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Open-Source Software & Databases for Simulations & Machine Learning in Catalysis & Kinetics:
Date
August 18, 2024
Division/Committee: [CATL] Division of Catalysis Science & Technology
Modern computing and machine learning methods have facilitated the development of advanced techniques for analysis and simulation of reaction kinetics, reactor engineering, and atomistic simulations. This symposium will focus on open-source software packages and databases, which are a critical tool for enabling adoption of these methods across both computational and experimental research groups. Submissions are strongly encouraged to include a link to the software within the abstract. Possible topics include: 1) Codes for micro-kinetic modeling and kinetic Monte Carlo; 2) Reactor modeling codes for integration of transport and kinetics; 3) Codes for applying machine learning and statistics to reaction kinetics; 4) Databases and machine learning methods for atomistic simulations