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 |
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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.
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Year of Publication |
2020
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Journal |
Computer Physics Communications
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Volume |
247
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Number of Pages |
106864
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Date Published |
feb
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