报告题目：机器学习设计增材制造专用新材料

报告人：谭超林

主持人（邀请人）：杨宏宇 研究员，邱丰  教授

报告时间：11月28日下午17:00—18:00

报告地点：逸夫机械材料馆209

主办单位：吉林大学材料科学与工程学院

报告摘要：

Existing commercial materials for laser additive manufacturing (LAM) were designed for traditional manufacturing methods, which mostly require post heat treatments (PHT). LAM's unique cyclic thermal history induces intrinsic heat treatment (IHT) on materials during deposition, which offers an opportunity to develop LAM-customized new materials. This report will introduce novel green steels customized by machine learning to leverage the IHT effect for in-situ forming massive precipitates during LAM without PHT. The intermittent interlayer deposition strategy and the high cooling rate of LAM lead to the formation of a martensitic matrix containing high-density dislocations. Fast precipitation kinetics and the IHT effect during subsequent layer depositions facilitate the heterogeneous nucleation of precipitates (e.g., Ni3(Ti, Al) and Cr3C7) on dislocations. The as-built steel achieves an excellent strength-ductility synergy, superior to a wide range of as-LAM-processed high-strength steels. The finding highlights materials customization for AM based on unique metallurgical features and machine learning for achieving high performance, energy efficiency and sustainability.

演讲嘉宾简介：

谭超林现任新加坡制造技术研究院(SIMTech)资深科学家(Senior Scientist)、首席研究员和博士生导师。江苏省特聘教授、国家级青年拔尖人才、英国伯明翰大学荣誉研究员、国际先进材料协会会士(FIAAM)。长期从事金属增材制造装备、工艺、材料等基础和应用研究。连续入选2022-2024全球前2%科学家榜单(位列SIMTech第一)。主持新加坡航空专项等国家级研究项目4项，指导博士生5名。以第一作者和通讯作者在Advanced Science、Int. J. Mach. Tools Manuf. (6篇)、Int. J. Extreme Manuf. (4篇)等期刊发表SCI论文40余篇，其中IF大于10的19篇，ESI热点和高被引6篇。出版增材制造署名专著2部。Google Scholar被引4000余次，H因子34。担任机械顶刊Int. J. Mach. Tools Manuf. (IF 14)编委(Editorial Board)。同时，担任中科院一区期刊The Innovation (IF 33.2)、Int. J. Extreme Manuf. (IF 16.1)、J Mater Sci Technol. (IF11.2)、Rare Metals (IF 9.6)、Mater. Res. Lett. (IF 8.6)等期刊青年编辑。研究活动被中国中央政府网、人民网、新华社等媒体报道。