316a21", + "metadata": { + "tags": [], + "trusted": false + }, + "outputs": [], + "source": [ + "from ase.calculators.espresso import Espresso, EspressoProfile\n", + "from atomistics.calculators import evaluate_with_ase\n", + "\n", + "result_dict = evaluate_with_ase(\n", + " task_dict={},\n", + " ase_calculator=Espresso(\n", + " pseudopotentials={\"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"},\n", + " tstress=True,\n", + " tprnfor=True,\n", + " kpts=(3, 3, 3),\n", + " profile=EspressoProfile(\n", + " command=\"pw.x\",\n", + " pseudo_dir=\"tests/static/qe\",\n", + " ),\n", + " ),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "c7f74b95-e161-4ee6-8a9b-58c11ba3ca47", + "metadata": {}, + "source": "The full documentation of the corresponding interface is available on the [Atomic Simulation Environment](https://wiki.fysik.dtu.dk/ase/ase/calculators/espresso.html)\nwebsite. " + }, + { + "cell_type": "markdown", + "id": "cdc1c88c-62f8-4af1-a135-9266ba1ab1ee", + "metadata": {}, + "source": "### Siesta\n[Siesta](https://siesta-project.org) - Electronic structure calculations and ab initio molecular dynamics:" + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "5fa73a10-043f-4b46-a162-3f1da7399cba", + "metadata": { + "tags": [], + "trusted": false + }, + "outputs": [], + "source": [ + "import os\n", + "from ase.calculators.siesta import Siesta\n", + "from ase.units import Ry\n", + "from atomistics.calculators import evaluate_with_ase\n", + "\n", + "result_dict = evaluate_with_ase(\n", + " task_dict={},\n", + " ase_calculator=Siesta(\n", + " label=\"siesta\",\n", + " xc=\"PBE\",\n", + " mesh_cutoff=200 * Ry,\n", + " energy_shift=0.01 * Ry,\n", + " basis_set=\"DZ\",\n", + " kpts=(5, 5, 5),\n", + " fdf_arguments={\"DM.MixingWeight\": 0.1, \"MaxSCFIterations\": 100},\n", + " pseudo_path=os.path.abspath(\"tests/static/siesta\"),\n", + " pseudo_qualifier=\"\",\n", + " ),\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "ed3bba6d-8fd9-4d26-8f0d-437fb5559397", + "metadata": {}, + "source": "The full documentation of the corresponding interface is available on the [Atomic Simulation Environment](https://wiki.fysik.dtu.dk/ase/ase/calculators/siesta.html)\nwebsite." + }, + { + "cell_type": "markdown", + "id": "0c09855c-80ca-4fb9-9f66-458b8d145e59", + "metadata": {}, + "source": "## LAMMPS\n[LAMMPS](https://www.lammps.org) - Molecular Dynamics:" + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "a95e1c9c-1ad1-4765-aa13-790db6971dab", + "metadata": { + "tags": [], + "trusted": false + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "/srv/conda/envs/notebook/lib/python3.10/site-packages/atomistics/calculators/lammps/potential.py:299: SettingWithCopyWarning: \nA value is trying to be set on a copy of a slice from a DataFrame.\nTry using .loc[row_indexer,col_indexer] = value instead\n\nSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n df_pot[\"Config\"] = config_lst\n" + } + ], + "source": [ + "from ase.build import bulk\n", + "from atomistics.calculators import evaluate_with_lammps, get_potential_by_name\n", + "\n", + "structure = bulk(\"Al\", cubic=True)\n", + "potential_dataframe = get_potential_by_name(\n", + " potential_name=\"1999--Mishin-Y--Al--LAMMPS--ipr1\", resource_path=\"static/lammps\"\n", + ")\n", + "\n", + "result_dict = evaluate_with_lammps(\n", + " task_dict={},\n", + " potential_dataframe=potential_dataframe,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "ed5732c4-4221-4081-83d8-2c1df793d8b7", + "metadata": {}, + "source": "The [LAMMPS](https://www.lammps.org) interface is based on the [pylammpsmpi](https://github.com/pyiron/pylammpsmpi)\npackage which couples a [LAMMPS](https://www.lammps.org) instance which is parallelized via the Message Passing Interface\n(MPI) with a serial python process or jupyter notebook. The challenging part about molecular dynamics simulation is \nidentifying a suitable interatomic potential. \n\nTo address this challenge the `atomistics` package is leveraging the [NIST database of interatomic potentials](https://www.ctcms.nist.gov/potentials). \nIt is recommended to install this database `iprpy-data` via the `conda` package manager, then the `resource_path` is\nautomatically set to `${CONDA_PREFIX}/share/iprpy`. Alternatively, the `resource_path` can be specified manually as an\noptional parameter of the `get_potential_by_name()` function.\n\nIn addition, the `get_potential_dataframe(structure)` function which takes an `ase.atoms.Atoms` object as input can be\nused to query the [NIST database of interatomic potentials](https://www.ctcms.nist.gov/potentials) for potentials, which\ninclude the interatomic interactions required to simulate the atomic structure defined by the `ase.atoms.Atoms` object. \nIt returns a `pandas.DataFrame` with all the available potentials and the `resource_path` can again be specified as \noptional parameter.\n\nFinally, another option to specify the interatomic potential for a LAMMPS simulation is by defining the `potential_dataframe`\ndirectly: " + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "4ab54444-0d8b-42dd-8a97-c0743598a7bd", + "metadata": { + "tags": [], + "trusted": false + }, + "outputs": [], + "source": [ + "import pandas\n", + "\n", + "potential_dataframe = pandas.DataFrame(\n", + " {\n", + " \"Config\": [\n", + " [\"pair_style morse/smooth/linear 9.0\", \"pair_coeff * * 0.5 1.8 2.95\"]\n", + " ],\n", + " \"Filename\": [[]],\n", + " \"Model\": [\"Morse\"],\n", + " \"Name\": [\"Morse\"],\n", + " \"Species\": [[\"Al\"]],\n", + " }\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "0fbec738-da33-44bf-ab6f-b222f1d56186", + "metadata": {}, + "source": "## Quantum Espresso\n[Quantum Espresso](https://www.quantum-espresso.org) - Integrated suite of Open-Source computer codes for \nelectronic-structure calculations:" + }, + { + "cell_type": "markdown", + "id": "1e7fe91e-424e-46c6-b1de-632ae9333b77", + "metadata": { + "tags": [] + }, + "source": "```\nfrom atomistics.calculators import evaluate_with_qe\n\nresult_dict = evaluate_with_qe(\n task_dict={},\n calculation_name=\"espresso\",\n working_directory=\".\",\n kpts=(3, 3, 3),\n pseudopotentials={\n \"Al\": \"Al.pbe-n-kjpaw_psl.1.0.0.UPF\"\n },\n tstress=True,\n tprnfor=True,\n ecutwfc=40.0, # kinetic energy cutoff (Ry) for wavefunctions\n conv_thr=1e-06, # Convergence threshold for selfconsistency\n diagonalization='david', \n electron_maxstep=100, # maximum number of iterations in a scf step. \n nstep=200, # number of molecular-dynamics or structural optimization steps performed in this run.\n etot_conv_thr=1e-4, # Convergence threshold on total energy (a.u) for ionic minimization\n forc_conv_thr=1e-3, # Convergence threshold on forces (a.u) for ionic minimization\n smearing='gaussian', # ordinary Gaussian spreading (Default)\n)\n```" + }, + { + "cell_type": "markdown", + "id": "727f824e-97a2-42ae-94f2-b8080c023e24", + "metadata": {}, + "source": "This secondary interface for [Quantum Espresso](https://www.quantum-espresso.org) is based on the input writer from the\n[Atomic Simulation Environment (ASE)](https://wiki.fysik.dtu.dk/ase/) and the output is parsed using the [pwtools](https://elcorto.github.io/pwtools/).\nThe executable can be set using the `ASE_ESPRESSO_COMMAND` environment variable:" + }, + { + "cell_type": "markdown", + "id": "b840f3d2-a7b3-42d6-8401-e350dc905c2f", + "metadata": {}, + "source": "```\nexport ASE_ESPRESSO_COMMAND=\"pw.x -in PREFIX.pwi > PREFIX.pwo\"\n```" + }, + { + "cell_type": "markdown", + "id": "54ee1c7b-a829-49b9-8746-d57496b339e6", + "metadata": { + "tags": [] + }, + "source": "The full list of possible keyword arguments is available in the [Quantum Espresso Documentation](https://www.quantum-espresso.org/Doc/INPUT_PW.html).\nFinally, the [Standard solid-state pseudopotentials (SSSP)](https://www.materialscloud.org/discover/sssp/table/efficiency) \nfor quantum espresso are distributed via the materials cloud." + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} \ No newline at end of file diff --git a/notebooks/thermal_expansion_with_lammps.ipynb b/notebooks/thermal_expansion_with_lammps.ipynb index 40d094df..b7f79a27 100644 --- a/notebooks/thermal_expansion_with_lammps.ipynb +++ b/notebooks/thermal_expansion_with_lammps.ipynb @@ -1 +1,525 @@ -{"metadata":{"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":5,"nbformat":4,"cells":[{"cell_type":"markdown","source":"## Thermal Expansion \nCalculate the thermal expansion for a Morse Pair potential using the [LAMMPS](https://www.lammps.org/) molecular dynamics\nsimulation code. In the following three methods to calculate the thermal expansion are introduced and compared for a \nMorse Pair Potential for Aluminium. \n\nAs a first step the potential is defined for the [LAMMPS](https://www.lammps.org/) molecular dynamics simulation code \nby specifying the `pair_style` and `pair_coeff` commands for the [Morse Pair Potential](https://docs.lammps.org/pair_morse.html)\nas well as the Aluminium bulk structure: ","metadata":{},"id":"ce2efe0c-f86c-4cbd-ab3f-2aae9c5a574d"},{"cell_type":"code","source":"from ase.build import bulk\nimport pandas\n\npotential_dataframe = pandas.DataFrame({\n \"Config\": [[\n \"pair_style morse/smooth/linear 9.0\",\n \"pair_coeff * * 0.5 1.8 2.95\"\n ]],\n \"Filename\": [[]],\n \"Model\": [\"Morse\"],\n \"Name\": [\"Morse\"],\n \"Species\": [[\"Al\"]],\n})\n\nstructure = bulk(\"Al\", cubic=True)","metadata":{"trusted":true},"execution_count":1,"outputs":[],"id":"7a96bac5-5afe-4924-90e5-04f6e6b2bedb"},{"cell_type":"markdown","source":"The `pandas.DataFrame` based format to specify interatomic potentials is the same `pylammpsmpi` uses to interface with \nthe [NIST database for interatomic potentials](https://www.ctcms.nist.gov/potentials). In comparison to just providing\nthe `pair_style` and `pair_coeff` commands, this extended format enables referencing specific files for the interatomic\npotentials `\"Filename\": [[]],` as well as the atomic species `\"Species\": [[\"Al\"]],` to enable consistency checks if the \ninteratomic potential implements all the interactions to simulate a given atomic structure. ","metadata":{},"id":"fe980834-e174-464a-8c07-04db9889a8c6"},{"cell_type":"markdown","source":"Finally, the last step of the preparation before starting the actual calculation is optimizing the interatomic structure. \nWhile for the Morse potential used in this example this is not necessary, it is essential for extending this example to\nother interactomic potentials. For the structure optimization the `optimize_positions_and_volume()` function is imported\nand applied on the `ase.atoms.Atoms` bulk structure for Aluminium:","metadata":{},"id":"b825e555-5e3d-43c2-8c51-50207ead60b5"},{"cell_type":"code","source":"from atomistics.workflows import optimize_positions_and_volume\n\ntask_dict = optimize_positions_and_volume(structure=structure)\ntask_dict","metadata":{"trusted":true},"execution_count":2,"outputs":[{"execution_count":2,"output_type":"execute_result","data":{"text/plain":"{'optimize_positions_and_volume': Atoms(symbols='Al4', pbc=True, cell=[4.05, 4.05, 4.05])}"},"metadata":{}}],"id":"7bd4ed1a-bffe-40f9-99f8-706797418877"},{"cell_type":"markdown","source":"It returns a `task_dict` with a single task, the optimization of the positions and the volume of the Aluminium structure.\nThis task is executed with the [LAMMPS](https://www.lammps.org/) molecular dynamics simulation code using the \n`evaluate_with_lammps()` function:","metadata":{},"id":"ed380b51-efa8-4ebb-bb27-b4aca90b21ec"},{"cell_type":"code","source":"from atomistics.calculators import evaluate_with_lammps\n\nresult_dict = evaluate_with_lammps(\n task_dict=task_dict,\n potential_dataframe=potential_dataframe,\n)\nstructure_opt = result_dict[\"structure_with_optimized_positions_and_volume\"]\nstructure_opt","metadata":{"trusted":true},"execution_count":3,"outputs":[{"name":"stderr","text":"[jupyter-pyiron-2datomistics-2djetdbyfr:00796] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n/srv/conda/envs/notebook/lib/python3.10/site-packages/pylammpsmpi/wrapper/ase.py:165: UserWarning: Warning: setting upper trangular matrix might slow down the calculation\n warnings.warn(\n","output_type":"stream"},{"execution_count":3,"output_type":"execute_result","data":{"text/plain":"Atoms(symbols='Al4', pbc=True, cell=[[4.047310585424964, 2.478262976797941e-16, 2.478262976797941e-16], [0.0, 4.047310585424964, 2.478262976797941e-16], [0.0, 0.0, 4.047310585424964]])"},"metadata":{}}],"id":"991eaf43-0c4b-4ca2-8494-2b11684f4a79"},{"cell_type":"markdown","source":"The `result_dict` just contains a single element, the `ase.atoms.Atoms` structure object with optimized positions and \nvolume. After this step the preparation is completed and the three different approximations can be compared in the following.","metadata":{},"id":"6750cc4c-106f-4066-80ad-860bf6980732"},{"cell_type":"markdown","source":"### Equation of State \nThe first approximation to calculate the thermal expansion is based on the Equation of State derived by [Moruzzi, V. L. et al.](https://link.aps.org/doi/10.1103/PhysRevB.37.790).\nSo in analogy to the previous example of calculating the elastic properties from the Equation of State, the `EnergyVolumeCurveWorkflow`\nis initialized with the default parameters: ","metadata":{},"id":"6c120581-efd6-4204-8413-75ee81065db1"},{"cell_type":"code","source":"from atomistics.workflows import EnergyVolumeCurveWorkflow\n\nworkflow_ev = EnergyVolumeCurveWorkflow(\n structure=structure_opt.copy(),\n num_points=11,\n fit_type='birchmurnaghan',\n vol_range=0.05,\n axes=['x', 'y', 'z'],\n strains=None,\n)\nstructure_dict = workflow_ev.generate_structures()\nstructure_dict","metadata":{"trusted":true},"execution_count":4,"outputs":[{"execution_count":4,"output_type":"execute_result","data":{"text/plain":"{'calc_energy': OrderedDict([(0.95,\n Atoms(symbols='Al4', pbc=True, cell=[[3.9786988461213992, 2.43625040333692e-16, 2.43625040333692e-16], [0.0, 3.9786988461213992, 2.43625040333692e-16], [0.0, 0.0, 3.9786988461213992]])),\n (0.96,\n Atoms(symbols='Al4', pbc=True, cell=[[3.992610493736228, 2.4447688306981026e-16, 2.4447688306981026e-16], [0.0, 3.992610493736228, 2.4447688306981026e-16], [0.0, 0.0, 3.992610493736228]])),\n (0.97,\n Atoms(symbols='Al4', pbc=True, cell=[[4.00642586504517, 2.4532283058243666e-16, 2.4532283058243666e-16], [0.0, 4.00642586504517, 2.4532283058243666e-16], [0.0, 0.0, 4.00642586504517]])),\n (0.98,\n Atoms(symbols='Al4', pbc=True, cell=[[4.020146608667117, 2.461629838203636e-16, 2.461629838203636e-16], [0.0, 4.020146608667117, 2.461629838203636e-16], [0.0, 0.0, 4.020146608667117]])),\n (0.99,\n Atoms(symbols='Al4', pbc=True, cell=[[4.033774328510742, 2.469974409946722e-16, 2.469974409946722e-16], [0.0, 4.033774328510742, 2.469974409946722e-16], [0.0, 0.0, 4.033774328510742]])),\n (1.0,\n Atoms(symbols='Al4', pbc=True, cell=[[4.047310585424964, 2.478262976797941e-16, 2.478262976797941e-16], [0.0, 4.047310585424964, 2.478262976797941e-16], [0.0, 0.0, 4.047310585424964]])),\n (1.01,\n Atoms(symbols='Al4', pbc=True, cell=[[4.060756898772644, 2.486496469098726e-16, 2.486496469098726e-16], [0.0, 4.060756898772644, 2.486496469098726e-16], [0.0, 0.0, 4.060756898772644]])),\n (1.02,\n Atoms(symbols='Al4', pbc=True, cell=[[4.074114747931804, 2.494675792706855e-16, 2.494675792706855e-16], [0.0, 4.074114747931804, 2.494675792706855e-16], [0.0, 0.0, 4.074114747931804]])),\n (1.03,\n Atoms(symbols='Al4', pbc=True, cell=[[4.087385573728375, 2.5028018298737613e-16, 2.5028018298737613e-16], [0.0, 4.087385573728375, 2.5028018298737613e-16], [0.0, 0.0, 4.087385573728375]])),\n (1.04,\n Atoms(symbols='Al4', pbc=True, cell=[[4.100570779804249, 2.51087544008222e-16, 2.51087544008222e-16], [0.0, 4.100570779804249, 2.51087544008222e-16], [0.0, 0.0, 4.100570779804249]])),\n (1.05,\n Atoms(symbols='Al4', pbc=True, cell=[[4.113671733924125, 2.518897460846561e-16, 2.518897460846561e-16], [0.0, 4.113671733924125, 2.518897460846561e-16], [0.0, 0.0, 4.113671733924125]]))])}"},"metadata":{}}],"id":"b69b6ee2-b526-4913-a6c7-36018e8960af"},{"cell_type":"markdown","source":"After the initialization the `generate_structures()` function is called to generate the atomistic structures which are\nthen in the second step evaluated with the [LAMMPS](https://www.lammps.org/) molecular dynamics simulation code to derive\nthe equilibrium properties:","metadata":{},"id":"8f5d1e8d-0204-4dca-9298-878b9b2f6406"},{"cell_type":"code","source":"result_dict = evaluate_with_lammps(\n task_dict=structure_dict, \n potential_dataframe=potential_dataframe\n)\nresult_dict","metadata":{"trusted":true},"execution_count":5,"outputs":[{"execution_count":5,"output_type":"execute_result","data":{"text/plain":"{'energy': {0.95: -14.609207927145926,\n 0.96: -14.656740101454448,\n 0.97: -14.692359030099395,\n 0.98: -14.716883724875528,\n 0.99: -14.731079276327009,\n 1.0: -14.735659820057942,\n 1.01: -14.731295089579728,\n 1.02: -14.718611862249286,\n 1.03: -14.698196715842329,\n 1.04: -14.670598736769112,\n 1.05: -14.636332030744796}}"},"metadata":{}}],"id":"7d1f126e-4fd0-41c5-986b-91d3b5910e3e"},{"cell_type":"markdown","source":"While in the previous example the fit of the energy volume curve was used directly, here the output of the fit, in\nparticular the derived equilibrium properties are the input for the Debye model as defined by [Moruzzi, V. L. et al.](https://link.aps.org/doi/10.1103/PhysRevB.37.790):","metadata":{},"id":"fb679eb1-338f-4485-a953-791e147fe632"},{"cell_type":"code","source":"structure_opt.get_volume()","metadata":{"trusted":true},"execution_count":6,"outputs":[{"execution_count":6,"output_type":"execute_result","data":{"text/plain":"66.29787349319821"},"metadata":{}}],"id":"2e0f7aab-6744-4b6f-a454-38c28833a3ac"},{"cell_type":"code","source":"fit_dict = workflow_ev.analyse_structures(output_dict=result_dict)\nfit_dict","metadata":{"trusted":true},"execution_count":7,"outputs":[{"execution_count":7,"output_type":"execute_result","data":{"text/plain":"{'b_prime_eq': 6.2365371733275845,\n 'bulkmodul_eq': 216.057292780608,\n 'volume_eq': 66.29790137569191,\n 'energy_eq': -14.735658078942949,\n 'fit_dict': {'fit_type': 'birchmurnaghan',\n 'least_square_error': array([8.12779273e-07, 2.83453476e-03, 1.45091623e-03, 3.00518393e-05])},\n 'energy': [-14.609207927145926,\n -14.656740101454448,\n -14.692359030099395,\n -14.716883724875528,\n -14.731079276327009,\n -14.735659820057942,\n -14.731295089579728,\n -14.718611862249286,\n -14.698196715842329,\n -14.670598736769112,\n -14.636332030744796],\n 'volume': [62.98297981853827,\n 63.645958553470244,\n 64.30893728840229,\n 64.97191602333424,\n 65.63489475826624,\n 66.29787349319821,\n 66.96085222813018,\n 67.62383096306218,\n 68.28680969799419,\n 68.94978843292616,\n 69.61276716785807]}"},"metadata":{}}],"id":"11c8b18d-64ff-4c93-b646-668b00eb1cf8"},{"cell_type":"code","source":"import numpy as np\n\nworkflow_ev.analyse_structures(output_dict=result_dict)\nthermal_properties_dict = workflow_ev.get_thermal_properties(\n temperatures=np.arange(1, 1500, 50),\n output_keys=[\"temperatures\", \"volumes\"],\n)\ntemperatures_ev, volume_ev = thermal_properties_dict[\"temperatures\"], thermal_properties_dict[\"volumes\"]","metadata":{"trusted":true},"execution_count":8,"outputs":[{"name":"stderr","text":"/srv/conda/envs/notebook/lib/python3.10/site-packages/atomistics/workflows/evcurve/debye.py:80: RuntimeWarning: overflow encountered in exp\n return xi**3 / (np.exp(xi) - 1)\n","output_type":"stream"}],"id":"9c7cd51c-6058-4d1d-8948-56d29c3b13e7"},{"cell_type":"markdown","source":"The output of the Debye model provides the change of the temperature specific optimal volume `volume_ev`\nwhich can be plotted over the temperature `temperatures_ev` to determine the thermal expansion. ","metadata":{},"id":"35ab7b86-0688-4520-ad47-ea54b4bfde86"},{"cell_type":"markdown","source":"### Quasi-Harmonic Approximation \nWhile the [Moruzzi, V. L. et al.](https://link.aps.org/doi/10.1103/PhysRevB.37.790) approach based on the Einstein crystal\nis limited to a single frequency, the quasi-harmonic model includes the volume dependent free energy. Inside the \n`atomistics` package the harmonic and quasi-harmonic model are implemented based on an interface to the [Phonopy](https://phonopy.github.io/phonopy/)\nframework. Still the user interface is still structured in the same three steps of (1) generating structures, (2) evaluating \nthese structures and (3) fitting the corresponding model. Starting with the initialization of the `QuasiHarmonicWorkflow`\nwhich combines the `PhonopyWorkflow` with the `EnergyVolumeCurveWorkflow`:","metadata":{},"id":"88ccd1f0-98c5-4e13-ab2c-febe5d3f235b"},{"cell_type":"code","source":"from atomistics.workflows import QuasiHarmonicWorkflow\nfrom phonopy.units import VaspToTHz\n\nworkflow_qh = QuasiHarmonicWorkflow(\n structure=structure_opt.copy(),\n num_points=11,\n vol_range=0.10,\n # fit_type='birchmurnaghan',\n interaction_range=10,\n factor=VaspToTHz,\n displacement=0.01,\n dos_mesh=20,\n primitive_matrix=None,\n number_of_snapshots=None,\n)\nstructure_dict = workflow_qh.generate_structures()\nstructure_dict","metadata":{"trusted":true},"execution_count":9,"outputs":[{"execution_count":9,"output_type":"execute_result","data":{"text/plain":"{'calc_energy': {0.9: Atoms(symbols='Al108', pbc=True, cell=[[11.7229062192894, 7.178209789078681e-16, 7.178209789078681e-16], [0.0, 11.7229062192894, 7.178209789078681e-16], [0.0, 0.0, 11.7229062192894]]),\n 0.92: Atoms(symbols='Al108', pbc=True, cell=[[11.80910715486485, 7.230992638996672e-16, 7.230992638996672e-16], [0.0, 11.80910715486485, 7.230992638996672e-16], [0.0, 0.0, 11.80910715486485]]),\n 0.94: Atoms(symbols='Al108', pbc=True, cell=[[11.894067681419225, 7.283015957446018e-16, 7.283015957446018e-16], [0.0, 11.894067681419225, 7.283015957446018e-16], [0.0, 0.0, 11.894067681419225]]),\n 0.96: Atoms(symbols='Al108', pbc=True, cell=[[11.977831481208684, 7.334306492094308e-16, 7.334306492094308e-16], [0.0, 11.977831481208684, 7.334306492094308e-16], [0.0, 0.0, 11.977831481208684]]),\n 0.98: Atoms(symbols='Al108', pbc=True, cell=[[12.060439826001351, 7.384889514610908e-16, 7.384889514610908e-16], [0.0, 12.060439826001351, 7.384889514610908e-16], [0.0, 0.0, 12.060439826001351]]),\n 1.0: Atoms(symbols='Al108', pbc=True, cell=[[12.141931756274893, 7.434788930393824e-16, 7.434788930393824e-16], [0.0, 12.141931756274893, 7.434788930393824e-16], [0.0, 0.0, 12.141931756274893]]),\n 1.02: Atoms(symbols='Al108', pbc=True, cell=[[12.222344243795412, 7.484027378120565e-16, 7.484027378120565e-16], [0.0, 12.222344243795412, 7.484027378120565e-16], [0.0, 0.0, 12.222344243795412]]),\n 1.04: Atoms(symbols='Al108', pbc=True, cell=[[12.301712339412747, 7.53262632024666e-16, 7.53262632024666e-16], [0.0, 12.301712339412747, 7.53262632024666e-16], [0.0, 0.0, 12.301712339412747]]),\n 1.06: Atoms(symbols='Al108', pbc=True, cell=[[12.38006930767338, 7.580606125432298e-16, 7.580606125432298e-16], [0.0, 12.38006930767338, 7.580606125432298e-16], [0.0, 0.0, 12.38006930767338]]),\n 1.08: Atoms(symbols='Al108', pbc=True, cell=[[12.457446749652004, 7.627986143754963e-16, 7.627986143754963e-16], [0.0, 12.457446749652004, 7.627986143754963e-16], [0.0, 0.0, 12.457446749652004]]),\n 1.1: Atoms(symbols='Al108', pbc=True, cell=[[12.533874715230777, 7.674784775460657e-16, 7.674784775460657e-16], [0.0, 12.533874715230777, 7.674784775460657e-16], [0.0, 0.0, 12.533874715230777]])},\n 'calc_forces': {(0.9,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[11.7229062192894, 7.178209789078681e-16, 7.178209789078681e-16], [0.0, 11.7229062192894, 7.178209789078681e-16], [0.0, 0.0, 11.7229062192894]]),\n (0.92,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[11.80910715486485, 7.230992638996672e-16, 7.230992638996672e-16], [0.0, 11.80910715486485, 7.230992638996672e-16], [0.0, 0.0, 11.80910715486485]]),\n (0.94,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[11.894067681419225, 7.283015957446018e-16, 7.283015957446018e-16], [0.0, 11.894067681419225, 7.283015957446018e-16], [0.0, 0.0, 11.894067681419225]]),\n (0.96,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[11.977831481208684, 7.334306492094308e-16, 7.334306492094308e-16], [0.0, 11.977831481208684, 7.334306492094308e-16], [0.0, 0.0, 11.977831481208684]]),\n (0.98,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.060439826001351, 7.384889514610908e-16, 7.384889514610908e-16], [0.0, 12.060439826001351, 7.384889514610908e-16], [0.0, 0.0, 12.060439826001351]]),\n (1.0,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.141931756274893, 7.434788930393824e-16, 7.434788930393824e-16], [0.0, 12.141931756274893, 7.434788930393824e-16], [0.0, 0.0, 12.141931756274893]]),\n (1.02,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.222344243795412, 7.484027378120565e-16, 7.484027378120565e-16], [0.0, 12.222344243795412, 7.484027378120565e-16], [0.0, 0.0, 12.222344243795412]]),\n (1.04,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.301712339412747, 7.53262632024666e-16, 7.53262632024666e-16], [0.0, 12.301712339412747, 7.53262632024666e-16], [0.0, 0.0, 12.301712339412747]]),\n (1.06,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.38006930767338, 7.580606125432298e-16, 7.580606125432298e-16], [0.0, 12.38006930767338, 7.580606125432298e-16], [0.0, 0.0, 12.38006930767338]]),\n (1.08,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.457446749652004, 7.627986143754963e-16, 7.627986143754963e-16], [0.0, 12.457446749652004, 7.627986143754963e-16], [0.0, 0.0, 12.457446749652004]]),\n (1.1,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.533874715230777, 7.674784775460657e-16, 7.674784775460657e-16], [0.0, 12.533874715230777, 7.674784775460657e-16], [0.0, 0.0, 12.533874715230777]])}}"},"metadata":{}}],"id":"493663b9-ea0c-4234-87ef-8f70774794f4"},{"cell_type":"markdown","source":"In contrast to the previous workflows which only used the `calc_energy` function of the simulation codes the `PhonopyWorkflow`\nand correspondingly also the `QuasiHarmonicWorkflow` require the calculation of the forces `calc_forces` in addition to\nthe calculation of the energy. Still the general steps of the workflow remain the same: ","metadata":{},"id":"9dcd4a1e-7122-4f57-93c1-bd9267084f70"},{"cell_type":"code","source":"result_dict = evaluate_with_lammps(\n task_dict=structure_dict,\n potential_dataframe=potential_dataframe,\n)","metadata":{"trusted":true},"execution_count":10,"outputs":[],"id":"2e96e588-e279-4d6c-8f40-2eafa982933b"},{"cell_type":"markdown","source":"The `structure_dict` is evaluated with the [LAMMPS](https://www.lammps.org/) molecular dynamics simulation code to \ncalculate the corresponding energies and forces. The output is not plotted here as the forces for the 108 atom cells \nresult in 3x108 outputs per cell. Still the structure of the `result_dict` again follows the labels of the `structure_dict`\nas explained before. Finally, in the third step the individual free energy curves at the different temperatures are \nfitted to determine the equilibrium volume at the given temperature using the `analyse_structures()` \nand `get_thermal_properties()` functions:","metadata":{},"id":"8fa40f79-f919-47df-ab07-c9a9dcd04b3d"},{"cell_type":"code","source":"workflow_qh.analyse_structures(output_dict=result_dict)\nthermal_properties_dict_qm = workflow_qh.get_thermal_properties(\n temperatures=np.arange(1, 1500, 50),\n output_keys=[\"free_energy\", \"temperatures\", \"volumes\"],\n quantum_mechanical=True\n)\ntemperatures_qh_qm, volume_qh_qm = thermal_properties_dict_qm[\"temperatures\"], thermal_properties_dict_qm[\"volumes\"]","metadata":{"trusted":true},"execution_count":11,"outputs":[],"id":"371977fd-cd4e-469f-8955-17a2946c8629"},{"cell_type":"markdown","source":"The optimal volume at the different `temperatures` is stored in the `volume_qh_qm` in analogy to the previous section. Here the extension `_qm` indicates that the quantum-mechanical harmonic oszillator is used. ","metadata":{},"id":"6c7145b4-9a55-4212-a34f-a1300f7b440f"},{"cell_type":"code","source":"thermal_properties_dict_cl = workflow_qh.get_thermal_properties(\n temperatures=np.arange(1, 1500, 50),\n output_keys=[\"free_energy\", \"temperatures\", \"volumes\"],\n quantum_mechanical=False,\n)\ntemperatures_qh_cl, volume_qh_cl = thermal_properties_dict_cl[\"temperatures\"], thermal_properties_dict_cl[\"volumes\"]","metadata":{"trusted":true},"execution_count":12,"outputs":[],"id":"70002fc3-2436-43ed-8a4c-0b3c1f9a3812"},{"cell_type":"markdown","source":"For the classical harmonic oszillator the resulting volumes are stored as `volume_qh_cl`. ","metadata":{},"id":"bb0db978-365f-43af-9a20-6ebb58fb8da9"},{"cell_type":"markdown","source":"### Molecular Dynamics\nFinally, the third and most commonly used method to determine the volume expansion is using a molecular dynamics \ncalculation. While the `atomistics` package already includes a `LangevinWorkflow` at this point we use the [Nose-Hoover\nthermostat implemented in LAMMPS](https://docs.lammps.org/fix_nh.html) directly via the LAMMPS calculator interface. ","metadata":{},"id":"eb795fbd-0477-492a-b883-9cb31b58d3e2"},{"cell_type":"code","source":"from atomistics.calculators import calc_molecular_dynamics_thermal_expansion_with_lammps\n\nstructure_md = structure_opt.copy().repeat(11)\nresult_dict = calc_molecular_dynamics_thermal_expansion_with_lammps(\n structure=structure_md, # atomistic structure\n potential_dataframe=potential_dataframe, # interatomic potential defined as pandas.DataFrame \n Tstart=15, # temperature to for initial velocity distribution\n Tstop=1500, # final temperature\n Tstep=5, # temperature step\n Tdamp=0.1, # temperature damping of the thermostat \n run=100, # number of MD steps for each temperature\n thermo=100, # print out from the thermostat\n timestep=0.001, # time step for molecular dynamics \n Pstart=0.0, # initial pressure\n Pstop=0.0, # final pressure \n Pdamp=1.0, # barostat damping \n seed=4928459, # random seed \n dist=\"gaussian\", # Gaussian velocity distribution \n)\ntemperature_md_lst, volume_md_lst = result_dict[\"temperatures\"], result_dict[\"volumes\"]","metadata":{"trusted":true},"execution_count":13,"outputs":[{"name":"stderr","text":"100%|██████████| 298/298 [06:54<00:00, 1.39s/it]\n","output_type":"stream"}],"id":"a41d36c9-34eb-46e0-b713-57941dfb0296"},{"cell_type":"markdown","source":"The `calc_molecular_dynamics_thermal_expansion_with_lammps()` function defines a loop over a vector of temperatures in \n5K steps. For each step 100 molecular dynamics steps are executed before the temperature is again increased by 5K. For \n~280 steps with the Morse Pair Potential this takes approximately 5 minutes on a single core. These simulations can be \nfurther accelerated by adding the `cores` parameter. The increase in computational cost is on the one hand related to \nthe large number of force and energy calls and on the other hand to the size of the atomistic structure, as these \nsimulations are typically executed with >5000 atoms rather than the 4 or 108 atoms in the other approximations. The \nvolume for the individual temperatures is stored in the `volume_md_lst` list. ","metadata":{},"id":"d2efeb52-ee54-4eb0-878a-184f353941bf"},{"cell_type":"markdown","source":"### Summary\nTo visually compare the thermal expansion predicted by the three different approximations, the [matplotlib](https://matplotlib.org)\nis used to plot the volume over the temperature:","metadata":{},"id":"eff137a4-61fc-4cbe-8c60-b0dc534a5f3f"},{"cell_type":"code","source":"import matplotlib.pyplot as plt\nplt.plot(temperature_md_lst, np.array(volume_md_lst)/len(structure_md) * len(structure_opt), label=\"Molecular Dynamics\", color=\"C2\")\nplt.plot(temperatures_qh_qm, volume_qh_qm, label=\"Quasi-Harmonic (qm)\", color=\"C3\")\nplt.plot(temperatures_qh_cl, volume_qh_cl, label=\"Quasi-Harmonic (classic)\", color=\"C0\")\nplt.plot(temperatures_ev, volume_ev, label=\"Moruzzi Model\", color=\"C1\")\nplt.axhline(structure_opt.get_volume(), linestyle=\"--\", color=\"red\")\nplt.legend()\nplt.xlabel(\"Temperature (K)\")\nplt.ylabel(\"Volume ($\\AA^3$)\")","metadata":{"trusted":true},"execution_count":14,"outputs":[{"execution_count":14,"output_type":"execute_result","data":{"text/plain":"Text(0, 0.5, 'Volume ($\\\\AA^3$)')"},"metadata":{}},{"output_type":"display_data","data":{"text/plain":"
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"},"metadata":{}}],"id":"da8f641d-c5e6-4c10-8aeb-c891109e2e6d"},{"cell_type":"markdown","source":"Both the [Moruzzi, V. L. et al.](https://link.aps.org/doi/10.1103/PhysRevB.37.790) and the quantum mechanical version of the quasi-harmonic approach start at a larger equilibrium volume as they include the zero point vibrations, resulting in an over-prediction of the volume expansion with increasing temperature. The equilibrium volume is indicated by the dashed red line. Finally, the quasi-harmonic approach with the classical harmonic oszillator agrees very well with the thermal expansion calculated from molecular dynamics for this example of using the Morse Pair Potential. ","metadata":{},"id":"03887d0e-da24-49ca-9bd8-9452fd666b3c"},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[],"id":"e7aeb2f2-12c5-492a-a821-384b030b4a68"}]} +{ + "cells": [ + { + "cell_type": "markdown", + "id": "ce2efe0c-f86c-4cbd-ab3f-2aae9c5a574d", + "metadata": {}, + "source": "## Thermal Expansion \nCalculate the thermal expansion for a Morse Pair potential using the [LAMMPS](https://www.lammps.org/) molecular dynamics\nsimulation code. In the following three methods to calculate the thermal expansion are introduced and compared for a \nMorse Pair Potential for Aluminium. \n\nAs a first step the potential is defined for the [LAMMPS](https://www.lammps.org/) molecular dynamics simulation code \nby specifying the `pair_style` and `pair_coeff` commands for the [Morse Pair Potential](https://docs.lammps.org/pair_morse.html)\nas well as the Aluminium bulk structure: " + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "7a96bac5-5afe-4924-90e5-04f6e6b2bedb", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "from ase.build import bulk\n", + "import pandas\n", + "\n", + "potential_dataframe = pandas.DataFrame(\n", + " {\n", + " \"Config\": [\n", + " [\"pair_style morse/smooth/linear 9.0\", \"pair_coeff * * 0.5 1.8 2.95\"]\n", + " ],\n", + " \"Filename\": [[]],\n", + " \"Model\": [\"Morse\"],\n", + " \"Name\": [\"Morse\"],\n", + " \"Species\": [[\"Al\"]],\n", + " }\n", + ")\n", + "\n", + "structure = bulk(\"Al\", cubic=True)" + ] + }, + { + "cell_type": "markdown", + "id": "fe980834-e174-464a-8c07-04db9889a8c6", + "metadata": {}, + "source": "The `pandas.DataFrame` based format to specify interatomic potentials is the same `pylammpsmpi` uses to interface with \nthe [NIST database for interatomic potentials](https://www.ctcms.nist.gov/potentials). In comparison to just providing\nthe `pair_style` and `pair_coeff` commands, this extended format enables referencing specific files for the interatomic\npotentials `\"Filename\": [[]],` as well as the atomic species `\"Species\": [[\"Al\"]],` to enable consistency checks if the \ninteratomic potential implements all the interactions to simulate a given atomic structure. " + }, + { + "cell_type": "markdown", + "id": "b825e555-5e3d-43c2-8c51-50207ead60b5", + "metadata": {}, + "source": "Finally, the last step of the preparation before starting the actual calculation is optimizing the interatomic structure. \nWhile for the Morse potential used in this example this is not necessary, it is essential for extending this example to\nother interactomic potentials. For the structure optimization the `optimize_positions_and_volume()` function is imported\nand applied on the `ase.atoms.Atoms` bulk structure for Aluminium:" + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "7bd4ed1a-bffe-40f9-99f8-706797418877", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "{'optimize_positions_and_volume': Atoms(symbols='Al4', pbc=True, cell=[4.05, 4.05, 4.05])}" + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from atomistics.workflows import optimize_positions_and_volume\n", + "\n", + "task_dict = optimize_positions_and_volume(structure=structure)\n", + "task_dict" + ] + }, + { + "cell_type": "markdown", + "id": "ed380b51-efa8-4ebb-bb27-b4aca90b21ec", + "metadata": {}, + "source": "It returns a `task_dict` with a single task, the optimization of the positions and the volume of the Aluminium structure.\nThis task is executed with the [LAMMPS](https://www.lammps.org/) molecular dynamics simulation code using the \n`evaluate_with_lammps()` function:" + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "991eaf43-0c4b-4ca2-8494-2b11684f4a79", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "[jupyter-pyiron-2datomistics-2djetdbyfr:00796] mca_base_component_repository_open: unable to open mca_btl_openib: librdmacm.so.1: cannot open shared object file: No such file or directory (ignored)\n/srv/conda/envs/notebook/lib/python3.10/site-packages/pylammpsmpi/wrapper/ase.py:165: UserWarning: Warning: setting upper trangular matrix might slow down the calculation\n warnings.warn(\n" + }, + { + "data": { + "text/plain": "Atoms(symbols='Al4', pbc=True, cell=[[4.047310585424964, 2.478262976797941e-16, 2.478262976797941e-16], [0.0, 4.047310585424964, 2.478262976797941e-16], [0.0, 0.0, 4.047310585424964]])" + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from atomistics.calculators import evaluate_with_lammps\n", + "\n", + "result_dict = evaluate_with_lammps(\n", + " task_dict=task_dict,\n", + " potential_dataframe=potential_dataframe,\n", + ")\n", + "structure_opt = result_dict[\"structure_with_optimized_positions_and_volume\"]\n", + "structure_opt" + ] + }, + { + "cell_type": "markdown", + "id": "6750cc4c-106f-4066-80ad-860bf6980732", + "metadata": {}, + "source": "The `result_dict` just contains a single element, the `ase.atoms.Atoms` structure object with optimized positions and \nvolume. After this step the preparation is completed and the three different approximations can be compared in the following." + }, + { + "cell_type": "markdown", + "id": "6c120581-efd6-4204-8413-75ee81065db1", + "metadata": {}, + "source": "### Equation of State \nThe first approximation to calculate the thermal expansion is based on the Equation of State derived by [Moruzzi, V. L. et al.](https://link.aps.org/doi/10.1103/PhysRevB.37.790).\nSo in analogy to the previous example of calculating the elastic properties from the Equation of State, the `EnergyVolumeCurveWorkflow`\nis initialized with the default parameters: " + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "b69b6ee2-b526-4913-a6c7-36018e8960af", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "{'calc_energy': OrderedDict([(0.95,\n Atoms(symbols='Al4', pbc=True, cell=[[3.9786988461213992, 2.43625040333692e-16, 2.43625040333692e-16], [0.0, 3.9786988461213992, 2.43625040333692e-16], [0.0, 0.0, 3.9786988461213992]])),\n (0.96,\n Atoms(symbols='Al4', pbc=True, cell=[[3.992610493736228, 2.4447688306981026e-16, 2.4447688306981026e-16], [0.0, 3.992610493736228, 2.4447688306981026e-16], [0.0, 0.0, 3.992610493736228]])),\n (0.97,\n Atoms(symbols='Al4', pbc=True, cell=[[4.00642586504517, 2.4532283058243666e-16, 2.4532283058243666e-16], [0.0, 4.00642586504517, 2.4532283058243666e-16], [0.0, 0.0, 4.00642586504517]])),\n (0.98,\n Atoms(symbols='Al4', pbc=True, cell=[[4.020146608667117, 2.461629838203636e-16, 2.461629838203636e-16], [0.0, 4.020146608667117, 2.461629838203636e-16], [0.0, 0.0, 4.020146608667117]])),\n (0.99,\n Atoms(symbols='Al4', pbc=True, cell=[[4.033774328510742, 2.469974409946722e-16, 2.469974409946722e-16], [0.0, 4.033774328510742, 2.469974409946722e-16], [0.0, 0.0, 4.033774328510742]])),\n (1.0,\n Atoms(symbols='Al4', pbc=True, cell=[[4.047310585424964, 2.478262976797941e-16, 2.478262976797941e-16], [0.0, 4.047310585424964, 2.478262976797941e-16], [0.0, 0.0, 4.047310585424964]])),\n (1.01,\n Atoms(symbols='Al4', pbc=True, cell=[[4.060756898772644, 2.486496469098726e-16, 2.486496469098726e-16], [0.0, 4.060756898772644, 2.486496469098726e-16], [0.0, 0.0, 4.060756898772644]])),\n (1.02,\n Atoms(symbols='Al4', pbc=True, cell=[[4.074114747931804, 2.494675792706855e-16, 2.494675792706855e-16], [0.0, 4.074114747931804, 2.494675792706855e-16], [0.0, 0.0, 4.074114747931804]])),\n (1.03,\n Atoms(symbols='Al4', pbc=True, cell=[[4.087385573728375, 2.5028018298737613e-16, 2.5028018298737613e-16], [0.0, 4.087385573728375, 2.5028018298737613e-16], [0.0, 0.0, 4.087385573728375]])),\n (1.04,\n Atoms(symbols='Al4', pbc=True, cell=[[4.100570779804249, 2.51087544008222e-16, 2.51087544008222e-16], [0.0, 4.100570779804249, 2.51087544008222e-16], [0.0, 0.0, 4.100570779804249]])),\n (1.05,\n Atoms(symbols='Al4', pbc=True, cell=[[4.113671733924125, 2.518897460846561e-16, 2.518897460846561e-16], [0.0, 4.113671733924125, 2.518897460846561e-16], [0.0, 0.0, 4.113671733924125]]))])}" + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from atomistics.workflows import EnergyVolumeCurveWorkflow\n", + "\n", + "workflow_ev = EnergyVolumeCurveWorkflow(\n", + " structure=structure_opt.copy(),\n", + " num_points=11,\n", + " fit_type=\"birchmurnaghan\",\n", + " vol_range=0.05,\n", + " axes=[\"x\", \"y\", \"z\"],\n", + " strains=None,\n", + ")\n", + "structure_dict = workflow_ev.generate_structures()\n", + "structure_dict" + ] + }, + { + "cell_type": "markdown", + "id": "8f5d1e8d-0204-4dca-9298-878b9b2f6406", + "metadata": {}, + "source": "After the initialization the `generate_structures()` function is called to generate the atomistic structures which are\nthen in the second step evaluated with the [LAMMPS](https://www.lammps.org/) molecular dynamics simulation code to derive\nthe equilibrium properties:" + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "7d1f126e-4fd0-41c5-986b-91d3b5910e3e", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "{'energy': {0.95: -14.609207927145926,\n 0.96: -14.656740101454448,\n 0.97: -14.692359030099395,\n 0.98: -14.716883724875528,\n 0.99: -14.731079276327009,\n 1.0: -14.735659820057942,\n 1.01: -14.731295089579728,\n 1.02: -14.718611862249286,\n 1.03: -14.698196715842329,\n 1.04: -14.670598736769112,\n 1.05: -14.636332030744796}}" + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result_dict = evaluate_with_lammps(\n", + " task_dict=structure_dict, potential_dataframe=potential_dataframe\n", + ")\n", + "result_dict" + ] + }, + { + "cell_type": "markdown", + "id": "fb679eb1-338f-4485-a953-791e147fe632", + "metadata": {}, + "source": "While in the previous example the fit of the energy volume curve was used directly, here the output of the fit, in\nparticular the derived equilibrium properties are the input for the Debye model as defined by [Moruzzi, V. L. et al.](https://link.aps.org/doi/10.1103/PhysRevB.37.790):" + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2e0f7aab-6744-4b6f-a454-38c28833a3ac", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "66.29787349319821" + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "structure_opt.get_volume()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "11c8b18d-64ff-4c93-b646-668b00eb1cf8", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "{'b_prime_eq': 6.2365371733275845,\n 'bulkmodul_eq': 216.057292780608,\n 'volume_eq': 66.29790137569191,\n 'energy_eq': -14.735658078942949,\n 'fit_dict': {'fit_type': 'birchmurnaghan',\n 'least_square_error': array([8.12779273e-07, 2.83453476e-03, 1.45091623e-03, 3.00518393e-05])},\n 'energy': [-14.609207927145926,\n -14.656740101454448,\n -14.692359030099395,\n -14.716883724875528,\n -14.731079276327009,\n -14.735659820057942,\n -14.731295089579728,\n -14.718611862249286,\n -14.698196715842329,\n -14.670598736769112,\n -14.636332030744796],\n 'volume': [62.98297981853827,\n 63.645958553470244,\n 64.30893728840229,\n 64.97191602333424,\n 65.63489475826624,\n 66.29787349319821,\n 66.96085222813018,\n 67.62383096306218,\n 68.28680969799419,\n 68.94978843292616,\n 69.61276716785807]}" + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fit_dict = workflow_ev.analyse_structures(output_dict=result_dict)\n", + "fit_dict" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "9c7cd51c-6058-4d1d-8948-56d29c3b13e7", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "/srv/conda/envs/notebook/lib/python3.10/site-packages/atomistics/workflows/evcurve/debye.py:80: RuntimeWarning: overflow encountered in exp\n return xi**3 / (np.exp(xi) - 1)\n" + } + ], + "source": [ + "import numpy as np\n", + "\n", + "workflow_ev.analyse_structures(output_dict=result_dict)\n", + "thermal_properties_dict = workflow_ev.get_thermal_properties(\n", + " temperatures=np.arange(1, 1500, 50),\n", + " output_keys=[\"temperatures\", \"volumes\"],\n", + ")\n", + "temperatures_ev, volume_ev = (\n", + " thermal_properties_dict[\"temperatures\"],\n", + " thermal_properties_dict[\"volumes\"],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "35ab7b86-0688-4520-ad47-ea54b4bfde86", + "metadata": {}, + "source": "The output of the Debye model provides the change of the temperature specific optimal volume `volume_ev`\nwhich can be plotted over the temperature `temperatures_ev` to determine the thermal expansion. " + }, + { + "cell_type": "markdown", + "id": "88ccd1f0-98c5-4e13-ab2c-febe5d3f235b", + "metadata": {}, + "source": "### Quasi-Harmonic Approximation \nWhile the [Moruzzi, V. L. et al.](https://link.aps.org/doi/10.1103/PhysRevB.37.790) approach based on the Einstein crystal\nis limited to a single frequency, the quasi-harmonic model includes the volume dependent free energy. Inside the \n`atomistics` package the harmonic and quasi-harmonic model are implemented based on an interface to the [Phonopy](https://phonopy.github.io/phonopy/)\nframework. Still the user interface is still structured in the same three steps of (1) generating structures, (2) evaluating \nthese structures and (3) fitting the corresponding model. Starting with the initialization of the `QuasiHarmonicWorkflow`\nwhich combines the `PhonopyWorkflow` with the `EnergyVolumeCurveWorkflow`:" + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "493663b9-ea0c-4234-87ef-8f70774794f4", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "{'calc_energy': {0.9: Atoms(symbols='Al108', pbc=True, cell=[[11.7229062192894, 7.178209789078681e-16, 7.178209789078681e-16], [0.0, 11.7229062192894, 7.178209789078681e-16], [0.0, 0.0, 11.7229062192894]]),\n 0.92: Atoms(symbols='Al108', pbc=True, cell=[[11.80910715486485, 7.230992638996672e-16, 7.230992638996672e-16], [0.0, 11.80910715486485, 7.230992638996672e-16], [0.0, 0.0, 11.80910715486485]]),\n 0.94: Atoms(symbols='Al108', pbc=True, cell=[[11.894067681419225, 7.283015957446018e-16, 7.283015957446018e-16], [0.0, 11.894067681419225, 7.283015957446018e-16], [0.0, 0.0, 11.894067681419225]]),\n 0.96: Atoms(symbols='Al108', pbc=True, cell=[[11.977831481208684, 7.334306492094308e-16, 7.334306492094308e-16], [0.0, 11.977831481208684, 7.334306492094308e-16], [0.0, 0.0, 11.977831481208684]]),\n 0.98: Atoms(symbols='Al108', pbc=True, cell=[[12.060439826001351, 7.384889514610908e-16, 7.384889514610908e-16], [0.0, 12.060439826001351, 7.384889514610908e-16], [0.0, 0.0, 12.060439826001351]]),\n 1.0: Atoms(symbols='Al108', pbc=True, cell=[[12.141931756274893, 7.434788930393824e-16, 7.434788930393824e-16], [0.0, 12.141931756274893, 7.434788930393824e-16], [0.0, 0.0, 12.141931756274893]]),\n 1.02: Atoms(symbols='Al108', pbc=True, cell=[[12.222344243795412, 7.484027378120565e-16, 7.484027378120565e-16], [0.0, 12.222344243795412, 7.484027378120565e-16], [0.0, 0.0, 12.222344243795412]]),\n 1.04: Atoms(symbols='Al108', pbc=True, cell=[[12.301712339412747, 7.53262632024666e-16, 7.53262632024666e-16], [0.0, 12.301712339412747, 7.53262632024666e-16], [0.0, 0.0, 12.301712339412747]]),\n 1.06: Atoms(symbols='Al108', pbc=True, cell=[[12.38006930767338, 7.580606125432298e-16, 7.580606125432298e-16], [0.0, 12.38006930767338, 7.580606125432298e-16], [0.0, 0.0, 12.38006930767338]]),\n 1.08: Atoms(symbols='Al108', pbc=True, cell=[[12.457446749652004, 7.627986143754963e-16, 7.627986143754963e-16], [0.0, 12.457446749652004, 7.627986143754963e-16], [0.0, 0.0, 12.457446749652004]]),\n 1.1: Atoms(symbols='Al108', pbc=True, cell=[[12.533874715230777, 7.674784775460657e-16, 7.674784775460657e-16], [0.0, 12.533874715230777, 7.674784775460657e-16], [0.0, 0.0, 12.533874715230777]])},\n 'calc_forces': {(0.9,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[11.7229062192894, 7.178209789078681e-16, 7.178209789078681e-16], [0.0, 11.7229062192894, 7.178209789078681e-16], [0.0, 0.0, 11.7229062192894]]),\n (0.92,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[11.80910715486485, 7.230992638996672e-16, 7.230992638996672e-16], [0.0, 11.80910715486485, 7.230992638996672e-16], [0.0, 0.0, 11.80910715486485]]),\n (0.94,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[11.894067681419225, 7.283015957446018e-16, 7.283015957446018e-16], [0.0, 11.894067681419225, 7.283015957446018e-16], [0.0, 0.0, 11.894067681419225]]),\n (0.96,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[11.977831481208684, 7.334306492094308e-16, 7.334306492094308e-16], [0.0, 11.977831481208684, 7.334306492094308e-16], [0.0, 0.0, 11.977831481208684]]),\n (0.98,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.060439826001351, 7.384889514610908e-16, 7.384889514610908e-16], [0.0, 12.060439826001351, 7.384889514610908e-16], [0.0, 0.0, 12.060439826001351]]),\n (1.0,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.141931756274893, 7.434788930393824e-16, 7.434788930393824e-16], [0.0, 12.141931756274893, 7.434788930393824e-16], [0.0, 0.0, 12.141931756274893]]),\n (1.02,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.222344243795412, 7.484027378120565e-16, 7.484027378120565e-16], [0.0, 12.222344243795412, 7.484027378120565e-16], [0.0, 0.0, 12.222344243795412]]),\n (1.04,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.301712339412747, 7.53262632024666e-16, 7.53262632024666e-16], [0.0, 12.301712339412747, 7.53262632024666e-16], [0.0, 0.0, 12.301712339412747]]),\n (1.06,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.38006930767338, 7.580606125432298e-16, 7.580606125432298e-16], [0.0, 12.38006930767338, 7.580606125432298e-16], [0.0, 0.0, 12.38006930767338]]),\n (1.08,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.457446749652004, 7.627986143754963e-16, 7.627986143754963e-16], [0.0, 12.457446749652004, 7.627986143754963e-16], [0.0, 0.0, 12.457446749652004]]),\n (1.1,\n 0): Atoms(symbols='Al108', pbc=True, cell=[[12.533874715230777, 7.674784775460657e-16, 7.674784775460657e-16], [0.0, 12.533874715230777, 7.674784775460657e-16], [0.0, 0.0, 12.533874715230777]])}}" + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from atomistics.workflows import QuasiHarmonicWorkflow\n", + "from phonopy.units import VaspToTHz\n", + "\n", + "workflow_qh = QuasiHarmonicWorkflow(\n", + " structure=structure_opt.copy(),\n", + " num_points=11,\n", + " vol_range=0.10,\n", + " # fit_type='birchmurnaghan',\n", + " interaction_range=10,\n", + " factor=VaspToTHz,\n", + " displacement=0.01,\n", + " dos_mesh=20,\n", + " primitive_matrix=None,\n", + " number_of_snapshots=None,\n", + ")\n", + "structure_dict = workflow_qh.generate_structures()\n", + "structure_dict" + ] + }, + { + "cell_type": "markdown", + "id": "9dcd4a1e-7122-4f57-93c1-bd9267084f70", + "metadata": {}, + "source": "In contrast to the previous workflows which only used the `calc_energy` function of the simulation codes the `PhonopyWorkflow`\nand correspondingly also the `QuasiHarmonicWorkflow` require the calculation of the forces `calc_forces` in addition to\nthe calculation of the energy. Still the general steps of the workflow remain the same: " + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "2e96e588-e279-4d6c-8f40-2eafa982933b", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "result_dict = evaluate_with_lammps(\n", + " task_dict=structure_dict,\n", + " potential_dataframe=potential_dataframe,\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "8fa40f79-f919-47df-ab07-c9a9dcd04b3d", + "metadata": {}, + "source": "The `structure_dict` is evaluated with the [LAMMPS](https://www.lammps.org/) molecular dynamics simulation code to \ncalculate the corresponding energies and forces. The output is not plotted here as the forces for the 108 atom cells \nresult in 3x108 outputs per cell. Still the structure of the `result_dict` again follows the labels of the `structure_dict`\nas explained before. Finally, in the third step the individual free energy curves at the different temperatures are \nfitted to determine the equilibrium volume at the given temperature using the `analyse_structures()` \nand `get_thermal_properties()` functions:" + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "371977fd-cd4e-469f-8955-17a2946c8629", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "workflow_qh.analyse_structures(output_dict=result_dict)\n", + "thermal_properties_dict_qm = workflow_qh.get_thermal_properties(\n", + " temperatures=np.arange(1, 1500, 50),\n", + " output_keys=[\"free_energy\", \"temperatures\", \"volumes\"],\n", + " quantum_mechanical=True,\n", + ")\n", + "temperatures_qh_qm, volume_qh_qm = (\n", + " thermal_properties_dict_qm[\"temperatures\"],\n", + " thermal_properties_dict_qm[\"volumes\"],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "6c7145b4-9a55-4212-a34f-a1300f7b440f", + "metadata": {}, + "source": "The optimal volume at the different `temperatures` is stored in the `volume_qh_qm` in analogy to the previous section. Here the extension `_qm` indicates that the quantum-mechanical harmonic oszillator is used. " + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "70002fc3-2436-43ed-8a4c-0b3c1f9a3812", + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "thermal_properties_dict_cl = workflow_qh.get_thermal_properties(\n", + " temperatures=np.arange(1, 1500, 50),\n", + " output_keys=[\"free_energy\", \"temperatures\", \"volumes\"],\n", + " quantum_mechanical=False,\n", + ")\n", + "temperatures_qh_cl, volume_qh_cl = (\n", + " thermal_properties_dict_cl[\"temperatures\"],\n", + " thermal_properties_dict_cl[\"volumes\"],\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "bb0db978-365f-43af-9a20-6ebb58fb8da9", + "metadata": {}, + "source": "For the classical harmonic oszillator the resulting volumes are stored as `volume_qh_cl`. " + }, + { + "cell_type": "markdown", + "id": "eb795fbd-0477-492a-b883-9cb31b58d3e2", + "metadata": {}, + "source": "### Molecular Dynamics\nFinally, the third and most commonly used method to determine the volume expansion is using a molecular dynamics \ncalculation. While the `atomistics` package already includes a `LangevinWorkflow` at this point we use the [Nose-Hoover\nthermostat implemented in LAMMPS](https://docs.lammps.org/fix_nh.html) directly via the LAMMPS calculator interface. " + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "a41d36c9-34eb-46e0-b713-57941dfb0296", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": "100%|██████████| 298/298 [06:54<00:00, 1.39s/it]\n" + } + ], + "source": [ + "from atomistics.calculators import calc_molecular_dynamics_thermal_expansion_with_lammps\n", + "\n", + "structure_md = structure_opt.copy().repeat(11)\n", + "result_dict = calc_molecular_dynamics_thermal_expansion_with_lammps(\n", + " structure=structure_md, # atomistic structure\n", + " potential_dataframe=potential_dataframe, # interatomic potential defined as pandas.DataFrame\n", + " Tstart=15, # temperature to for initial velocity distribution\n", + " Tstop=1500, # final temperature\n", + " Tstep=5, # temperature step\n", + " Tdamp=0.1, # temperature damping of the thermostat\n", + " run=100, # number of MD steps for each temperature\n", + " thermo=100, # print out from the thermostat\n", + " timestep=0.001, # time step for molecular dynamics\n", + " Pstart=0.0, # initial pressure\n", + " Pstop=0.0, # final pressure\n", + " Pdamp=1.0, # barostat damping\n", + " seed=4928459, # random seed\n", + " dist=\"gaussian\", # Gaussian velocity distribution\n", + ")\n", + "temperature_md_lst, volume_md_lst = result_dict[\"temperatures\"], result_dict[\"volumes\"]" + ] + }, + { + "cell_type": "markdown", + "id": "d2efeb52-ee54-4eb0-878a-184f353941bf", + "metadata": {}, + "source": "The `calc_molecular_dynamics_thermal_expansion_with_lammps()` function defines a loop over a vector of temperatures in \n5K steps. For each step 100 molecular dynamics steps are executed before the temperature is again increased by 5K. For \n~280 steps with the Morse Pair Potential this takes approximately 5 minutes on a single core. These simulations can be \nfurther accelerated by adding the `cores` parameter. The increase in computational cost is on the one hand related to \nthe large number of force and energy calls and on the other hand to the size of the atomistic structure, as these \nsimulations are typically executed with >5000 atoms rather than the 4 or 108 atoms in the other approximations. The \nvolume for the individual temperatures is stored in the `volume_md_lst` list. " + }, + { + "cell_type": "markdown", + "id": "eff137a4-61fc-4cbe-8c60-b0dc534a5f3f", + "metadata": {}, + "source": "### Summary\nTo visually compare the thermal expansion predicted by the three different approximations, the [matplotlib](https://matplotlib.org)\nis used to plot the volume over the temperature:" + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "da8f641d-c5e6-4c10-8aeb-c891109e2e6d", + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": "Text(0, 0.5, 'Volume ($\\\\AA^3$)')" + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "plt.plot(\n", + " temperature_md_lst,\n", + " np.array(volume_md_lst) / len(structure_md) * len(structure_opt),\n", + " label=\"Molecular Dynamics\",\n", + " color=\"C2\",\n", + ")\n", + "plt.plot(temperatures_qh_qm, volume_qh_qm, label=\"Quasi-Harmonic (qm)\", color=\"C3\")\n", + "plt.plot(temperatures_qh_cl, volume_qh_cl, label=\"Quasi-Harmonic (classic)\", color=\"C0\")\n", + "plt.plot(temperatures_ev, volume_ev, label=\"Moruzzi Model\", color=\"C1\")\n", + "plt.axhline(structure_opt.get_volume(), linestyle=\"--\", color=\"red\")\n", + "plt.legend()\n", + "plt.xlabel(\"Temperature (K)\")\n", + "plt.ylabel(\"Volume ($\\AA^3$)\")" + ] + }, + { + "cell_type": "markdown", + "id": "03887d0e-da24-49ca-9bd8-9452fd666b3c", + "metadata": {}, + "source": "Both the [Moruzzi, V. L. et al.](https://link.aps.org/doi/10.1103/PhysRevB.37.790) and the quantum mechanical version of the quasi-harmonic approach start at a larger equilibrium volume as they include the zero point vibrations, resulting in an over-prediction of the volume expansion with increasing temperature. The equilibrium volume is indicated by the dashed red line. Finally, the quasi-harmonic approach with the classical harmonic oszillator agrees very well with the thermal expansion calculated from molecular dynamics for this example of using the Morse Pair Potential. " + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e7aeb2f2-12c5-492a-a821-384b030b4a68", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}