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Accelerated design of high-performance Mg-Mn-based magnesium alloys based on novel bayesian optimization

查看全文 作　　者：Xiaoxi [1,2]Mi;Lili [1]Dai;Xuerui [1]Jing;Jia [1,3]She;Bjørn [4]Holmedal;Aitao [1,3]Tang;Fusheng [1,3]Pan 高影响力作者 机构地区：[1]College of Materials Science and Engineering,Chongqing University,Chongqing 400044,China;[2]Southwest Technology and Engineering Research Institute,Chongqing 400039,China;[3]National Engineering Research Center for Magnesium Alloys,Chongqing University,Chongqing 400044,China;[4]Department of Materials Science and Engineering,Norwegian University of Science and Technology(NTNU),Trondheim 7051,Norway高影响力机构 出　　处：《Journal of Magnesium and Alloys》索引2024年第12卷第2期,共17页高影响力期刊 基　　金：supported by the National Natural the Science Foundation of China(51971042,51901028);the Chongqing Academician Special Fund(cstc2020yszxjcyj X0001);the China Scholarship Council(CSC);Norwegian University of Science and Technology(NTNU)for their financial and technical support。 摘　　要：Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation. 关 键 词：Mg-Mn-based alloys HIGH-PERFORMANCE Alloy design Machine learning Bayesian optimization
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