Computational prediction of new auxetic materials

There are very few inorganic materials with auxetic homogenous Poisson’s ratio in polycrystalline form. Here authors develop an approach to screening materials databases for target properties such as negative Poisson’s ratio by using stability and structural motifs to predict new instances of homoge...

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Autores principales:	John Dagdelen, Joseph Montoya, Maarten de Jong, Kristin Persson
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/82292ab548c844e7be40fa476910b250
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spelling	oai:doaj.org-article:82292ab548c844e7be40fa476910b2502021-12-02T13:57:45ZComputational prediction of new auxetic materials10.1038/s41467-017-00399-62041-1723https://doaj.org/article/82292ab548c844e7be40fa476910b2502017-08-01T00:00:00Zhttps://doi.org/10.1038/s41467-017-00399-6https://doaj.org/toc/2041-1723There are very few inorganic materials with auxetic homogenous Poisson’s ratio in polycrystalline form. Here authors develop an approach to screening materials databases for target properties such as negative Poisson’s ratio by using stability and structural motifs to predict new instances of homogenous auxetic behavior as well as a number of materials with near-zero Poisson’s ratio.John DagdelenJoseph MontoyaMaarten de JongKristin PerssonNature PortfolioarticleScienceQENNature Communications, Vol 8, Iss 1, Pp 1-8 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q John Dagdelen Joseph Montoya Maarten de Jong Kristin Persson Computational prediction of new auxetic materials
description	There are very few inorganic materials with auxetic homogenous Poisson’s ratio in polycrystalline form. Here authors develop an approach to screening materials databases for target properties such as negative Poisson’s ratio by using stability and structural motifs to predict new instances of homogenous auxetic behavior as well as a number of materials with near-zero Poisson’s ratio.
format	article
author	John Dagdelen Joseph Montoya Maarten de Jong Kristin Persson
author_facet	John Dagdelen Joseph Montoya Maarten de Jong Kristin Persson
author_sort	John Dagdelen
title	Computational prediction of new auxetic materials
title_short	Computational prediction of new auxetic materials
title_full	Computational prediction of new auxetic materials
title_fullStr	Computational prediction of new auxetic materials
title_full_unstemmed	Computational prediction of new auxetic materials
title_sort	computational prediction of new auxetic materials
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/82292ab548c844e7be40fa476910b250
work_keys_str_mv	AT johndagdelen computationalpredictionofnewauxeticmaterials AT josephmontoya computationalpredictionofnewauxeticmaterials AT maartendejong computationalpredictionofnewauxeticmaterials AT kristinpersson computationalpredictionofnewauxeticmaterials
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Computational prediction of new auxetic materials

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