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A property-oriented design strategy of high-strength ductile RAFM steels based on machine learning

文献类型：期刊论文

作者Li, Xiaochen1,2; Zheng, Mingjie1,2; Yang, Xinyi1,2; Chen, Pinghan1,2; Ding, Wenyi1
刊名MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING
出版日期2022-04-18
卷号840
ISSN号0921-5093
关键词Machine learning Intelligent design RAFM steel Tensile property High strength and ductility
DOI10.1016/j.msea.2022.142891
通讯作者Zheng, Mingjie(mingjie.zheng@inest.cas.cn) ; Ding, Wenyi(wenyi.ding@inest.cas.cn)
英文摘要Property-oriented design of RAFM steels can greatly enhance the opportunity to discover high-performance structural materials for fusion reactors, which has always been a big challenge. In the present work, the forward and reverse models are established, which are used to capture the mutual relationship of compositions and heat treatment conditions to tensile properties. The intelligent design model, combining the forward model with the reverse model, is developed to design the compositions and heat treatment parameters for RAFM steels with the targeted tensile properties. The validity of the intelligent design model is verified by the experimental data of three RAFM steels reported in the relevant literatures. Using this intelligent design model, a new type of RAFM steel was designed and prepared. In the test temperature range of 25-600 degrees C, the ultimate tensile strength of the new RAFM steel is -100-400 MPa higher than the conventional RAFM steels while maintaining comparable elongation. Therefore, this strategy is suitable for the property-oriented design of RAFM steels and can also be considered as a very promising approach to develop high-performance structural materials.
WOS关键词ACTIVATION FERRITIC/MARTENSITIC STEEL ; HIGH ENTROPY ALLOYS ; MECHANICAL-PROPERTIES ; TENSILE PROPERTIES ; MICROSTRUCTURE STABILITY ; MARTENSITIC STEEL ; IMPACT PROPERTIES ; PRECIPITATION ; SILICON ; TOUGHNESS
资助项目National Natural Science Foundation of China[11632001] ; National Magnetic Confinement Fusion Science Program of China[2018YFE0307104]
WOS研究方向Science & Technology - Other Topics ; Materials Science ; Metallurgy & Metallurgical Engineering
语种英语
出版者ELSEVIER SCIENCE SA
WOS记录号WOS:000781860300004
资助机构National Natural Science Foundation of China ; National Magnetic Confinement Fusion Science Program of China
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/131480]  
专题中国科学院合肥物质科学研究院
通讯作者Zheng, Mingjie; Ding, Wenyi
作者单位1.Chinese Acad Sci, Hefei Inst Phys Sci, Hefei 230031, Anhui, Peoples R China
2.Univ Sci & Technol China, Hefei 230026, Anhui, Peoples R China
推荐引用方式
GB/T 7714		 Li, Xiaochen,Zheng, Mingjie,Yang, Xinyi,et al. A property-oriented design strategy of high-strength ductile RAFM steels based on machine learning[J]. MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING,2022,840.
APA Li, Xiaochen,Zheng, Mingjie,Yang, Xinyi,Chen, Pinghan,&Ding, Wenyi.(2022).A property-oriented design strategy of high-strength ductile RAFM steels based on machine learning.MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING,840.
MLA Li, Xiaochen,et al."A property-oriented design strategy of high-strength ductile RAFM steels based on machine learning".MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING 840(2022).

入库方式： OAI收割

来源：合肥物质科学研究院

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