Physically informed artificial neural networks for atomistic modeling of materials

Traditional machine learning potentials suffer from poor transferability to unknown structures. Here the authors present an approach to improve the transferability of machine-learning potentials by including information on the physical nature of interatomic bonding.

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Autores principales:	G. P. Purja Pun, R. Batra, R. Ramprasad, Y. Mishin
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/4ce116e79e4e45a4ac852f09407b14a1
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spelling	oai:doaj.org-article:4ce116e79e4e45a4ac852f09407b14a12021-12-02T16:50:56ZPhysically informed artificial neural networks for atomistic modeling of materials10.1038/s41467-019-10343-52041-1723https://doaj.org/article/4ce116e79e4e45a4ac852f09407b14a12019-05-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-10343-5https://doaj.org/toc/2041-1723Traditional machine learning potentials suffer from poor transferability to unknown structures. Here the authors present an approach to improve the transferability of machine-learning potentials by including information on the physical nature of interatomic bonding.G. P. Purja PunR. BatraR. RamprasadY. MishinNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-10 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q G. P. Purja Pun R. Batra R. Ramprasad Y. Mishin Physically informed artificial neural networks for atomistic modeling of materials
description	Traditional machine learning potentials suffer from poor transferability to unknown structures. Here the authors present an approach to improve the transferability of machine-learning potentials by including information on the physical nature of interatomic bonding.
format	article
author	G. P. Purja Pun R. Batra R. Ramprasad Y. Mishin
author_facet	G. P. Purja Pun R. Batra R. Ramprasad Y. Mishin
author_sort	G. P. Purja Pun
title	Physically informed artificial neural networks for atomistic modeling of materials
title_short	Physically informed artificial neural networks for atomistic modeling of materials
title_full	Physically informed artificial neural networks for atomistic modeling of materials
title_fullStr	Physically informed artificial neural networks for atomistic modeling of materials
title_full_unstemmed	Physically informed artificial neural networks for atomistic modeling of materials
title_sort	physically informed artificial neural networks for atomistic modeling of materials
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/4ce116e79e4e45a4ac852f09407b14a1
work_keys_str_mv	AT gppurjapun physicallyinformedartificialneuralnetworksforatomisticmodelingofmaterials AT rbatra physicallyinformedartificialneuralnetworksforatomisticmodelingofmaterials AT rramprasad physicallyinformedartificialneuralnetworksforatomisticmodelingofmaterials AT ymishin physicallyinformedartificialneuralnetworksforatomisticmodelingofmaterials
_version_	1718382975358337024

Physically informed artificial neural networks for atomistic modeling of materials

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