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

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 Bronsted-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.