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Calculate thermodynamic properties of matter using phonon gas model (PGM)

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MineralsCloud/pgm

pgm: A Python package for free energy calculations within the phonon gas model

Calculate thermodynamic properties of matter using phonon gas model(PGM)

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Contributors

This repository is authored and maintained by Hongjin Wang and Jingyi Zhuang.

How to cite

The associated paper is published online here.

Please cite this article as:

Hongjin Wang, Jingyi Zhuang, Zhen Zhang, Qi Zhang, Renata M. Wentzcovitch, pgm: A Python package for free energy calculations within the phonon gas model, Computer Physics Communications (2023), Volume 291, 2023, 108845, https://doi.org/10.1016/j.cpc.2023.108845.

If you are unable to access the full text of this article, please contact the authors.

Installation

Install from PyPI

You can install the package directly from PyPI:

$ pip install phonon-gas-model

Manual install

To install the pgm package, first clone the code repository using git:

$ git clone https://github.com/MineralsCloud/pgm.git

After cloning the code repository, change to the code directory using cd:

$ cd pgm

After changing to the code directory, install the required Python packages using pip:

$ pip install -r requirements.txt

Finally, install the pgm package using pip:

$ pip install .

See details in Installation of pgm.

How to use

Here we provide two examples inside the example folder. One is CaSiO₃, and one is B8-FeO.

For the case of CaSiO₃, simply run the following commands from the root path of the package:

$ cd examples/casio3
$ pgm run casio3.yaml

and for another case, B8-FeO,

run the following commands from the root path of the package:

$ cd examples/feo
$ pgm run feo.yaml

See details Command Line Tool of pgm.

Use your own example

First, you need to prepare a set of phonon calculations calculated at different temperatures.

Convert them as standard qha input files(for now use input converter in qha pkg), and put the input files like in the case of CaSiO₃ or B8-FeO

Compose your own settings.yaml file, enjoy.

Details will be provide shortly.

Documentation

See GitHub pages of pgm.