Breaking the Coupled Cluster Barrier for Machine-Learned Potentials of Large Molecules: The Case of 15-Atom Acetylacetone

[Image: see text] Machine-learned potential energy surfaces (PESs) for molecules with more than 10 atoms are typically forced to use lower-level electronic structure methods such as density functional theory (DFT) and second-order Møller–Plesset perturbation theory (MP2). While these are efficient a...

Descripción completa

Detalles Bibliográficos
Autores principales: Qu, Chen, Houston, Paul L., Conte, Riccardo, Nandi, Apurba, Bowman, Joel M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279733/
https://www.ncbi.nlm.nih.gov/pubmed/34006096
http://dx.doi.org/10.1021/acs.jpclett.1c01142

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8279733/
https://www.ncbi.nlm.nih.gov/pubmed/34006096
http://dx.doi.org/10.1021/acs.jpclett.1c01142

Ejemplares similares