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Published in: Topics in Catalysis 1-4/2022

12-09-2021 | Original Paper

Automated Construction and Optimization Combined with Machine Learning to Generate Pt(II) Methane C–H Activation Transition States

Authors: Shusen Chen, Taylor Nielson, Elayna Zalit, Bastian Bjerkem Skjelstad, Braden Borough, William J. Hirschi, Spencer Yu, David Balcells, Daniel H. Ess

Published in: Topics in Catalysis | Issue 1-4/2022

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Abstract

Quantum–mechanical transition states can aid in the identification of promising catalysts for methane C–H activation and functionalization. However, only a limited amount of the vast metal–ligand chemical space has been computationally evaluated. To begin to solve this problem, we showcase a workflow that combines automated construction of Pt(II)-ligand combinations and automated transition-state searching with machine learning to maximize the generation of fully optimized transition states.

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Appendix
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Metadata
Title
Automated Construction and Optimization Combined with Machine Learning to Generate Pt(II) Methane C–H Activation Transition States
Authors
Shusen Chen
Taylor Nielson
Elayna Zalit
Bastian Bjerkem Skjelstad
Braden Borough
William J. Hirschi
Spencer Yu
David Balcells
Daniel H. Ess
Publication date
12-09-2021
Publisher
Springer US
Published in
Topics in Catalysis / Issue 1-4/2022
Print ISSN: 1022-5528
Electronic ISSN: 1572-9028
DOI
https://doi.org/10.1007/s11244-021-01506-0

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