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Machine Learning Customized Green Metal for 4D Printing

发布者:谭超林发布时间:2023-06-13浏览量:

湖南大学岳麓材料青年学者论坛235

目:Machine Learning Customized Green Metal for 4D Printing

报告人:谭超林 博士/首席研究员

点:中三栋205会议室

间:2023615日(周四)下午16:00-17:00

主持人:蒋福林 副教授

邀请人:材料科学与工程学院

报告摘要:Existing commercial powders for laser additive manufacturing (LAM) were designed for traditional manufacturing methods requiring 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 a novel green steel 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 Ni3(Ti, Al) precipitates on dislocations. The as-built steel achieves a tensile strength of 1538 MPa and a uniform elongation of 8.1%, superior to a wide range of as-LAM-processed high-strength steel. The finding highlights in-situ 4D printing via the synchronous integration of time-dependent precipitation hardening with 3D geometry shaping, which shows high energy efficiency and sustainability.


报告人简介:谭超林博士现任新加坡制造技术研究院科学家(Scientist)和博士生导师, CSC公派博士生外方导师。长期从事金属增材制造基础和应用研究。2019年获英国伯明翰大学荣誉研究员,2022年入选国际先进材料协会会士(IAAM Fellow)和全球前2%顶尖科学家榜单。主持新加坡国家级基础研究项目3项,总经费超过500万元人民币。以第一作者发表SCI论文26篇,通讯作者SCI论文7篇, 其中中科院一区Top期刊23篇,包括Advanced Science (IF 17.5)和Int. J. Mach. Tools Manuf. (6篇)等影响因子大于10的优秀期刊14篇。多篇入选ESI热点/高被引。Google Scholar被引2000余次, H-index 23。参与撰写并署名专业书籍《粉末床激光熔融技术》1部(59万字)。担任机械顶刊Int. J. Mach. Tools Manuf. (IF 10.33)长聘编委,Int. J. Extreme Manuf. (IF 10.03)、J Mater Sci Technol. (IF 10.03)、Mater. Res. Lett. (IF 8.51)和Rare Metals (IF 6.32)青年编辑。是波兰科学院项目和中国自然科学基金面上项目评审专家,Nat. Commun.等20余种SCI期刊审稿人。



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