Machine learning-enabled design of Fe-based bulk metallic glasses for superior thermal neutron absorption properties

doi:10.1016/j.jallcom.2024.177595

IMR OpenIR

	Machine learning-enabled design of Fe-based bulk metallic glasses for superior thermal neutron absorption properties
	Gao, Jin 1,2; Hou, Jianxin 3; Wu, Yuting 1; Ji, Baoting 2; Wang, Debin 2; Qiu, Keqiang 1; You, Junhua 1; Wang, Jianqiang 2
通讯作者	Hou, Jianxin(jxhou@lam.ln.cn) ; Qiu, Keqiang(kqqiu@sut.edu.cn) ; Wang, Jianqiang(jqwang@imr.ac.cn)
	2025-01-05
发表期刊	JOURNAL OF ALLOYS AND COMPOUNDS
ISSN	0925-8388
卷号	1010 页码:10
摘要	The pressing demand for innovative Fe-based amorphous alloys that excel in both glass-forming ability (GFA) and neutron-absorption has led to the exploration of novel alloying concepts incorporating high levels of B and Gd. In this study, we utilized AutoGluon, an advance autoML framework, to pinpoint the optimal feature sets for predicting the Dmax in Fe-based bulk metallic glasses (BMGs), effectively excluding characteristic temperatures from our analysis. This approach was validated across a dataset of 241 data points, achieving an R2 of 0.817 and an MSE of 1.88. Further, we applied the SHAP method to determine critical conditions that enhance GFA, aligning these with the feature distribution of the extrapolated BMGs. Consequently, we successfully fabricated the alloy (Fe0.72B0.22Nb0.04Cr0.02)96.5Gd3.5, which not only reached a Dmax of 3 mm but also exhibited superior neutron absorption properties. This research enhances our understanding of GFA and supports the development of innovative Fe-based BMGs with optimized material properties.
关键词	Bulk metallic glasses Machine learning Nuclear energy Glass-forming ability Neutron absorption
资助者	National Natural Science Foundation of China ; Key Research Program of the Chinese Academy of Sciences ; Liaoning Applied Basic Research Program ; Basic scientific research project of Liaoning Province Department of Education ; Shenyang Science and Technology Project
DOI	10.1016/j.jallcom.2024.177595
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[U1908219] ; National Natural Science Foundation of China[52171163] ; Key Research Program of the Chinese Academy of Sciences[ZDRW-CN-2021-2-2] ; Liaoning Applied Basic Research Program[2023JH2/101300011] ; Basic scientific research project of Liaoning Province Department of Education[LJKZZ20220024] ; Shenyang Science and Technology Project[23-407-3-13]
WOS研究方向	Chemistry ; Materials Science ; Metallurgy & Metallurgical Engineering
WOS类目	Chemistry, Physical ; Materials Science, Multidisciplinary ; Metallurgy & Metallurgical Engineering
WOS记录号	WOS:001361340400001
出版者	ELSEVIER SCIENCE SA
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/191729
专题	中国科学院金属研究所
通讯作者	Hou, Jianxin; Qiu, Keqiang; Wang, Jianqiang
作者单位	1.Shenyang Univ Technol, Sch Mat Sci & Engn, Shenyang 110870, Peoples R China 2.Chinese Acad Sci, Inst Met Res, Shenyang Natl Lab Mat Sci, Shenyang 110016, Peoples R China 3.Liaoning Acad Mat, Inst Mat Intelligent Technol, Shenyang 110004, Peoples R China
推荐引用方式 GB/T 7714	Gao, Jin,Hou, Jianxin,Wu, Yuting,et al. Machine learning-enabled design of Fe-based bulk metallic glasses for superior thermal neutron absorption properties[J]. JOURNAL OF ALLOYS AND COMPOUNDS,2025,1010:10.
APA	Gao, Jin.,Hou, Jianxin.,Wu, Yuting.,Ji, Baoting.,Wang, Debin.,...&Wang, Jianqiang.(2025).Machine learning-enabled design of Fe-based bulk metallic glasses for superior thermal neutron absorption properties.JOURNAL OF ALLOYS AND COMPOUNDS,1010,10.
MLA	Gao, Jin,et al."Machine learning-enabled design of Fe-based bulk metallic glasses for superior thermal neutron absorption properties".JOURNAL OF ALLOYS AND COMPOUNDS 1010(2025):10.