diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
index 6dd1076..3f95bd5 100644
--- a/.devcontainer/devcontainer.json
+++ b/.devcontainer/devcontainer.json
@@ -36,7 +36,9 @@
                 "ms-python.pylint",
                 "ms-python.black-formatter",
                 "ms-python.flake8",
-                "ms-python.pylint"
+                "ms-python.pylint",
+                "GitHub.copilot",
+                "GitHub.copilot-chat"
             ]
         }
     },
diff --git a/examples/CO2deprezzurizing.py b/examples/CO2deprezzurizing.py
index ae77a21..4d1db83 100644
--- a/examples/CO2deprezzurizing.py
+++ b/examples/CO2deprezzurizing.py
@@ -1,5 +1,21 @@
 # -*- coding: utf-8 -*-
 """
+This script demonstrates the process of CO2 depressurization using the NeqSim library.
+
+The script performs the following steps:
+1. Creates a fluid object using the SRK equation of state.
+2. Adds 100 moles of CO2 to the fluid.
+3. Sets the initial temperature to -25°C and pressure to 18 bara.
+4. Enables multi-phase and solid-phase checks for CO2.
+5. Performs a temperature-pressure (TP) flash calculation.
+6. Calculates the bubble point temperature.
+7. Prints the fluid properties before depressurization.
+8. Initializes the fluid properties and calculates the enthalpy.
+9. Sets the pressure to 1 bara and performs a pressure-enthalpy (PH) flash calculation.
+10. Prints the fluid properties after depressurization.
+
+The script also includes commented-out lines for performing dew point and solid phase flash calculations.
+
 Created on Tue Jun 23 10:37:26 2020
 
 @author: ESOL
diff --git a/examples/CarnotCycle.py b/examples/CarnotCycle.py
index 1c316ad..22b376d 100644
--- a/examples/CarnotCycle.py
+++ b/examples/CarnotCycle.py
@@ -1,5 +1,42 @@
 # -*- coding: utf-8 -*-
 """
+This script simulates a Carnot cycle using the neqsim library for thermodynamic calculations.
+
+The Carnot cycle consists of four main processes:
+1. Isothermal Expansion (1-2): Heat is transferred reversibly from a high-temperature reservoir at constant temperature.
+2. Isentropic Expansion (2-3): Reversible adiabatic expansion of the gas, resulting in work output.
+3. Isothermal Compression (3-4): Heat is transferred reversibly to a low-temperature reservoir at constant temperature.
+4. Adiabatic Reversible Compression (4-1): The gas is compressed adiabatically and reversibly.
+
+The script performs the following steps:
+1. Initializes a fluid at thermodynamic equilibrium with specified components and conditions.
+2. Simulates the isothermal expansion process and calculates the state properties.
+3. Simulates the isentropic expansion process and calculates the state properties.
+4. Simulates the isothermal compression process and calculates the state properties.
+5. Simulates the adiabatic reversible compression process and calculates the state properties.
+6. Calculates the Carnot efficiency based on the heat transferred during the cycle.
+7. Plots the pressure-volume (PV) and temperature-entropy (TS) diagrams for the Carnot cycle.
+
+Variables:
+- P1: Initial pressure in bara.
+- T_hot: High temperature in Celsius.
+- T_cold: Low temperature in Celsius.
+- fluid_1: Thermodynamic fluid object.
+- T1, T2, T3, T4, T5: Temperatures at different states in Celsius.
+- P2, P3, P4, P5: Pressures at different states in bara.
+- H1, H2, H3, H4, H5: Enthalpies at different states in kJ/kg.
+- U1, U2, U3, U4, U5: Internal energies at different states in kJ/kg.
+- S1, S2, S3, S4, S5: Entropies at different states in kJ/kgK.
+- V1, V2, V3, V4, V5: Volumes at different states in m3.
+- dS: Change in entropy between states 1 and 2 in kJ/kgK.
+- QH: Heat added during the isothermal expansion in kJ.
+- QC: Heat rejected during the isothermal compression in kJ.
+- efficiency: Calculated Carnot efficiency.
+- efficiency2: Theoretical Carnot efficiency.
+
+Plots:
+- Pressure vs. Volume (PV) diagram.
+- Temperature vs. Entropy (TS) diagram.
 Created on Thu Jan  2 15:49:07 2020
 
 @author: esol
@@ -19,7 +56,7 @@
 fluid_1.setTemperature(T_hot, "C")
 fluid_1.setPressure(P1, "bara")
 TPflash(fluid_1)
-fluid_1.display()
+printFrame(fluid_1)
 T1 = fluid_1.getTemperature("C")
 H1 = fluid_1.getEnthalpy("kJ/kg")
 U1 = fluid_1.getInternalEnergy("kJ/kg")
@@ -30,7 +67,7 @@
 # 1-2: Isothermal Expansion. Heat is transferred reversibly from high temperature reservoir at constant temperature TH (isothermal heat addition or absorption).
 V2 = V1 * 1.5
 TVflash(fluid_1, V2, "m3")
-fluid_1.display()
+printFrame(fluid_1)
 T2 = fluid_1.getTemperature("C")
 P2 = fluid_1.getPressure("bara")
 H2 = fluid_1.getEnthalpy("kJ/kg")
@@ -40,7 +77,7 @@
 # 2-3: Isentropic (reversible adiabatic) expansion of the gas (isentropic work output).
 fluid_1.setTemperature(T_cold, "C")
 TSflash(fluid_1, S2, "kJ/kgK")
-fluid_1.display()
+printFrame(fluid_1)
 
 T3 = fluid_1.getTemperature("C")
 P3 = fluid_1.getPressure()
@@ -59,7 +96,7 @@
 S4 = fluid_1.getEntropy("kJ/kgK")
 V4 = fluid_1.getVolume("m3")
 
-fluid_1.display()
+printFrame(fluid_1)
 # 4-1 Adiabatic reversible compression.
 
 VSflash(fluid_1, V1, S4, "m3", "kJ/kgK")
@@ -69,7 +106,7 @@
 U5 = fluid_1.getInternalEnergy("kJ/kg")
 S5 = fluid_1.getEntropy("kJ/kgK")
 V5 = fluid_1.getVolume("m3")
-fluid_1.display()
+printFrame(fluid_1)
 
 dS = S2 - S1
 QH = (T_hot + 273.15) * dS
diff --git a/examples/compressorCalc.py b/examples/compressorCalc.py
index fee43a7..f846f37 100644
--- a/examples/compressorCalc.py
+++ b/examples/compressorCalc.py
@@ -2,6 +2,7 @@
 """
 Created on Thu Jun  4 10:52:50 2020
 
+
 @author: ESOL
 """
 import pandas as pd
diff --git a/examples/jupyter/examplesInPython.ipynb b/examples/jupyter/examplesInPython.ipynb
index 1d19e9f..87596bf 100644
--- a/examples/jupyter/examplesInPython.ipynb
+++ b/examples/jupyter/examplesInPython.ipynb
@@ -11,21 +11,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "ename": "ModuleNotFoundError",
-     "evalue": "No module named 'neqsim'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[2], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mneqsim\u001b[39;00m\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mnumpy\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mnp\u001b[39;00m\n",
-      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'neqsim'"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import neqsim\n",
     "import matplotlib\n",
@@ -51,8 +39,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Gas enthalpy  1079.4821290144278\n",
-      "Gas viscosity  1.0760998263783299e-05\n"
+      "Gas enthalpy  1079.8561270889081\n",
+      "Gas viscosity  1.0760998263782569e-05\n"
      ]
     }
    ],
@@ -89,14 +77,12 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -178,20 +164,18 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "gas density  74.03007867929436\n",
-      "oil density  712.123693220221\n"
+      "gas density  74.1410489655628\n",
+      "oil density  713.5448551807647\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -256,11 +240,14 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "LP compressor power  2016.953986008122  kW\n",
-      "HP compressor power  10027.680843485874  kW\n"
+     "ename": "AttributeError",
+     "evalue": "Java package 'neqsim.process' has no attribute 'processequipment'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[6], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m processequipment \u001b[38;5;241m=\u001b[39m \u001b[43mjneqsim\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mprocess\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mprocessequipment\u001b[49m\n\u001b[1;32m      3\u001b[0m testSystem \u001b[38;5;241m=\u001b[39m jneqsim\u001b[38;5;241m.\u001b[39mthermo\u001b[38;5;241m.\u001b[39msystem\u001b[38;5;241m.\u001b[39mSystemSrkEos((\u001b[38;5;241m273.15\u001b[39m \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m50.0\u001b[39m), \u001b[38;5;241m50.00\u001b[39m)\n\u001b[1;32m      4\u001b[0m testSystem\u001b[38;5;241m.\u001b[39maddComponent(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmethane\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;241m900.00\u001b[39m)\n",
+      "\u001b[0;31mAttributeError\u001b[0m: Java package 'neqsim.process' has no attribute 'processequipment'"
      ]
     }
    ],
@@ -417,19 +404,87 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
+     "name": "stdout",
      "output_type": "stream",
      "text": [
-      "OpenJDK 64-Bit Server VM warning: Attempt to protect stack guard pages failed.\n",
-      "OpenJDK 64-Bit Server VM warning: Attempt to deallocate stack guard pages failed.\n"
+      "                       0           1           2            3 4 5  \\\n",
+      "0                              total         GAS      AQUEOUS       \n",
+      "1                methane  6.66667E-1  8.13907E-1   5.02515E-9       \n",
+      "2              n-heptane  1.33333E-1  1.62781E-1  1.29701E-25       \n",
+      "3                  water        2E-1   2.3312E-2          1E0       \n",
+      "4                                                                   \n",
+      "5                Density               1.22577E0    1.00172E3       \n",
+      "6         Phase Fraction              8.19095E-1   1.80905E-1       \n",
+      "7             Molar Mass   2.7659E-2   2.9789E-2    1.8015E-2       \n",
+      "8               Z factor              9.93332E-1   7.35079E-4       \n",
+      "9     Heat Capacity (Cp)               1.91919E0    4.81092E0       \n",
+      "10    Heat Capacity (Cv)               1.63218E0    3.53037E0       \n",
+      "11        Speed of Sound               3.10779E2    3.45954E3       \n",
+      "12              Enthalpy  -2.62425E5   4.49999E4    -2.5641E6       \n",
+      "13               Entropy  -5.31475E2   3.13357E2   -6.85667E3       \n",
+      "14        JT coefficient              8.79618E-1  -2.17531E-2       \n",
+      "15                                                                  \n",
+      "16             Viscosity              1.00189E-5   8.91546E-4       \n",
+      "17  Thermal Conductivity              2.67223E-2   6.15036E-1       \n",
+      "18       Surface Tension              7.42648E-2   7.42648E-2       \n",
+      "19                                                                  \n",
+      "20                                                                  \n",
+      "21                                                                  \n",
+      "22              Pressure                 1.01325      1.01325       \n",
+      "23           Temperature                    25.0         25.0       \n",
+      "24                                                                  \n",
+      "25                 Model                 SRK-EOS      SRK-EOS       \n",
+      "26           Mixing Rule                 classic      classic       \n",
+      "27                                                                  \n",
+      "28                Stream                                            \n",
+      "29                                                                  \n",
+      "30                                                                  \n",
+      "31                                                                  \n",
+      "32                                                                  \n",
+      "\n",
+      "                  6  \n",
+      "0                    \n",
+      "1   [mole fraction]  \n",
+      "2   [mole fraction]  \n",
+      "3   [mole fraction]  \n",
+      "4                    \n",
+      "5             kg/m3  \n",
+      "6   [mole fraction]  \n",
+      "7            kg/mol  \n",
+      "8               [-]  \n",
+      "9            kJ/kgK  \n",
+      "10           kJ/kgK  \n",
+      "11            m/sec  \n",
+      "12             J/kg  \n",
+      "13            J/kgK  \n",
+      "14            C/bar  \n",
+      "15                   \n",
+      "16          kg/msec  \n",
+      "17             W/mK  \n",
+      "18            [N/m]  \n",
+      "19                   \n",
+      "20                   \n",
+      "21                   \n",
+      "22             bara  \n",
+      "23                C  \n",
+      "24                   \n",
+      "25                -  \n",
+      "26                -  \n",
+      "27                   \n",
+      "28                -  \n",
+      "29                   \n",
+      "30                   \n",
+      "31                   \n",
+      "32                   \n"
      ]
     }
    ],
    "source": [
+    "from neqsim.thermo import fluid, printFrame\n",
     "fluid1 = fluid(\"srk\")\n",
     "fluid1.addComponent(\"methane\", 10.0)\n",
     "fluid1.addComponent(\"n-heptane\", 2.0)\n",
@@ -437,14 +492,22 @@
     "fluid1.setMixingRule(2)\n",
     "fluid1.setMultiPhaseCheck(True)\n",
     "TPflash(fluid1)\n",
-    "show(fluid1)"
+    "printFrame(fluid1)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "density  0.8659695521155993  kg/m3\n"
+     ]
+    }
+   ],
    "source": [
     "fluid1 = fluid(\"srk\")\n",
     "fluid1.addComponent(\"methane\", 10.0)\n",
@@ -457,18 +520,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
-     "ename": "NameError",
-     "evalue": "name 'fluid' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "\u001b[1;32m/Users/ASMF/Code/neqsimpython/examples/jupyter/examplesInPython.ipynb Cell 18'\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> <a href='vscode-notebook-cell:/Users/ASMF/Code/neqsimpython/examples/jupyter/examplesInPython.ipynb#ch0000017?line=0'>1</a>\u001b[0m fluid1 \u001b[39m=\u001b[39m fluid(\u001b[39m'\u001b[39m\u001b[39msrk\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[1;32m      <a href='vscode-notebook-cell:/Users/ASMF/Code/neqsimpython/examples/jupyter/examplesInPython.ipynb#ch0000017?line=1'>2</a>\u001b[0m fluid1\u001b[39m.\u001b[39maddComponent(\u001b[39m'\u001b[39m\u001b[39mn-heptane\u001b[39m\u001b[39m'\u001b[39m,\u001b[39m49.39\u001b[39m)\n\u001b[1;32m      <a href='vscode-notebook-cell:/Users/ASMF/Code/neqsimpython/examples/jupyter/examplesInPython.ipynb#ch0000017?line=2'>3</a>\u001b[0m \u001b[39m#fluid1.addComponent('methane',50.61)\u001b[39;00m\n",
-      "\u001b[0;31mNameError\u001b[0m: name 'fluid' is not defined"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "density  617.2714448481995  kg/m3\n",
+      "thermal conductivity  0.12321094874956391\n",
+      "thermal conductivity  0.12321094874956391\n"
      ]
     }
    ],
@@ -484,16 +545,16 @@
     "fluid1.initPhysicalProperties()\n",
     "\n",
     "print(\"density \", fluid1.getPhase(\"oil\").getDensity(), \" kg/m3\")\n",
-    "print(\"conductivity \", fluid1.getPhase(\"oil\").getConductivity())\n",
+    "print(\"thermal conductivity \", fluid1.getPhase(\"oil\").getThermalConductivity('W/mK'))\n",
     "fluid1.getPhase(0).getPhysicalProperties().setConductivityModel(\"PFCT\")\n",
     "fluid1.initPhysicalProperties()\n",
-    "print(\"conductivity \", fluid1.getPhase(\"oil\").getConductivity())"
+    "print(\"thermal conductivity \", fluid1.getPhase(\"oil\").getThermalConductivity('W/mK'))"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "neqsim",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -507,7 +568,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.1"
+   "version": "3.10.16"
   }
  },
  "nbformat": 4,
diff --git a/examples/jupyter/readEclipseE300format.ipynb b/examples/jupyter/readEclipseE300format.ipynb
index bf15beb..bf9cf94 100644
--- a/examples/jupyter/readEclipseE300format.ipynb
+++ b/examples/jupyter/readEclipseE300format.ipynb
@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -36,7 +36,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -47,7 +47,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -85,8 +85,8 @@
        "      <th>0</th>\n",
        "      <td></td>\n",
        "      <td>total</td>\n",
-       "      <td>gas</td>\n",
-       "      <td>oil</td>\n",
+       "      <td>GAS</td>\n",
+       "      <td>OIL</td>\n",
        "      <td></td>\n",
        "      <td></td>\n",
        "      <td></td>\n",
@@ -95,8 +95,8 @@
        "      <th>1</th>\n",
        "      <td>nitrogen</td>\n",
        "      <td>1.328E-3</td>\n",
-       "      <td>1.37375E-3</td>\n",
-       "      <td>2.27017E-6</td>\n",
+       "      <td>1.37208E-3</td>\n",
+       "      <td>2.10134E-6</td>\n",
        "      <td></td>\n",
        "      <td></td>\n",
        "      <td>[mole fraction]</td>\n",
@@ -105,8 +105,8 @@
        "      <th>2</th>\n",
        "      <td>CO2</td>\n",
        "      <td>3.25865E-2</td>\n",
-       "      <td>3.36916E-2</td>\n",
-       "      <td>5.65258E-4</td>\n",
+       "      <td>3.36515E-2</td>\n",
+       "      <td>5.53463E-4</td>\n",
        "      <td></td>\n",
        "      <td></td>\n",
        "      <td>[mole fraction]</td>\n",
@@ -115,8 +115,8 @@
        "      <th>3</th>\n",
        "      <td>methane</td>\n",
        "      <td>8.39723E-1</td>\n",
-       "      <td>8.68521E-1</td>\n",
-       "      <td>5.27666E-3</td>\n",
+       "      <td>8.67475E-1</td>\n",
+       "      <td>5.02947E-3</td>\n",
        "      <td></td>\n",
        "      <td></td>\n",
        "      <td>[mole fraction]</td>\n",
@@ -125,8 +125,8 @@
        "      <th>4</th>\n",
        "      <td>ethane</td>\n",
        "      <td>4.83544E-2</td>\n",
-       "      <td>4.99564E-2</td>\n",
-       "      <td>1.93729E-3</td>\n",
+       "      <td>4.98992E-2</td>\n",
+       "      <td>1.89264E-3</td>\n",
        "      <td></td>\n",
        "      <td></td>\n",
        "      <td>[mole fraction]</td>\n",
@@ -198,11 +198,11 @@
       ],
       "text/plain": [
        "           0           1           2           3 4  5                 6\n",
-       "0                  total         gas         oil                       \n",
-       "1   nitrogen    1.328E-3  1.37375E-3  2.27017E-6        [mole fraction]\n",
-       "2        CO2  3.25865E-2  3.36916E-2  5.65258E-4        [mole fraction]\n",
-       "3    methane  8.39723E-1  8.68521E-1  5.27666E-3        [mole fraction]\n",
-       "4     ethane  4.83544E-2  4.99564E-2  1.93729E-3        [mole fraction]\n",
+       "0                  total         GAS         OIL                       \n",
+       "1   nitrogen    1.328E-3  1.37208E-3  2.10134E-6        [mole fraction]\n",
+       "2        CO2  3.25865E-2  3.36515E-2  5.53463E-4        [mole fraction]\n",
+       "3    methane  8.39723E-1  8.67475E-1  5.02947E-3        [mole fraction]\n",
+       "4     ethane  4.83544E-2  4.98992E-2  1.89264E-3        [mole fraction]\n",
        "..       ...         ...         ...         ... .. ..              ...\n",
        "59    Stream                                                          -\n",
        "60                                                                     \n",
@@ -213,7 +213,7 @@
        "[64 rows x 7 columns]"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -232,7 +232,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -241,7 +241,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -279,8 +279,8 @@
        "      <th>0</th>\n",
        "      <td></td>\n",
        "      <td>total</td>\n",
-       "      <td>gas</td>\n",
-       "      <td>oil</td>\n",
+       "      <td>GAS</td>\n",
+       "      <td>OIL</td>\n",
        "      <td></td>\n",
        "      <td></td>\n",
        "      <td></td>\n",
@@ -289,8 +289,8 @@
        "      <th>1</th>\n",
        "      <td>nitrogen</td>\n",
        "      <td>8.49998E-4</td>\n",
-       "      <td>8.70757E-4</td>\n",
-       "      <td>1.39448E-6</td>\n",
+       "      <td>8.70763E-4</td>\n",
+       "      <td>1.36793E-6</td>\n",
        "      <td></td>\n",
        "      <td></td>\n",
        "      <td>[mole fraction]</td>\n",
@@ -299,8 +299,8 @@
        "      <th>2</th>\n",
        "      <td>CO2</td>\n",
        "      <td>3.26669E-2</td>\n",
-       "      <td>3.34524E-2</td>\n",
-       "      <td>5.57794E-4</td>\n",
+       "      <td>3.34527E-2</td>\n",
+       "      <td>5.54883E-4</td>\n",
        "      <td></td>\n",
        "      <td></td>\n",
        "      <td>[mole fraction]</td>\n",
@@ -309,8 +309,8 @@
        "      <th>3</th>\n",
        "      <td>methane</td>\n",
        "      <td>8.62505E-1</td>\n",
-       "      <td>8.83475E-1</td>\n",
-       "      <td>5.27028E-3</td>\n",
+       "      <td>8.83482E-1</td>\n",
+       "      <td>5.20781E-3</td>\n",
        "      <td></td>\n",
        "      <td></td>\n",
        "      <td>[mole fraction]</td>\n",
@@ -319,8 +319,8 @@
        "      <th>4</th>\n",
        "      <td>ethane</td>\n",
        "      <td>4.28819E-2</td>\n",
-       "      <td>4.38895E-2</td>\n",
-       "      <td>1.68985E-3</td>\n",
+       "      <td>4.389E-2</td>\n",
+       "      <td>1.68005E-3</td>\n",
        "      <td></td>\n",
        "      <td></td>\n",
        "      <td>[mole fraction]</td>\n",
@@ -392,11 +392,11 @@
       ],
       "text/plain": [
        "           0           1           2           3 4  5                 6\n",
-       "0                  total         gas         oil                       \n",
-       "1   nitrogen  8.49998E-4  8.70757E-4  1.39448E-6        [mole fraction]\n",
-       "2        CO2  3.26669E-2  3.34524E-2  5.57794E-4        [mole fraction]\n",
-       "3    methane  8.62505E-1  8.83475E-1  5.27028E-3        [mole fraction]\n",
-       "4     ethane  4.28819E-2  4.38895E-2  1.68985E-3        [mole fraction]\n",
+       "0                  total         GAS         OIL                       \n",
+       "1   nitrogen  8.49998E-4  8.70763E-4  1.36793E-6        [mole fraction]\n",
+       "2        CO2  3.26669E-2  3.34527E-2  5.54883E-4        [mole fraction]\n",
+       "3    methane  8.62505E-1  8.83482E-1  5.20781E-3        [mole fraction]\n",
+       "4     ethane  4.28819E-2    4.389E-2  1.68005E-3        [mole fraction]\n",
        "..       ...         ...         ...         ... .. ..              ...\n",
        "59    Stream                                                          -\n",
        "60                                                                     \n",
@@ -407,7 +407,7 @@
        "[64 rows x 7 columns]"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -419,11 +419,8 @@
   }
  ],
  "metadata": {
-  "interpreter": {
-   "hash": "a5df7bd4ca0d6bb9986d9d69faf4f6c25893f82bf7982e9868ee8495bd8c927f"
-  },
   "kernelspec": {
-   "display_name": "Python 3.7.9 64-bit ('base': conda)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -437,7 +434,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.9"
+   "version": "3.10.16"
   },
   "orig_nbformat": 4
  },
diff --git a/examples/jupyter/separatorEfficiency.ipynb b/examples/jupyter/separatorEfficiency.ipynb
index 557bc82..dacc712 100644
--- a/examples/jupyter/separatorEfficiency.ipynb
+++ b/examples/jupyter/separatorEfficiency.ipynb
@@ -2,68 +2,68 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "                     0           1               2 3 4 5                6\n",
-      "0                            total             gas                       \n",
-      "1                  CO2  5.91466E-3      5.91466E-3        [mole fraction]\n",
-      "2             nitrogen  9.71766E-3      9.71766E-3        [mole fraction]\n",
-      "3              methane  9.48747E-1      9.48747E-1        [mole fraction]\n",
-      "4               ethane  2.51198E-2      2.51198E-2        [mole fraction]\n",
-      "5              propane   4.0632E-3       4.0632E-3        [mole fraction]\n",
-      "6             i-butane  1.48117E-3      1.48117E-3        [mole fraction]\n",
-      "7             n-butane   1.0108E-3       1.0108E-3        [mole fraction]\n",
-      "8            i-pentane  7.82617E-4      7.82617E-4        [mole fraction]\n",
-      "9            n-pentane  4.33341E-4      4.33341E-4        [mole fraction]\n",
-      "10              2-m-C5  4.07321E-4      4.07321E-4        [mole fraction]\n",
-      "11              3-m-C5  1.28101E-4      1.28101E-4        [mole fraction]\n",
-      "12            n-hexane  2.13168E-4      2.13168E-4        [mole fraction]\n",
-      "13           n-heptane  1.57124E-4      1.57124E-4        [mole fraction]\n",
-      "14            c-hexane  8.54673E-4      8.54673E-4        [mole fraction]\n",
-      "15                c-C7  6.08479E-4      6.08479E-4        [mole fraction]\n",
-      "16             benzene  2.23176E-5      2.23176E-5        [mole fraction]\n",
-      "17            n-octane  4.64366E-5      4.64366E-5        [mole fraction]\n",
-      "18             toluene  5.81458E-5      5.81458E-5        [mole fraction]\n",
-      "19                c-C8  1.05083E-4      1.05083E-4        [mole fraction]\n",
-      "20            n-nonane  3.62285E-5      3.62285E-5        [mole fraction]\n",
-      "21            m-Xylene  3.86304E-5      3.86304E-5        [mole fraction]\n",
-      "22                nC10    5.074E-5        5.074E-5        [mole fraction]\n",
-      "23                nC11  2.48196E-6      2.48196E-6        [mole fraction]\n",
-      "24                nC12  4.04319E-7      4.04319E-7        [mole fraction]\n",
-      "25                                                                       \n",
-      "26             Density                   7.17283E1               [kg/m^3]\n",
-      "27       PhaseFraction                         1E0        [mole fraction]\n",
-      "28           MolarMass   1.71729E1       1.71729E1              [kg/kmol]\n",
-      "29            Z factor                  8.17122E-1                    [-]\n",
-      "30  Heat Capacity (Cp)                    2.8802E0              [kJ/kg*K]\n",
-      "31  Heat Capacity (Cv)                   1.71961E0              [kJ/kg*K]\n",
-      "32      Speed of Sound                   4.09599E2                [m/sec]\n",
-      "33            Enthalpy  -5.94004E1      -5.94004E1                [kJ/kg]\n",
-      "34             Entropy  -2.10432E0      -2.10432E0              [kJ/kg*K]\n",
-      "35      JT coefficient                  3.99278E-1                [K/bar]\n",
-      "36                                                                       \n",
-      "37           Viscosity                   1.3499E-5             [kg/m*sec]\n",
-      "38        Conductivity                  4.28907E-2                [W/m*K]\n",
-      "39      SurfaceTension                                              [N/m]\n",
-      "40                                                                       \n",
-      "41                                                                       \n",
-      "42                                                                       \n",
-      "43            Pressure                    85.01325                  [bar]\n",
-      "44         Temperature                      293.15                    [K]\n",
-      "45                                                                       \n",
-      "46               Model              UMR-PRU-MC-EoS                      -\n",
-      "47         Mixing Rule                 Huron-Vidal                      -\n",
-      "48                                                                       \n",
-      "49              Stream                                                  -\n",
-      "50                                                                       \n",
-      "51                                                                       \n",
-      "52                                                                       \n",
-      "53                                                                       \n"
+      "                       0           1               2 3 4 5                6\n",
+      "0                              total             GAS                       \n",
+      "1                    CO2  5.91466E-3      5.91466E-3        [mole fraction]\n",
+      "2               nitrogen  9.71766E-3      9.71766E-3        [mole fraction]\n",
+      "3                methane  9.48747E-1      9.48747E-1        [mole fraction]\n",
+      "4                 ethane  2.51198E-2      2.51198E-2        [mole fraction]\n",
+      "5                propane   4.0632E-3       4.0632E-3        [mole fraction]\n",
+      "6               i-butane  1.48117E-3      1.48117E-3        [mole fraction]\n",
+      "7               n-butane   1.0108E-3       1.0108E-3        [mole fraction]\n",
+      "8              i-pentane  7.82617E-4      7.82617E-4        [mole fraction]\n",
+      "9              n-pentane  4.33341E-4      4.33341E-4        [mole fraction]\n",
+      "10                2-m-C5  4.07321E-4      4.07321E-4        [mole fraction]\n",
+      "11                3-m-C5  1.28101E-4      1.28101E-4        [mole fraction]\n",
+      "12              n-hexane  2.13168E-4      2.13168E-4        [mole fraction]\n",
+      "13             n-heptane  1.57124E-4      1.57124E-4        [mole fraction]\n",
+      "14              c-hexane  8.54673E-4      8.54673E-4        [mole fraction]\n",
+      "15                  c-C7  6.08479E-4      6.08479E-4        [mole fraction]\n",
+      "16               benzene  2.23176E-5      2.23176E-5        [mole fraction]\n",
+      "17              n-octane  4.64366E-5      4.64366E-5        [mole fraction]\n",
+      "18               toluene  5.81458E-5      5.81458E-5        [mole fraction]\n",
+      "19                  c-C8  1.05083E-4      1.05083E-4        [mole fraction]\n",
+      "20              n-nonane  3.62285E-5      3.62285E-5        [mole fraction]\n",
+      "21              m-Xylene  3.86304E-5      3.86304E-5        [mole fraction]\n",
+      "22                  nC10    5.074E-5        5.074E-5        [mole fraction]\n",
+      "23                  nC11  2.48196E-6      2.48196E-6        [mole fraction]\n",
+      "24                  nC12  4.04319E-7      4.04319E-7        [mole fraction]\n",
+      "25                                                                         \n",
+      "26               Density                   7.17283E1                  kg/m3\n",
+      "27        Phase Fraction                         1E0        [mole fraction]\n",
+      "28            Molar Mass  1.71729E-2      1.71729E-2                 kg/mol\n",
+      "29              Z factor                  8.35058E-1                    [-]\n",
+      "30    Heat Capacity (Cp)                   2.88062E0                 kJ/kgK\n",
+      "31    Heat Capacity (Cv)                   1.72003E0                 kJ/kgK\n",
+      "32        Speed of Sound                   4.09578E2                  m/sec\n",
+      "33              Enthalpy  -5.93931E4      -5.93931E4                   J/kg\n",
+      "34               Entropy  -2.10429E3      -2.10429E3                  J/kgK\n",
+      "35        JT coefficient                  3.99219E-1                  C/bar\n",
+      "36                                                                         \n",
+      "37             Viscosity                   1.3499E-5                kg/msec\n",
+      "38  Thermal Conductivity                  4.28919E-2                   W/mK\n",
+      "39       Surface Tension                                              [N/m]\n",
+      "40                                                                         \n",
+      "41                                                                         \n",
+      "42                                                                         \n",
+      "43              Pressure                    85.01325                   bara\n",
+      "44           Temperature                        20.0                      C\n",
+      "45                                                                         \n",
+      "46                 Model              UMR-PRU-MC-EoS                      -\n",
+      "47           Mixing Rule                 Huron-Vidal                      -\n",
+      "48                                                                         \n",
+      "49                Stream                                                  -\n",
+      "50                                                                         \n",
+      "51                                                                         \n",
+      "52                                                                         \n",
+      "53                                                                         \n"
      ]
     }
    ],
@@ -114,21 +114,21 @@
     "\n",
     "clearProcess()\n",
     "\n",
-    "feedStream = stream(fluid1, \"feed fluid\")\n",
+    "feedStream = stream(\"feed fluid\", fluid1)\n",
     "feedStream.setTemperature(20.0, 'C')\n",
     "feedStream.setPressure(84.0, 'barg')\n",
     "feedStream.setFlowRate(25.7, 'MSm3/day')\n",
     "\n",
-    "separator1 = separator3phase(feedStream)\n",
+    "separator1 = separator3phase('sep1', feedStream)\n",
     "\n",
-    "cooler1 = cooler(separator1.getGasOutStream())\n",
+    "cooler1 = cooler('cooler 1',separator1.getGasOutStream())\n",
     "cooler1.setOutTemperature(11.3, 'C')\n",
     "cooler1.setOutPressure(80.8, 'barg')\n",
     "\n",
-    "separator2 = separator3phase(cooler1.getOutStream())\n",
+    "separator2 = separator3phase('sep 2', cooler1.getOutStream())\n",
     "separator2.setEntrainment(0.1, 'mole', 'feed', 'oil', 'gas')\n",
     "\n",
-    "exportGas = stream(separator2.getGasOutStream())\n",
+    "exportGas = stream('export gas', separator2.getGasOutStream())\n",
     "\n",
     "runProcess()\n",
     "\n",
@@ -137,7 +137,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -154,7 +154,7 @@
     "exportGasFluid.setTemperature(0.0, \"C\")\n",
     "exportGasFluid.setPressure(10.0, \"bara\")\n",
     "\n",
-    "cvdSim = jneqsim.PVTsimulation.simulation.SaturationPressure(exportGasFluid)\n",
+    "cvdSim = jneqsim.pvtsimulation.simulation.SaturationPressure(exportGasFluid)\n",
     "cvdSim.run()\n",
     "\n",
     "\n",
@@ -163,7 +163,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -176,9 +176,216 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "efficiency  0.0\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.01\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.02\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.03\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.04\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.05\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.06\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.07\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.08\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.09\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.1\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.11\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.12\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.13\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.14\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.15\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.16\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.17\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.18\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.19\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.2\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.21\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.22\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.23\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.24\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.25\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.26\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.27\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.28\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.29\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.3\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.31\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.32\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.33\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.34\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.35000000000000003\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.36\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.37\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.38\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.39\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.4\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.41000000000000003\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.42\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.43\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.44\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.45\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.46\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.47000000000000003\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.48\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.49\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.5\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.51\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.52\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.53\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.54\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.55\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.56\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.5700000000000001\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.58\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.59\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.6\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.61\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.62\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.63\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.64\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.65\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.66\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.67\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.68\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.6900000000000001\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.7000000000000001\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.71\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.72\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.73\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.74\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.75\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.76\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.77\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.78\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.79\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.8\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.81\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.8200000000000001\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.8300000000000001\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.84\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.85\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.86\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.87\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.88\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.89\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.9\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.91\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.92\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.93\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.9400000000000001\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.9500000000000001\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.96\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.97\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.98\n",
+      "dew point pressur @0C  100.66896057128906  bara\n",
+      "efficiency  0.99\n",
+      "dew point pressur @0C  100.66896057128906  bara\n"
+     ]
+    }
+   ],
    "source": [
     "scrubberEfficiency = []\n",
     "c6plus = []\n",
@@ -193,13 +400,11 @@
     "    exportGasFluid = separator2.getGasOutStream().getFluid().clone()\n",
     "    exportGasFluid.setTemperature(0.0, \"C\")\n",
     "    exportGasFluid.setPressure(10.0, \"bara\")\n",
-    "    cvdSim = jneqsim.PVTsimulation.simulation.SaturationPressure(exportGasFluid)\n",
+    "    cvdSim = jneqsim.pvtsimulation.simulation.SaturationPressure(exportGasFluid)\n",
     "    cvdSim.run()\n",
-    "    c6plus.append(getC6plus(exportGasFluid)*100)\n",
     "    dewpointpressure.append(cvdSim.getSaturationPressure()-1.01325)\n",
-    "    #print('efficiency ', efficiency)\n",
-    "    #print('dew point pressur @0C ', cvdSim.getSaturationPressure(), ' bara')\n",
-    "    #print('C6+ ', cvdSim.getSaturationPressure(), ' bara')\n"
+    "    print('efficiency ', efficiency)\n",
+    "    print('dew point pressur @0C ', cvdSim.getSaturationPressure(), ' bara')\n"
    ]
   },
   {
@@ -292,7 +497,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.10.8 64-bit",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -306,14 +511,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.8"
+   "version": "3.10.16"
   },
-  "orig_nbformat": 4,
-  "vscode": {
-   "interpreter": {
-    "hash": "949777d72b0d2535278d3dc13498b2535136f6dfe0678499012e853ee9abcab1"
-   }
-  }
+  "orig_nbformat": 4
  },
  "nbformat": 4,
  "nbformat_minor": 2
diff --git a/examples/jupyter/simpleFlash.ipynb b/examples/jupyter/simpleFlash.ipynb
index cc1bc06..2221046 100644
--- a/examples/jupyter/simpleFlash.ipynb
+++ b/examples/jupyter/simpleFlash.ipynb
@@ -27,58 +27,59 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "                         total         oil                   \n",
-      "             water  4.39785E-3  4.39785E-3    [mole fraction]\n",
-      "          nitrogen  7.09893E-4  7.09893E-4    [mole fraction]\n",
-      "               CO2  1.00456E-2  1.00456E-2    [mole fraction]\n",
-      "           methane  1.72078E-1  1.72078E-1    [mole fraction]\n",
-      "            ethane  8.05144E-2  8.05144E-2    [mole fraction]\n",
-      "           propane  8.95376E-2  8.95376E-2    [mole fraction]\n",
-      "          i-butane  8.88836E-2  8.88836E-2    [mole fraction]\n",
-      "          n-butane  7.27659E-2  7.27659E-2    [mole fraction]\n",
-      "         i-pentane  5.56419E-2  5.56419E-2    [mole fraction]\n",
-      "         n-pentane  6.23861E-2  6.23861E-2    [mole fraction]\n",
-      "             C6_PC  1.56711E-1  1.56711E-1    [mole fraction]\n",
-      "             C7_PC  6.18607E-2  6.18607E-2    [mole fraction]\n",
-      "             C8_PC  5.39536E-2  5.39536E-2    [mole fraction]\n",
-      "             C9_PC  6.94317E-2  6.94317E-2    [mole fraction]\n",
-      "            C10_PC  2.10817E-2  2.10817E-2    [mole fraction]\n",
-      "                                                             \n",
-      "           Density               6.03969E2           [kg/m^3]\n",
-      "     PhaseFraction                     1E0    [mole fraction]\n",
-      "         MolarMass   6.77873E1   6.77873E1          [kg/kmol]\n",
-      "          Z factor              2.45511E-1                [-]\n",
-      "Heat Capacity (Cp)               2.47443E0          [kJ/kg*K]\n",
-      "Heat Capacity (Cv)               1.93545E0          [kJ/kg*K]\n",
-      "    Speed of Sound               7.04037E2            [m/sec]\n",
-      "          Enthalpy  -2.71505E2  -2.71505E2            [kJ/kg]\n",
-      "           Entropy -6.54047E-1 -6.54047E-1          [kJ/kg*K]\n",
-      "    JT coefficient             -2.35673E-2            [K/bar]\n",
-      "                                                             \n",
-      "         Viscosity              1.71553E-4         [kg/m*sec]\n",
-      "      Conductivity               9.4728E-2            [W/m*K]\n",
-      "    SurfaceTension                                      [N/m]\n",
-      "                                                             \n",
-      "                                                             \n",
-      "                                                             \n",
-      "          Pressure                    55.0              [bar]\n",
-      "       Temperature                  328.15                [K]\n",
-      "                                                             \n",
-      "             Model                 SRK-EOS                  -\n",
-      "       Mixing Rule                 classic                  -\n",
-      "                                                             \n",
-      "            Stream                                          -\n",
-      "                                                             \n",
-      "                                                             \n",
-      "                                                             \n",
-      "                                                             \n"
+      "                       0           1                  2 3 4 5                6\n",
+      "0                              total                OIL                       \n",
+      "1                  water  4.40709E-3         4.40709E-3        [mole fraction]\n",
+      "2               nitrogen  7.01888E-4         7.01888E-4        [mole fraction]\n",
+      "3                    CO2   1.0004E-2          1.0004E-2        [mole fraction]\n",
+      "4                methane  1.70793E-1         1.70793E-1        [mole fraction]\n",
+      "5                 ethane  8.02149E-2         8.02149E-2        [mole fraction]\n",
+      "6                propane  8.93794E-2         8.93794E-2        [mole fraction]\n",
+      "7               i-butane  8.87988E-2         8.87988E-2        [mole fraction]\n",
+      "8               n-butane  7.27956E-2         7.27956E-2        [mole fraction]\n",
+      "9              i-pentane  5.57328E-2         5.57328E-2        [mole fraction]\n",
+      "10             n-pentane  6.25305E-2         6.25305E-2        [mole fraction]\n",
+      "11                 C6_PC  1.57144E-1         1.57144E-1        [mole fraction]\n",
+      "12                 C7_PC  6.21577E-2         6.21577E-2        [mole fraction]\n",
+      "13                 C8_PC  5.42687E-2         5.42687E-2        [mole fraction]\n",
+      "14                 C9_PC  6.98588E-2         6.98588E-2        [mole fraction]\n",
+      "15                C10_PC  2.12135E-2         2.12135E-2        [mole fraction]\n",
+      "16                                                                            \n",
+      "17               Density                      6.05351E2                  kg/m3\n",
+      "18        Phase Fraction                            1E0        [mole fraction]\n",
+      "19            Molar Mass  6.79536E-2         6.79536E-2                 kg/mol\n",
+      "20              Z factor                     2.26288E-1                    [-]\n",
+      "21    Heat Capacity (Cp)                      2.46269E0                 kJ/kgK\n",
+      "22    Heat Capacity (Cv)                      1.92539E0                 kJ/kgK\n",
+      "23        Speed of Sound                      7.05169E2                  m/sec\n",
+      "24              Enthalpy  -2.72127E5         -2.72127E5                   J/kg\n",
+      "25               Entropy  -6.55488E2         -6.55488E2                  J/kgK\n",
+      "26        JT coefficient                    -2.36319E-2                  C/bar\n",
+      "27                                                                            \n",
+      "28             Viscosity                     1.72665E-4                kg/msec\n",
+      "29  Thermal Conductivity                     9.50053E-2                   W/mK\n",
+      "30       Surface Tension                                                 [N/m]\n",
+      "31                                                                            \n",
+      "32                                                                            \n",
+      "33                                                                            \n",
+      "34              Pressure                           55.0                   bara\n",
+      "35           Temperature              54.99999999999994                      C\n",
+      "36                                                                            \n",
+      "37                 Model                        SRK-EOS                      -\n",
+      "38           Mixing Rule                        classic                      -\n",
+      "39                                                                            \n",
+      "40                Stream                                                     -\n",
+      "41                                                                            \n",
+      "42                                                                            \n",
+      "43                                                                            \n",
+      "44                                                                            \n"
      ]
     }
    ],
@@ -108,10 +109,10 @@
     "TPflash(fluid1)\n",
     "\n",
     "clearProcess()\n",
-    "feedStream = stream(fluid1, \"feed fluid\")\n",
-    "separator1 = separator3phase(feedStream)\n",
+    "feedStream = stream(\"feed fluid\", fluid1)\n",
+    "separator1 = separator3phase('seå 1', feedStream)\n",
     "oilstream1 = separator1.getLiquidOutStream()\n",
-    "valve1 = valve(oilstream1, 10.0, 'valv1')\n",
+    "valve1 = valve('valv1', oilstream1, 10.0)\n",
     "runProcess()\n",
     "\n",
     "printFrame(oilstream1.getFluid())\n"
@@ -120,7 +121,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.9.9 64-bit ('3.9.9')",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -134,12 +135,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.9"
-  },
-  "vscode": {
-   "interpreter": {
-    "hash": "4ba6f98cb0310955db44ebb7b01f232ba27fa841a671ff9eb55769e6a89a3e8b"
-   }
+   "version": "3.10.16"
   }
  },
  "nbformat": 4,
diff --git a/examples/jupyter/wetgascompression.ipynb b/examples/jupyter/wetgascompression.ipynb
index 29fadd4..0364cd3 100644
--- a/examples/jupyter/wetgascompression.ipynb
+++ b/examples/jupyter/wetgascompression.ipynb
@@ -204,12 +204,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Feed GOR  14.590220146656824\n",
-      "GOR fitted  98.9999999999377\n",
+      "Feed GOR  14.590220146656849\n",
+      "GOR fitted  98.99999999993761\n",
       "GVF fitted  0.9899999999999938\n",
-      "Compressor power  8.647058772103767  MW\n",
-      "Polytropic efficiency  0.7962250986266902  [-]\n",
-      "Polytropic fluid head  94.24228389686303  kJ/kg\n"
+      "Compressor power  8.647058772103753  MW\n",
+      "Polytropic efficiency  0.7962250986267035  [-]\n",
+      "Polytropic fluid head  94.24228389686442  kJ/kg\n"
      ]
     }
    ],
diff --git a/examples/mineralScale.py b/examples/mineralScale.py
index 9a39cf7..c639aef 100644
--- a/examples/mineralScale.py
+++ b/examples/mineralScale.py
@@ -55,4 +55,4 @@
 print(pandas.DataFrame(ionCompResults))
 print(pandas.DataFrame(scaleResults))
 
-fluid1.display()
+printFrame(fluid1)
diff --git a/src/neqsim/__init__.py b/src/neqsim/__init__.py
index 1ccce8e..09ae2bf 100644
--- a/src/neqsim/__init__.py
+++ b/src/neqsim/__init__.py
@@ -7,6 +7,7 @@
 from neqsim.neqsimpython import jneqsim, jpype
 import gzip
 
+
 def methods(checkClass):
     methods = checkClass.getClass().getMethods()
     for method in methods:
@@ -60,13 +61,13 @@ def save_neqsim(javaobject, filename):
     """
     # Instantiate XStream from the Java packages
     xstream = jpype.JPackage("com.thoughtworks.xstream").XStream()
-    
+
     # Convert the Java object to an XML string (java.lang.String)
     xml_java_string = xstream.toXML(javaobject)
-    
+
     # Convert java.lang.String to a native Python string
     xml_python_string = str(xml_java_string)
-    
+
     # Compress and save the string as UTF-8 bytes in a .gz file
     with gzip.open(filename, "wb") as f:
         f.write(xml_python_string.encode("utf-8"))
@@ -76,16 +77,16 @@ def save_neqsim(javaobject, filename):
 
 def open_neqsim(filename, allow_all=True, wildcard_permission=None):
     """
-    Decompress and deserialize a Java object (e.g., a NEQSim ProcessSystem) 
+    Decompress and deserialize a Java object (e.g., a NEQSim ProcessSystem)
     from a gzipped XStream XML file.
 
     Args:
         filename (str): Path to the gzipped file (e.g. 'process.neqsim').
         allow_all (bool): If True, uses AnyTypePermission to allow all classes
-            during deserialization. This is simple but not recommended for 
+            during deserialization. This is simple but not recommended for
             production security.
-        wildcard_permission (list of str, optional): 
-            A list of wildcard patterns for XStream to allow. For example, 
+        wildcard_permission (list of str, optional):
+            A list of wildcard patterns for XStream to allow. For example,
             ['neqsim.**'] would allow classes under 'neqsim'.
 
     Returns:
@@ -93,13 +94,13 @@ def open_neqsim(filename, allow_all=True, wildcard_permission=None):
                 or None if an error occurs.
 
     Raises:
-        Any exceptions raised by file I/O, gzip, XStream, or JPype will 
+        Any exceptions raised by file I/O, gzip, XStream, or JPype will
         propagate unless caught by the caller.
 
     Usage Example:
         # Ensure the JVM is started and the XStream JAR is on the classpath.
         # jpype.startJVM(..., classpath=[...])
-        
+
         # open_neqsim("myProcess.neqsim", allow_all=True)
     """
     # 1. Create an XStream instance