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Xin Li

     
Updated:: 2024-12-03  Clicks: 11  




Xin Li

Lecturer

ADDRESSMechanical and Electrical   Engineering Institute, Zhengzhou University of Light Industry

E-mail2023049@zzuli.edu.cn

Research Field and Interests

Evolution mechanism of material organization and properties, digital twin, optimization of material organization and properties based on machine learning

EducationBackground

2018.9-2023.11 Northeastern University  Majored in Material processing engineeringPHD degree

2016.9- 2018.6  Northeastern University  Majored in Material processing engineeringMaster degree

2010.9-2014.7   Henan University of Science and Technology   Majored in Material forming and control engineering (bachelor degree)

Teaching Courses:Theoretical Mechanics

Publications:

[1] 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)

[2] 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)

[3] 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)

[4] 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)

[5] 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)

[6] 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)

[7] 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)

[8] 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)

[9] 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)

Projects

[1] Science and Technology Research Project of He Nan Province242102230069

[2] The Zhengzhou University of Light Industry Doctoral Research Initiation Fund(2024BSJJ003).




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