Force-field-enhanced neural network interactions: from local equivariant embedding to atom-in-molecule properties and long-range effects

We introduce FENNIX (Force-Field-Enhanced Neural Network InteraXions), a hybrid approach between machine-learning and force-fields. We leverage state-of-the-art equivariant neural networks to predict local energy contributions and multiple atom-in-molecule properties that are then used as geometry-d...

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Detalles Bibliográficos
Autores principales: Plé, Thomas, Lagardère, Louis, Piquemal, Jean-Philip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2023
Materias:
Chemistry
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10646944/
https://www.ncbi.nlm.nih.gov/pubmed/38020379
http://dx.doi.org/10.1039/d3sc02581k

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10646944/
https://www.ncbi.nlm.nih.gov/pubmed/38020379
http://dx.doi.org/10.1039/d3sc02581k

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