Machine learning autonomous identification of magnetic alloys beyond the Slater-Pauling limit

Finding materials with large magnetization is highly desirable for technological applications. Here, a machine learning autonomous search and automated combinatorial synthesis reveal that multi-element alloys with Ir and Pt impurities have a magnetization exceeding the Slater-Pauling limit of Fe75Co...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Yuma Iwasaki, Ryohto Sawada, Eiji Saitoh, Masahiko Ishida
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Materials of engineering and construction. Mechanics of materials TA401-492
Acceso en línea:	https://doaj.org/article/157c58c7e40c43eb891e7c9a61f5ce7b
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:157c58c7e40c43eb891e7c9a61f5ce7b
record_format	dspace
spelling	oai:doaj.org-article:157c58c7e40c43eb891e7c9a61f5ce7b2021-12-02T17:04:52ZMachine learning autonomous identification of magnetic alloys beyond the Slater-Pauling limit10.1038/s43246-021-00135-02662-4443https://doaj.org/article/157c58c7e40c43eb891e7c9a61f5ce7b2021-03-01T00:00:00Zhttps://doi.org/10.1038/s43246-021-00135-0https://doaj.org/toc/2662-4443Finding materials with large magnetization is highly desirable for technological applications. Here, a machine learning autonomous search and automated combinatorial synthesis reveal that multi-element alloys with Ir and Pt impurities have a magnetization exceeding the Slater-Pauling limit of Fe75Co25.Yuma IwasakiRyohto SawadaEiji SaitohMasahiko IshidaNature PortfolioarticleMaterials of engineering and construction. Mechanics of materialsTA401-492ENCommunications Materials, Vol 2, Iss 1, Pp 1-7 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Materials of engineering and construction. Mechanics of materials TA401-492
spellingShingle	Materials of engineering and construction. Mechanics of materials TA401-492 Yuma Iwasaki Ryohto Sawada Eiji Saitoh Masahiko Ishida Machine learning autonomous identification of magnetic alloys beyond the Slater-Pauling limit
description	Finding materials with large magnetization is highly desirable for technological applications. Here, a machine learning autonomous search and automated combinatorial synthesis reveal that multi-element alloys with Ir and Pt impurities have a magnetization exceeding the Slater-Pauling limit of Fe75Co25.
format	article
author	Yuma Iwasaki Ryohto Sawada Eiji Saitoh Masahiko Ishida
author_facet	Yuma Iwasaki Ryohto Sawada Eiji Saitoh Masahiko Ishida
author_sort	Yuma Iwasaki
title	Machine learning autonomous identification of magnetic alloys beyond the Slater-Pauling limit
title_short	Machine learning autonomous identification of magnetic alloys beyond the Slater-Pauling limit
title_full	Machine learning autonomous identification of magnetic alloys beyond the Slater-Pauling limit
title_fullStr	Machine learning autonomous identification of magnetic alloys beyond the Slater-Pauling limit
title_full_unstemmed	Machine learning autonomous identification of magnetic alloys beyond the Slater-Pauling limit
title_sort	machine learning autonomous identification of magnetic alloys beyond the slater-pauling limit
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/157c58c7e40c43eb891e7c9a61f5ce7b
work_keys_str_mv	AT yumaiwasaki machinelearningautonomousidentificationofmagneticalloysbeyondtheslaterpaulinglimit AT ryohtosawada machinelearningautonomousidentificationofmagneticalloysbeyondtheslaterpaulinglimit AT eijisaitoh machinelearningautonomousidentificationofmagneticalloysbeyondtheslaterpaulinglimit AT masahikoishida machinelearningautonomousidentificationofmagneticalloysbeyondtheslaterpaulinglimit
_version_	1718381834209853440

Machine learning autonomous identification of magnetic alloys beyond the Slater-Pauling limit

Ejemplares similares