Learning from data to design functional materials without inversion symmetry

Computational design of functional materials with broken inversion symmetry is a complex task. Here, the authors demonstrate an approach that integrates symmetry analysis, data science methods, and density functional theory to accelerate the selection and identification process in complex oxides.

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Autores principales:	Prasanna V. Balachandran, Joshua Young, Turab Lookman, James M. Rondinelli
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/6caa49546c9f44e8b3a0551c932bbc54
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spelling	oai:doaj.org-article:6caa49546c9f44e8b3a0551c932bbc542021-12-02T15:38:38ZLearning from data to design functional materials without inversion symmetry10.1038/ncomms142822041-1723https://doaj.org/article/6caa49546c9f44e8b3a0551c932bbc542017-02-01T00:00:00Zhttps://doi.org/10.1038/ncomms14282https://doaj.org/toc/2041-1723Computational design of functional materials with broken inversion symmetry is a complex task. Here, the authors demonstrate an approach that integrates symmetry analysis, data science methods, and density functional theory to accelerate the selection and identification process in complex oxides.Prasanna V. BalachandranJoshua YoungTurab LookmanJames M. RondinelliNature PortfolioarticleScienceQENNature Communications, Vol 8, Iss 1, Pp 1-13 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Prasanna V. Balachandran Joshua Young Turab Lookman James M. Rondinelli Learning from data to design functional materials without inversion symmetry
description	Computational design of functional materials with broken inversion symmetry is a complex task. Here, the authors demonstrate an approach that integrates symmetry analysis, data science methods, and density functional theory to accelerate the selection and identification process in complex oxides.
format	article
author	Prasanna V. Balachandran Joshua Young Turab Lookman James M. Rondinelli
author_facet	Prasanna V. Balachandran Joshua Young Turab Lookman James M. Rondinelli
author_sort	Prasanna V. Balachandran
title	Learning from data to design functional materials without inversion symmetry
title_short	Learning from data to design functional materials without inversion symmetry
title_full	Learning from data to design functional materials without inversion symmetry
title_fullStr	Learning from data to design functional materials without inversion symmetry
title_full_unstemmed	Learning from data to design functional materials without inversion symmetry
title_sort	learning from data to design functional materials without inversion symmetry
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/6caa49546c9f44e8b3a0551c932bbc54
work_keys_str_mv	AT prasannavbalachandran learningfromdatatodesignfunctionalmaterialswithoutinversionsymmetry AT joshuayoung learningfromdatatodesignfunctionalmaterialswithoutinversionsymmetry AT turablookman learningfromdatatodesignfunctionalmaterialswithoutinversionsymmetry AT jamesmrondinelli learningfromdatatodesignfunctionalmaterialswithoutinversionsymmetry
_version_	1718386117739282432

Learning from data to design functional materials without inversion symmetry

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