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Automated Construction and Optimization Combined with Machine Learning to Generate Pt(II) Methane C–H Activation Transition States.
- Source :
-
Topics in Catalysis . Feb2022, Vol. 65 Issue 1-4, p312-324. 13p. - Publication Year :
- 2022
-
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. [ABSTRACT FROM AUTHOR]
- Subjects :
- *MACHINE learning
*METHANE
*GOVERNMENT aid
*PROBLEM solving
*STEAM reforming
Subjects
Details
- Language :
- English
- ISSN :
- 10225528
- Volume :
- 65
- Issue :
- 1-4
- Database :
- Academic Search Index
- Journal :
- Topics in Catalysis
- Publication Type :
- Academic Journal
- Accession number :
- 155078613
- Full Text :
- https://doi.org/10.1007/s11244-021-01506-0