A Gibbs energy minimization based on the CALPHAD approach
Project description
Equilipy
Equilipy is an open-source python package that offers multicomponent multiphase equilibrium calculations based on the CALPHAD (CALculation of PHAse Diagram) approach. With a set of Gibbs energy description (Thermochemical database) and input conditions (Composition, temperature, pressure), equilibrium phase configureation, amount, composition, and thermochemical properties can be obtained. Equilipy uses the Gibbs energy descriptions furnished by THERMOCHIMICA with the modified Gibbs energy minimization algorithm initially proposed by de Capitani, C. and Brown, T.H. (1987).
Check out documentation for further description.
Dependencies
| Dependency | Version | Required | Libraries |
|---|---|---|---|
| Fortran | - | Yes | - |
| Python | 3.9+ | Yes | numpy, wheel, meson, ninja |
Installation
Installation using pip is available for Equilipy.
pip install equilipy
Features and example
The following features are currently available.
- Single condition equilibrium calculations
- Batch equilibrium calculations
- Scheil-Gulliver solidification
- Phase selection Hehehe
For details, check out the example directory and Features and Examples
Citing Equilipy
If you use Equilipy in your work, please cite the following paper. In addition, cite the current release or version used from Zenodo.
Contributing
We encourage you to contribute to Equilipy. Please see contributing guidelines.
Additional note
Examples in Equilipy uses polars dataframe for fast data processing. In particular, example 3 requires fastexcel as the optional dependancy in polars.
Install fastexcel via
pip install fastexcel
Additionally, if you are using large dataset (> 4billion), install
pip install polars-u64-idx
If you are using old CPUs, install
pip install polars-lts-cpu
For details, check out polars dependencies.
Project details
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