李鑫

发布时间:2024-06-05作者:设置

李鑫  硕士生导师

学位:工学博士

职称:讲师

毕业院校:东北大学

办公地点:西四楼301

联系方式:2023049@zzuli.edu.cn

 

个人简介

主要从事钢铁材料组织性能预测及工艺智能优化等研究工作。研究了典型微合金钢再结晶与析出行为机器学习及应用。近年来,作为研究人员,主持河南省自然科学基金项目1项,河南省科技攻关项目1项,参与国家重点研发计划项目和校企合作项目等科研项目6项,研究成果以第一作者在《Journal of Materials Research and Technology》、《Materials Characterization》和《Metallurgical   and Materials Transactions A》等国内外著名期刊发表论文10余篇,其中SCI收录8篇,EI收录1篇,国际会议论文1篇。作为主要发明人,授权发明专利6件,授权软件著作权4项。

 

研究方向

材料组织性能演变机理

数字孪生

基于机器学习的材料组织性能优化

 

教育背景

2018.09-2023.11,东北大学,材料加工工程,博士

2016.09-2018.06,东北大学,材料加工工程,硕士

2012.09-2016.06,河南科技大学,材料成型及控制工程,学士

 

开设课程

《理论力学B》《材料力学A》等

科研项目

[1] 河南省自然科学基金项目(252300421576),融合机器学习与冶金机理的热轧Ti微合金钢析出与再结晶行为研究,2025-2026,主持。

[2] 河南省科技攻关项目(242102230069),数据驱动高强度低合金钢形性柔性调控关键技术研究,2024-2025,主持。

[3] 郑州轻工业大学博士启动基金(2024BSJJ003),融合机器学习与冶金机理的热轧Ti微合金钢析出与再结晶行为研究,2024-2026,主持


论文专著与专利

专利:

[1]一种涡轮式孕育剂混合装置,实用新型专利,ZL202422021620.5。

[2]一种预测Nb微合金钢动态再结晶分数的方法, 发明专利,ZL202010766776.X。

[3]一种预测Nb微合金钢动态再结晶型流变应力的方法, 发明专利,ZL202010767229.3.

[4]一种厚规格高韧性X80管线钢及其生产方法, 发明专利,ZL202010781072.X.

[5]一种屈服强度555MPa级高韧性管线钢及其生产方法, 发明专利, ZL202010781065.X.

[6]一种含Sn超级奥氏体不锈钢冷轧板的制备方法, 发明专利, ZL201710279915.4.

[7]一种热轧低碳钢氧化铁皮结构演变数字解析方法, 发明专利, ZL20201 0966429.1.

论文:

[1]Li Xin, Cao Wenqi, Mao Feng, Wu Siwei, Shi Ruxing, Yu Baoning, Lin Yichou, Tian Shuxia, Miao Kunlin,Wei Shizhong, Prediction and optimization of flaw detection qualification rate for 12Cr2Mo1V large cylindrical forgings using random forest and particle swarm optimization[J]. Steel Research International, 2026. DOI:10.1002/srin.70679. (SCI)

[2]Li Xin, Guo Junhua, Fan Jianglei, Wang Yongbiao, Li Yanyan, Zhou Xiaoguang, Tian Shuxia, Mao Feng, Miao Kunlin, Wei Shizhong, Optimization of smelting process of magnesium based on machine learning[J]. Journal of Mining and Metallurgy, Section B: Metallurgy, 2026, 62(1), 41-52. (SCI)

[3]Li   Xin, Jiang Qi-ming, Zhou Xiao-guang, Wu Si-wei, Cao Guang-ming, Liu Zhen-yu. Machine learning interphase precipitation behavior of Ti micro-alloyed steel guided by physical metallurgy principle [J]. Journal of Materials Research and Technology, 2023, 25: 2641-2653. (SCI, TOP期刊)

[4]Li Xin, Gao Fei, Jiao Jun-hong, Cao Guang-ming, Wang Yong, Liu Zhen-yu. Influences of cooling rates on delta ferrite of nuclear power 316H austenitic stainless steel [J]. Materials   Characterization, 2021, 174:111029. (SCI, TOP期刊)

[5]Li Xin, Zhou   Xiao-guang, Cao Guang-ming, Xu Shao-hua, Wang Yong, Liu Zhen-yu.   Machine learning hot deformation behavior of Nb micro-alloyed steels and its   extrapolation to dynamic recrystallization kinetics [J]. Metallurgical and   Materials Transactions A, 2021, 52:3171-3181. (SCI)

[6]Li Xin,   Jiang Qi-ming, Zhou Xiao-guang, Cao Guang-ming, Wang Guo-dong, Liu Zhen-yu. Machine learning complex interactions   among recovery, precipitation, and recrystallization for Nb micro-alloyed   steels [J]. Metals and Materials   International, 2023, 30: 167-181. (SCI)

[7]Li Xin, Zhou Xiao-guang, Jiang Qi-ming, Liu Zhen-yu. The prediction of   the mechanical properties for hot rolled Nb micro-alloyed dual-phase steel   based on microstructure characteristics [J]. JOM, 2023, 75(7): 2225-2234. (SCI)

[8]Li Xin,   Jiang Qi-ming, Cui Chun-yuan, Zhou Xiao-guang, Cao Guang-ming, Liu Zhen-yu. Physical metallurgy guided machine   learning for strain-induced precipitation of Nb (C, N) based on the   orthogonalized small data [J]. Steel Research International,2023, 94: 2200722.(SCI)

[9]Li Xin, Jiang Qi-ming, Zhou Xiao-guang, Wu Si-wei, Cao Guang-ming, Liu   Zhen-yu. Modelling the double-pass flow curve of Nb micro-alloyed   steel by machine learning and its extrapolation to static softening kinetics   [J]. Journal of Materials Engineering   and Performance,2024, 33: 3669–3679. (SCI)

[10]Zhou   Xiao-guang, Li Xin*, Zeng   Cai-you, Wu Si-wei, Liu Zhen-yu. Austenite grain growth and its equation in   the austenitizing process for 700MPa grade high strength steel [J].   Transactions of the Indian Institute of Metals, 2023, 76: 3115–3125. (SCI)

[11]Li Xin, Zhou Xiao-guang, Liu   Zhen-yu. Machine learning strain-induced precipitation behavior of   Nb(C,N) [C]. The 6th International Conference on ThermoMechanical Processing   (TMP), 2022.9, Shenyang, China. (EI)

[12]李鑫, 周晓光, 曹光明, 崔春圆, 吴思炜, 刘振宇. 融合物理冶金学与机器学习的组织性能预测及热轧工艺优化[J]. 冶金自动化, 2023, 47 (2): 16-26. (核心)

[13]李鑫,郭军华,王永彪,张廷安. 相对真空下铝热法制备金属镁及镁铝尖晶石[J]. 有色金属科学与工程, 2025 ,1-11 [2026-09-07]. https://link.cnki.net/urlid/36.1311.TF.20251215.1046.002. (核心)

 

荣誉获奖

[1] 第八届中国TRIZ杯大学生创新方法大赛,国家级一等奖,2020。

[2]全国大学生冶金科技竞赛,国家级三等奖,2020。

[3]“钢研杯”材料高温原位微观组织图像竞赛,国家级三等奖,2018。

[4]“钢研杯”2019年全国钢铁材料透射电镜图像竞赛,国家级优秀奖,2020。

[5]2020年辽宁省创新方法大赛暨第六届辽宁省TRIZ杯大学生创新方法大赛,省级一等奖,2020。

[6]第二届辽宁省人工智能应用大赛, 省级三等奖,2020。


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