Interpolating Nonadiabatic Molecular Dynamics Hamiltonian with Bidirectional Long Short-Term Memory Networks

[Image: see text] Essential for understanding far-from-equilibrium processes, nonadiabatic (NA) molecular dynamics (MD) requires expensive calculations of the excitation energies and NA couplings. Machine learning (ML) can simplify computation; however, the NA Hamiltonian requires complex ML models...

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Detalles Bibliográficos
Autores principales: Wang, Bipeng, Winkler, Ludwig, Wu, Yifan, Müller, Klaus-Robert, Sauceda, Huziel E., Prezhdo, Oleg V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10424239/
https://www.ncbi.nlm.nih.gov/pubmed/37530451
http://dx.doi.org/10.1021/acs.jpclett.3c01723

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10424239/
https://www.ncbi.nlm.nih.gov/pubmed/37530451
http://dx.doi.org/10.1021/acs.jpclett.3c01723

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