Predicting Molecular Photochemistry Using Machine-Learning-Enhanced Quantum Dynamics Simulations
Author:
Affiliation:
1. Department of Chemistry, University of Warwick, Coventry, United Kingdom CV4 7AL
Funder
Engineering and Physical Sciences Research Council
Leverhulme Trust
Publisher
American Chemical Society (ACS)
Subject
General Medicine,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.accounts.1c00665
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1. Direct grid-based quantum dynamics on propagated diabatic potential energy surfaces
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5. Comparing Photosynthetic and Photovoltaic Efficiencies and Recognizing the Potential for Improvement
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