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Predictions on the Phase Constitution of SmCo(7−X)M(x) Alloys by Data Mining
Based on a home-built Sm-Co-based alloys database, this work proposes a support vector machine model to study the concurrent effects of element doping and microstructure scale on the phase constitution of SmCo(7)-based alloys. The results indicated that the doping element’s melting point and electro...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9100234/ https://www.ncbi.nlm.nih.gov/pubmed/35564161 http://dx.doi.org/10.3390/nano12091452 |
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author | Xu, Guojing Lu, Hao Guo, Kai Tang, Fawei Song, Xiaoyan |
author_facet | Xu, Guojing Lu, Hao Guo, Kai Tang, Fawei Song, Xiaoyan |
author_sort | Xu, Guojing |
collection | PubMed |
description | Based on a home-built Sm-Co-based alloys database, this work proposes a support vector machine model to study the concurrent effects of element doping and microstructure scale on the phase constitution of SmCo(7)-based alloys. The results indicated that the doping element’s melting point and electronegativity difference with Co are the key features that affect the stability of the 1:7 H phase. High-throughput predictions on the phase constitution of SmCo(7)-based alloys with various characteristics were achieved. It was found that doping elements with electronegativity differences with Co that are smaller than 0.05 can significantly enhance 1:7 H phase stability in a broad range of grain sizes. When the electronegativity difference increases to 0.4, the phase stability becomes more dependent on the melting point of the doping element, the doping concentration, and the mean grain size of the alloy. The present data-driven method and the proposed rule for 1:7 H phase stabilization were confirmed by experiments. This work provides a quantitative strategy for composition design and tailoring grain size to achieve high stability of the 1:7 H phase in Sm-Co-based permanent magnets. The present method is applicable for evaluating the phase stability of a wide range of metastable alloys. |
format | Online Article Text |
id | pubmed-9100234 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91002342022-05-14 Predictions on the Phase Constitution of SmCo(7−X)M(x) Alloys by Data Mining Xu, Guojing Lu, Hao Guo, Kai Tang, Fawei Song, Xiaoyan Nanomaterials (Basel) Article Based on a home-built Sm-Co-based alloys database, this work proposes a support vector machine model to study the concurrent effects of element doping and microstructure scale on the phase constitution of SmCo(7)-based alloys. The results indicated that the doping element’s melting point and electronegativity difference with Co are the key features that affect the stability of the 1:7 H phase. High-throughput predictions on the phase constitution of SmCo(7)-based alloys with various characteristics were achieved. It was found that doping elements with electronegativity differences with Co that are smaller than 0.05 can significantly enhance 1:7 H phase stability in a broad range of grain sizes. When the electronegativity difference increases to 0.4, the phase stability becomes more dependent on the melting point of the doping element, the doping concentration, and the mean grain size of the alloy. The present data-driven method and the proposed rule for 1:7 H phase stabilization were confirmed by experiments. This work provides a quantitative strategy for composition design and tailoring grain size to achieve high stability of the 1:7 H phase in Sm-Co-based permanent magnets. The present method is applicable for evaluating the phase stability of a wide range of metastable alloys. MDPI 2022-04-24 /pmc/articles/PMC9100234/ /pubmed/35564161 http://dx.doi.org/10.3390/nano12091452 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Xu, Guojing Lu, Hao Guo, Kai Tang, Fawei Song, Xiaoyan Predictions on the Phase Constitution of SmCo(7−X)M(x) Alloys by Data Mining |
title | Predictions on the Phase Constitution of SmCo(7−X)M(x) Alloys by Data Mining |
title_full | Predictions on the Phase Constitution of SmCo(7−X)M(x) Alloys by Data Mining |
title_fullStr | Predictions on the Phase Constitution of SmCo(7−X)M(x) Alloys by Data Mining |
title_full_unstemmed | Predictions on the Phase Constitution of SmCo(7−X)M(x) Alloys by Data Mining |
title_short | Predictions on the Phase Constitution of SmCo(7−X)M(x) Alloys by Data Mining |
title_sort | predictions on the phase constitution of smco(7−x)m(x) alloys by data mining |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9100234/ https://www.ncbi.nlm.nih.gov/pubmed/35564161 http://dx.doi.org/10.3390/nano12091452 |
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