Python Multiscale Thermochemistry Toolbox (pmutt)
Project description
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 (jlym@udel.edu)
Gerhard Wittreich, P.E. (wittregr@udel.edu)
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
pyGal: Similar to Matplotlib. Used for plotting interactive graphs.
PyMongo: Used to read/write to databases
dnspython: Used to connect to databases
NetworkX: Used to plot reaction networks.
Getting Started
Install using pip:
pip install --user pmutt
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
Look at examples using the code
License
This project is licensed under the MIT License - see the LICENSE.md file for details.
Publications
J. Lym, G.R Wittreich and D.G Vlachos, “A Python Multiscale Thermochemistry Toolbox (pMuTT) for Thermochemical and Kinetic Parameter Estimation” (submitted)
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)
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