A Python Multiscale Thermochemistry Toolbox (pMuTT) for thermochemical and kinetic parameter estimation

Title A Python Multiscale Thermochemistry Toolbox (pMuTT) for thermochemical and kinetic parameter estimation
Publication Type Journal Article
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Abstract
Estimating the thermochemical properties of systems is important in many fields such as material science and catalysis. The Python multiscale thermochemistry toolbox (pMuTT) is a Python software library developed to streamline the conversion of ab-initio data to thermochemical properties using statistical mechanics, to perform thermodynamic analysis, and to create input files for kinetic modeling software. Its open-source implementation in Python leverages existing scientific codes, encourages users to write scripts for their needs, and allows the code to be expanded easily. The core classes developed include a statistical mechanical model in which energy modes can be included or excluded to suit the application, empirical models for rapid thermodynamic property estimation, and a reaction model to calculate kinetic parameters or changes in thermodynamic properties. In addition, pMuTT supports other features, such as Brønsted–Evans–Polanyi (BEP) relationships, coverage effects, and ab-initio phase diagrams. Program summary: Program title: pMuTT Program files doi: http://dx.doi.org/10.17632/b7f7d28ynd.1 Licensing provisions: MIT license (MIT) Programming language: Python External routines: ASE, NumPy, Pandas, SciPy, Matplotlib, Pygal, PyMongo, dnspython Nature of problem: Conversion of ab-initio properties to thermochemical properties and rate constants is time consuming and error-prone. Solution method: Python package with a modular approach to statistical thermodynamics and rate constant estimation.
Year of Publication
2020
Journal
Computer Physics Communications
Volume
247
Number of Pages
106864
Date Published
feb
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