pmutt 1.2.3

Python Multiscale Thermochemistry Toolbox (pMuTT)

The Python Multiscale Thermochemistry Toolbox (pMuTT) is a Python library for Thermochemistry developed by the Vlachos Research Group at the University of Delaware. This code was originally developed to convert ab-initio data from DFT to observable thermodynamic properties such as heat capacity, enthalpy, entropy, and Gibbs energy. These properties can be fit to empirical equations and written to different formats.

Documentation

See our documentation page for examples, equations used, and docstrings.

Developers

• Jonathan Lym ([e-mail])

• Gerhard Wittreich, P.E. ([e-mail])

Dependencies

• Python3

• Atomic Simulation Environment: Used for I/O operations and to calculate thermodynamic properties

• Numpy: Used for vector and matrix operations

• Pandas: Used to import data from Excel files

• SciPy: Used for fitting heat capacities and generating smooth curves for

  reaction coordinate diagram

• Matplotlib: Used for plotting thermodynamic data

Getting Started

1. Install using pip:

   pip install --user pMuTT

2. Run the tests by navigating to the tests directory in a command-line interface and inputting the following command:

   python -m unittest

The expected output is shown below. The number of tests will not necessarily be the same.

.........................
----------------------------------------------------------------------
Ran 25 tests in 0.020s

OK

3. Look at examples using the code

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Contributing

If you have a suggestion or find a bug, please post to our Issues page with the enhancement or bug tag respectively.

Finally, if you would like to add to the body of code, please:

• fork the development branch

• make the desired changes

• write the appropriate unit tests

• submit a pull request.

Questions

If you are having issues, please post to our Issues page with the help wanted or question tag. We will do our best to assist.

Funding

This material is based upon work supported by the Department of Energy’s Office of Energy Efficient and Renewable Energy’s Advanced Manufacturing Office under Award Number DE-EE0007888-9.5.

Special Thanks

• Dr. Jeffrey Frey (pip and conda compatibility)

• Jaynell Keely (Logo design)