Conference by Dr. Clément SOULIE (Judit ZADOR group, Sandia National Laboratories, Livermore, California, USA)

December 11, 2024
11:00
Salle du Conseil - Faculté de Chimie - 1 rue Blaise Pascal, Strasbourg

KinBot: An automated journey from a single structure to rate coefficients

Contact: Dr. Christophe GOURLAOUEN, Laboratory of Modelling and Molecular Simulation

Abstract: With the advances in computer power and improved robustness of quantum chemistry calculations, it is now possible to automate those in order to provide the necessary data for rate coefficients calculations using master equation solvers. This is the objective of KinBot [1], an open-source software developed by the group of Judit Zádor at Sandia National Laboratories.

KinBot explores the potential energy surface (PES) of a system starting from an initial structure by proposing transition state (TS) geometries based on reaction templates, selected depending on the patterns present in the initial well. If the connectivity between the new product and the initial well is established (IRC), a new search starts from the product. Each structure also undergoes a conformational minimization, as well as hindered rotors scans and the results can be wrapped in an input for subsequent Master Equation calculation of the temperature and pressure dependent rate coefficients of each reaction.

However, calculating the rate coefficients for barrierless bimolecular capture reactions remain a challenge as the rigid-rotor/harmonic approximation is a bad approximation to describe the normal modes along the reaction coordinate. Hence, among the recent advances, KinBot has been extended to prepare variable reaction coordinate transition state theory (VRC-TST) calculations with a new interface to rotdPy[2], a PES sampler for VRC-TST.

[1]: Judit Zádor, Carles Martí, Ruben Van de Vijver, Sommer L. Johansen, Yoona Yang, Hope A. Michelsen, Habib N. Najm: Automated reaction kinetics of gas-phase organic species over multiwell potential energy surfaces, J. Phys. Chem. A, 2023, 127, 565–588. https://pubs.acs.org/doi/10.1021/acs.jpca.2c06558