Machine Learning Approach to Vertical Energy Gap in Redox Processes
Author:
Affiliation:
1. Department of Chemistry, Syracuse University, Syracuse, New York 13244, United States
2. BioInspired Syracuse, Syracuse University, Syracuse, New York 13244, United States
Publisher
American Chemical Society (ACS)
Link
https://pubs.acs.org/doi/pdf/10.1021/acs.jctc.4c00715
Reference65 articles.
1. Development of redox flow batteries. A historical bibliography
2. Flow Batteries: Current Status and Trends
3. Quantum chemistry reveals thermodynamic principles of redox biochemistry
4. Free energies for biological electron transfer from QM/MM calculation: method, application and critical assessment
5. Polarizable embedding for simulating redox potentials of biomolecules
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