py-sc-fermi

py-sc-fermi is a materials modelling code for calculating self-consistent Fermi energies and defect concentrations under thermodynamic equilibrium (or quasi-equilibrium) in the dilute limit given pre-calculated defect formation energies. For the theory, see this paper.

The necessary inputs are (charged) defect formation energies, an (electronic) density of states, and the volume of the unit cell. Having this data, a DefectSystem object can be inititalised, from which the self consistent Fermi energy, defect concentrations, defect transition levels and electron and hole concentrations can be calculated.

Documentation and usage guides can be found here.

Installation

py-sc-fermi can be installed with pip:

pip install py-sc-fermi

Alternatively, the latest development build can be installed by cloning this repository and installing with pip:

git clone https://github.com/bjmorgan/py-sc-fermi.git
cd py-sc-fermi
pip install .

Contributing

Bugs reports and feature requests

If you think you've found a bug, please report it on the issue tracker. This is also the place to propose ideas for new features or ask questions about the design of py-sc-fermi. Poor documentation is considered a bug, but please be as specific as possible when asking for improvements.

Code contributions

We welcome help in improving the package with your external contributions. This is managed through Github pull requests; for external contributions fork and pull is preferred:

1. First open an Issue to discuss the proposed contribution. This discussion might include how the changes fit py-sc-fermi scope and a general technical approach.
2. Make your own project fork and implement the changes there.
3. Open a pull request to merge the changes into the main project. A more detailed discussion can take place there before the changes are accepted.

Citing

If you use py-sc-fermi in your work, please consider citing the following:

• the paper associated with the py-sc-fermi
• the paper associated with the FORTRAN code SC-Fermi on which this code was initially based, which provides an excellent discussion of the underlying theory.