# 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.

## Dependencies¶

• Python3
• Atomic Simulation Environment: Used for I/O operations and to calculate some thermodynamic properties
• Numpy: Used for vector and matrix operations
• Pandas: Used to import data from Excel files
• xlrd: Used by Pandas to import 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
• More Itertools: Used for writing ranges for OpenMKM output.
• PyYAML: Used to write YAML input files for OpenMKM.

## Getting Started¶

1. Install using pip (see documentation for more thorough instructions):

pip install pmutt

2. Look at examples using the code

3. Run the unit tests.

## Publications¶

• J. Lym, G.R. Wittreich and D.G. Vlachos, A Python Multiscale Thermochemistry Toolbox (pMuTT) for thermochemical and kinetic parameter estimation, Computer Physics Communications (2019) 106864, https://doi.org/10.1016/j.cpc.2019.106864.

## Contributing¶

If you have a suggestion or find a bug, please post to our Issues page with the or 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 or 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)