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Machine learning assisted design of high entropy alloys with desired property
文献类型：期刊论文
| 作者 | Wen C5,6,7; Zhang Y6,7; Wang CX6,7 ; Xue DZ4; Bai Y6,7; Antonov S3,7; Dai LH(戴兰宏)2; Lookman T1; Su YJ6,7
|
| 刊名 | ACTA MATERIALIA
 |
| 出版日期 | 2019-05-15 |
| 卷号 | 170页码:109-117 |
| 关键词 | Multi-principal element alloys Active learning Machine learning Materials genome initiative |
| ISSN号 | 1359-6454 |
| DOI | 10.1016/j.actamat.2019.03.010 |
| 通讯作者 | Xue, Dezhen(xuedezhen@xjtu.edu.cn) ; Su, Yanjing(yjsu@ustb.edu.cn) |
| 英文摘要 | We formulate a materials design strategy combining a machine learning (ML) surrogate model with experimental design algorithms to search for high entropy alloys (HEAs) with large hardness in a model Al-Co-Cr-Cu-Fe-Ni system. We fabricated several alloys with hardness 10% higher than the best value in the original training dataset via only seven experiments. We find that a strategy using both the compositions and descriptors based on a knowledge of the properties of HEAs, outperforms that merely based on the compositions alone. This strategy offers a recipe to rapidly optimize multi-component systems, such as bulk metallic glasses and superalloys, towards desired properties. (C) 2019 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved. |
| 分类号 | 一类 |
| URL标识 | 查看原文 |
| WOS关键词 | MECHANICAL-PROPERTIES ; PHASE SELECTION ; BEHAVIOR ; MICROSTRUCTURE ; THERMODYNAMICS ; ELEMENT ; ALCOCRCUFENI ; SEARCH |
| 资助项目 | National Key Research and Development Program of China[2016YFB0700505] ; National Natural Science Foundation of China[51671157] ; 111 project[B170003] ; Los Alamos National Laboratory |
| WOS研究方向 | Materials Science ; Metallurgy & Metallurgical Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000466252400010 |
| 资助机构 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; 111 project ; Los Alamos National Laboratory |
| 其他责任者 | Xue, Dezhen ; Su, Yanjing |
| 源URL | [http://dspace.imech.ac.cn/handle/311007/79185]  |
| 专题 | 力学研究所_非线性力学国家重点实验室 |
| 作者单位 | 1.Los Alamos Natl Lab, Div Theoret, Los Alamos, NM 87545 USA 2.Chinese Acad Sci, Inst Mech, Lab Nonlinear Mech Continuous Media LNM, Beijing 100080, Peoples R China; 3.Univ Sci & Technol Beijing, State Key Lab Adv Met & Mat, Beijing 100083, Peoples R China; 4.Xi An Jiao Tong Univ, State Key Lab Mech Behav Mat, Xian 710049, Peoples R China; 5.Guangdong Ocean Univ, Sch Mech & Power Engn, Zhanjiang 524000, Peoples R China; 6.Univ Sci & Technol Beijing, Ctr Corros & Protect, Beijing 100083, Peoples R China; 7.Univ Sci & Technol Beijing, Beijing Adv Innovat Ctr Mat Genome Engn, Beijing 100083, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Wen C,Zhang Y,Wang CX,et al. Machine learning assisted design of high entropy alloys with desired property[J]. ACTA MATERIALIA,2019,170:109-117. |
| APA | Wen C.,Zhang Y.,Wang CX.,Xue DZ.,Bai Y.,...&Su YJ.(2019).Machine learning assisted design of high entropy alloys with desired property.ACTA MATERIALIA,170,109-117. |
| MLA | Wen C,et al."Machine learning assisted design of high entropy alloys with desired property".ACTA MATERIALIA 170(2019):109-117. |
入库方式： OAI收割
来源：力学研究所
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