ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost

Deep learning is revolutionizing many areas of science and technology, especially image, text, and speech recognition. In this paper, we demonstrate how a deep neural network (NN) trained on quantum mechanical (QM) DFT calculations can learn an accurate and transferable potential for organic molecul...

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Detalles Bibliográficos
Autores principales: Smith, J. S., Isayev, O., Roitberg, A. E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Royal Society of Chemistry 2017
Materias:
Chemistry
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414547/
https://www.ncbi.nlm.nih.gov/pubmed/28507695
http://dx.doi.org/10.1039/c6sc05720a

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5414547/
https://www.ncbi.nlm.nih.gov/pubmed/28507695
http://dx.doi.org/10.1039/c6sc05720a

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