Developing novel low-density high-entropy superalloys with high strength and superior creep resistance guided by automated machine learning

doi:10.1016/j.actamat.2024.120656

IMR OpenIR

	Developing novel low-density high-entropy superalloys with high strength and superior creep resistance guided by automated machine learning
	Li, Yancheng 1; Pang, Jingyu 2; Li, Zhen 3; Wang, Qing 1; Wang, Zhenhua 1; Li, Jinlin 1; Zhang, Hongwei 2; Jiao, Zengbao 4; Dong, Chuang 1; Liaw, Peter K.5
通讯作者	Wang, Qing(wangq@dlut.edu.cn) ; Zhang, Hongwei(hongweizhang@imr.ac.cn)
	2025-02-15
发表期刊	ACTA MATERIALIA
ISSN	1359-6454
卷号	285 页码:17
摘要	Design of novel superalloys with low density, high strength, and great microstructural stability is a big challenge. This work used an automated machine learning (ML) model to explore high-entropy superalloys (HESAs) with coherent gamma' nanoprecipitates in the FCC-gamma matrix. The database samples were firstly preprocessed via the domain-knowledge before ML. Both autogluon and genetic algorithm methods were applied to establish the relationship between the alloy composition and yield strength and to deal with the optimization problem in ML. Thus, the ML model cannot only predict the strength with a high accuracy (R-2 > 95 %), but also design compositions efficiently with desired property in multi-component systems. Novel HESAs with targeted strengths and densities were predicted by ML and then validated by a series of experiments. It is found that the experimental results are well consistent with the predicted properties, as evidenced by the fact that the designed Ni-5.82Fe-15.34Co-2.53Al-2.99Ti-2.90Nb-15.97Cr-2.50Mo (wt.%) HESA has a yield strength of 1346 MPa at room temperature and 1061 MPa at 1023 K and a density of 7.98 g/cm(3). Moreover, it exhibits superior creep resistance with a rupture lifetime of 149 h under 480 MPa at 1023 K, outperforming most conventional wrought superalloys. Additionally, the coarsening rate of gamma' nanoprecipitates in these alloys is extremely slow at 1023 K, showing a prominent microstructural stability. The strengthening and deformation mechanisms were further discussed. This framework provides a new pathway to realize the property-oriented composition design for high-performance complex alloys via ML.
关键词	High-entropy superalloys gamma/gamma' microstructural stability Mechanical mechanisms Deformation mechanisms Machine learning
资助者	National Natural Science Foundation of China ; Research Grant Council of Hong Kong ; National Science Foundation ; US Army Research Office
DOI	10.1016/j.actamat.2024.120656
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[U24A2024] ; National Natural Science Foundation of China[52171152] ; Research Grant Council of Hong Kong[15227121] ; National Science Foundation[DMR -1611180] ; National Science Foundation[1809640] ; National Science Foundation[2226508] ; US Army Research Office[W911NF-13-1-0438] ; US Army Research Office[W911NF-19-2-0049]
WOS研究方向	Materials Science ; Metallurgy & Metallurgical Engineering
WOS类目	Materials Science, Multidisciplinary ; Metallurgy & Metallurgical Engineering
WOS记录号	WOS:001394713900001
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计	被引频次：4[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/321006/180879
专题	中国科学院金属研究所
通讯作者	Wang, Qing; Zhang, Hongwei
作者单位	1.Dalian Univ Technol, Engn Res Ctr High Entropy Alloy Mat Liaoning Prov, Sch Mat Sci & Engn, Dalian 116024, Peoples R China 2.Chinese Acad Sci, Inst Met Res, Shi changxu Innovat Ctr Adv Mat, Shenyang 110016, Peoples R China 3.Dalian Univ Technol, Sch Mech Engn, Dalian 116024, Peoples R China 4.Hong Kong Polytech Univ, Res Inst Adv Mfg, Dept Mech Engn, Hong Kong, Peoples R China 5.Univ Tennessee, Dept Mat Sci & Engn, Knoxville, TN 37996 USA
推荐引用方式 GB/T 7714	Li, Yancheng,Pang, Jingyu,Li, Zhen,et al. Developing novel low-density high-entropy superalloys with high strength and superior creep resistance guided by automated machine learning[J]. ACTA MATERIALIA,2025,285:17.
APA	Li, Yancheng.,Pang, Jingyu.,Li, Zhen.,Wang, Qing.,Wang, Zhenhua.,...&Liaw, Peter K..(2025).Developing novel low-density high-entropy superalloys with high strength and superior creep resistance guided by automated machine learning.ACTA MATERIALIA,285,17.
MLA	Li, Yancheng,et al."Developing novel low-density high-entropy superalloys with high strength and superior creep resistance guided by automated machine learning".ACTA MATERIALIA 285(2025):17.