Virtual Kinetics Lab (VLab): Suite of Open-source Tools for Multiscale Modeling, Optimization, Machine Learning, and Databases.
Workshop instructors: Sashank Kasiraju, Siddhant Lambor, and Gerhard Wittreich.
Virtual Kinetics Lab is a suite of open-source software tools aimed at multiscale modeling, cheminformatics, and machine learning. This toolkit integrates first-principles calculations and data-driven methods to calculate thermodynamic properties of adsorbates on catalysts, reaction rate constants, reaction pathways and networks, kinetic models, visualization, and analysis. We also leverage optimization and machine learning paradigms for kinetic parameter estimation, similarity analysis of molecules, uncertainty quantification, and development of surrogate models. We provide integrated databases that retain information from simulations at various scales, including the learnt reaction rules, density functional theory data, thermochemistry data, reaction rate parameters, and reaction mechanisms.
We will demonstrate some of the key software related to chemical kinetics (OpenMKM, pMuTT, pGrAdd) and databases (CKineticsDB).
The source-code and documentation for most of the tools is available on Vlachos Group GitHub and UD’s RAPID Software Website.