Exploiting Machine Learning to Efficiently Predict Multidimensional Optical Spectra in Complex Environments
Author:
Affiliation:
1. Department of Chemistry, Stanford University, Stanford, California 94305, United States
2. Chemistry and Chemical Biology, University of California Merced, Merced, California 95343, United States
Funder
Basic Energy Sciences
National Science Foundation
Camille and Henry Dreyfus Foundation Teacher-Scholar Awards Program
Publisher
American Chemical Society (ACS)
Subject
General Materials Science,Physical and Theoretical Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jpclett.0c02168
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