Year: 2016
Type: article
Abstract: Machine learning ground state QM/MM for accelerated computation of exciton dynamics.
Source: Chemical Science
DOI: 10.1039/c5sc04786b
Authors: Florian Häse, Stéphanie Valleau, Edward Pyzer-Knapp, Alán Aspuru-Guzik
Institution: Harvard University
Language: English
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: diamond
Funder: U.S. Department of Energy
OpenAlex ID: W2175728817