Learning grain boundary segregation energy spectra in polycrystals

Predicting segregation energies of alloy systems can be challenging even for a single grain boundary. Here the authors propose a machine-learning framework, which maps the local environments on a distribution of segregation energies, to predict segregation energies of alloy elements in polycrystalli...

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Autores principales:	Malik Wagih, Peter M. Larsen, Christopher A. Schuh
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/1f55fdb2211c4604ab802a521ce57a38
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id	oai:doaj.org-article:1f55fdb2211c4604ab802a521ce57a38
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spelling	oai:doaj.org-article:1f55fdb2211c4604ab802a521ce57a382021-12-02T13:24:15ZLearning grain boundary segregation energy spectra in polycrystals10.1038/s41467-020-20083-62041-1723https://doaj.org/article/1f55fdb2211c4604ab802a521ce57a382020-12-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-20083-6https://doaj.org/toc/2041-1723Predicting segregation energies of alloy systems can be challenging even for a single grain boundary. Here the authors propose a machine-learning framework, which maps the local environments on a distribution of segregation energies, to predict segregation energies of alloy elements in polycrystalline materials.Malik WagihPeter M. LarsenChristopher A. SchuhNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Malik Wagih Peter M. Larsen Christopher A. Schuh Learning grain boundary segregation energy spectra in polycrystals
description	Predicting segregation energies of alloy systems can be challenging even for a single grain boundary. Here the authors propose a machine-learning framework, which maps the local environments on a distribution of segregation energies, to predict segregation energies of alloy elements in polycrystalline materials.
format	article
author	Malik Wagih Peter M. Larsen Christopher A. Schuh
author_facet	Malik Wagih Peter M. Larsen Christopher A. Schuh
author_sort	Malik Wagih
title	Learning grain boundary segregation energy spectra in polycrystals
title_short	Learning grain boundary segregation energy spectra in polycrystals
title_full	Learning grain boundary segregation energy spectra in polycrystals
title_fullStr	Learning grain boundary segregation energy spectra in polycrystals
title_full_unstemmed	Learning grain boundary segregation energy spectra in polycrystals
title_sort	learning grain boundary segregation energy spectra in polycrystals
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/1f55fdb2211c4604ab802a521ce57a38
work_keys_str_mv	AT malikwagih learninggrainboundarysegregationenergyspectrainpolycrystals AT petermlarsen learninggrainboundarysegregationenergyspectrainpolycrystals AT christopheraschuh learninggrainboundarysegregationenergyspectrainpolycrystals
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Learning grain boundary segregation energy spectra in polycrystals

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