Δ-Machine learning for quantum chemistry prediction of solution-phase molecular properties at the ground and excited states
Author:
Affiliation:
1. Department of Chemistry, Emory University, Atlanta, 30322, Georgia
Abstract
Funder
American Chemical Society Petroleum Research Fund
Research Corporation for Science Advancement
Publisher
Royal Society of Chemistry (RSC)
Subject
Physical and Theoretical Chemistry,General Physics and Astronomy
Link
http://pubs.rsc.org/en/content/articlepdf/2023/CP/D3CP00506B
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1. A Mixed Quantum Chemistry/Machine Learning Approach for the Fast and Accurate Prediction of Biochemical Redox Potentials and Its Large-Scale Application to 315 000 Redox Reactions
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