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RESEARCH PAPER · Fusion Engineering and Design · 2020

Composition optimization of high strength and ductility ODS alloy based on machine learning

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42 direct citing works

Composition optimization of high strength and ductility ODS alloy based on machine learningOriginalDeep Convolutional Neural Network Modeling and Laplace Transformation Algorithm for the Analysis of Surface Quality of Friction Stir Welded Joints5Materials Informatics for Mechanical Deformation: A Review of Applications and Challenges67Composition optimization of radiation resistance ODS alloy with high strength and ductility for advanced reactor based on machine learning8Preparation and property optimization of FeCrAl-based ODS alloy by machine learning combined with wedge-shaped hot-rolling31Influence analysis of alloy elements on irradiation embrittlement of RPV steel based on deep neural network13Achieving excellent mechanical properties of ODS steel by Y2O3 addition56Bayesian approach for inferrable machine learning models of process–structure–property linkages in complex concentrated alloys25Unleashing the Power of Artificial Intelligence in Materials Design179Composition design and optimization of Fe–C–Mn–Al steel based on machine learning7Predicting Irradiation Hardening of Ods Steels: An Interpretable Machine Learning Approach with Microstructural Features0The influence of alloy composition on neutron irradiation swelling of austenitic stainless steel by deep neural network0Prediction of creep rupture life of ODS steels based on machine learning13Prediction of hardness or yield strength for ODS steels based on machine learning15Effect of annealing temperature on the evolution of microstructure, texture, and mechanical properties of hot-rolled 12Cr-ODS steel12Additive manufacturing of FeCrAl alloys for nuclear applications - A focused review33Cost-Effective Thermomechanical Processing of Nanostructured Ferritic Alloys: Microstructure and Mechanical Properties Investigation0Intelligent optimization of cold radial forging process for 20CrMnTiH alloy based on GA-BP and performance analysis8Studying corrosion resistance of ODS steels in supercritical water by machine learning5Comparison of microstructure and mechanical properties of ODS nickel-based alloy fabricated by laser powder bed fusion and spark plasma sintering1Research on the prediction of component activity silicon-based binary melt using the MIVM and machine learning algorithms2Superior plastic flow stability of self-patterned carbide – amorphous ceramic nanostructures2Intelligent reconfiguration of production mechanism for anomalous-performance seamless steel tubes via dual optimization of production cycle and operational loss0Machine Learning Approaches for Heat Treatment in Thermal Manufacturing Processes: A Review9Prediction of the tensile properties of ODS ferritic/martensitic steels under various temperature conditions using interpretable machine learning models4Machine Learning Applied to High Entropy Alloys under Irradiation8Application and challenges of artificial intelligence technology in ODS steel research: A review0

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  1. Deep Convolutional Neural Network Modeling and Laplace Transformation Algorithm for the Analysis of Surface Quality of Friction Stir Welded Joints

    Gredos (University of Salamanca) · 2021-10-01

    Akshansh Mishra, Anusri Patti

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  2. Materials Informatics for Mechanical Deformation: A Review of Applications and Challenges

    Materials · 2021-10-02

    Karol Frydrych, Kamran Karimi, Michal Pecelerowicz, Rene Alvarez, Francesco Javier Dominguez-Gutiérrez, Fabrizio Rovaris, Stefanos Papanikolaou

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  3. Composition optimization of radiation resistance ODS alloy with high strength and ductility for advanced reactor based on machine learning

    Journal of Nuclear Science and Technology · 2021-12-02

    Bing Zhe Bai, Xu Han, Han Bing Cao, Xinfu He, Changyi Zhang, Wen Luh Yang

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  4. Preparation and property optimization of FeCrAl-based ODS alloy by machine learning combined with wedge-shaped hot-rolling

    Materials Characterization · 2022-04-12

    Linhong Deng, Changhao Wang, Jinru Luo, Jian Tu, Ning Guo, Haiyan Xu, Pei He, Shengquan Xia, Zhongwen Yao

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  5. Influence analysis of alloy elements on irradiation embrittlement of RPV steel based on deep neural network

    International Journal of Advanced Nuclear Reactor Design and Technology · 2023-03-01

    Bing Zhe Bai, Xu Han, Lixia Jia, Xinfu He, Changyi Zhang, Wen Luh Yang

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  6. Achieving excellent mechanical properties of ODS steel by Y2O3 addition

    Materials Science and Engineering A · 2023-04-05

    Linhong Deng, Jinru Luo, Jian Tu, Rong Hu, Ning Guo, Wen-yu Zeng, Chang-hao Wang, Pei He, Yong Zhang

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  7. Bayesian approach for inferrable machine learning models of process–structure–property linkages in complex concentrated alloys

    Journal of Alloys and Compounds · 2023-08-01

    George Stephen Thoppil, Jian‐Feng Nie, Alankar Alankar

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  8. Unleashing the Power of Artificial Intelligence in Materials Design

    Materials · 2023-08-30

    Silvia Badini, Stefano Regondi, Raffaele Pugliese

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  9. Composition design and optimization of Fe–C–Mn–Al steel based on machine learning

    Physical Chemistry Chemical Physics · 2024-01-01

    Hong Cheng, Zhongping He, Meiling Ge, Lun Che, Kaiyuan Zheng, Tianyu Si, Feng Zhao

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  10. Predicting Irradiation Hardening of Ods Steels: An Interpretable Machine Learning Approach with Microstructural Features

    SSRN Electronic Journal · 2024-01-01

    Tian-Xing Yang, Peng Dou

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  11. The influence of alloy composition on neutron irradiation swelling of austenitic stainless steel by deep neural network

    Mechanical Engineering Journal · 2024-01-01

    Bing Zhe Bai, Xu Han, Shi WU, Jin Gao, Xinfu He, Wen Luh Yang

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  12. Prediction of creep rupture life of ODS steels based on machine learning

    Materials Today Communications · 2024-01-21

    Tian-Xing Yang, Peng Dou

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  13. Prediction of hardness or yield strength for ODS steels based on machine learning

    Materials Characterization · 2024-04-06

    Tian-Xing Yang, Akihiko Kimura, Peng Dou

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  14. Effect of annealing temperature on the evolution of microstructure, texture, and mechanical properties of hot-rolled 12Cr-ODS steel

    Journal of Materials Research and Technology · 2024-04-24

    Jiajie Li, Jingxian Chen, Zhangjing You, Liping Deng, Chen Wang, Junfeng Chen, Lei Xiao, Bingshu Wang

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  15. Additive manufacturing of FeCrAl alloys for nuclear applications - A focused review

    Nuclear Materials and Energy · 2024-07-14

    Selvamurugan Palaniappan, Sameehan S. Joshi, Shashank Sharma, Madhavan Radhakrishnan, K.V. Mani Krishna, Narendra B. Dahotre

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  16. Cost-Effective Thermomechanical Processing of Nanostructured Ferritic Alloys: Microstructure and Mechanical Properties Investigation

    Materials · 2024-09-28

    Yan-Ru Lin, Yajie Zhao, Yi‐Feng Su, Thak Sang Byun

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  17. Intelligent optimization of cold radial forging process for 20CrMnTiH alloy based on GA-BP and performance analysis

    The International Journal of Advanced Manufacturing Technology · 2024-11-06

    Wenxia Xu, Zhaohui Wang, Xuwen Zhu, Bowen Zhang, Zecheng Zheng, Mi Lv, Hongxia Wang

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  18. Studying corrosion resistance of ODS steels in supercritical water by machine learning

    Journal of Iron and Steel Research International · 2025-04-08

    Tian-Xing Yang, Peng Dou

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  19. Comparison of microstructure and mechanical properties of ODS nickel-based alloy fabricated by laser powder bed fusion and spark plasma sintering

    Powder Metallurgy · 2025-04-24

    Dinh Van Cong, Dong-Wan Lee, Su-Gwan Lee, Hwi-Jun Kim, Joong-Gyeong Lim, Tae Sik Yoon, Jin-Chun Kim

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  20. Research on the prediction of component activity silicon-based binary melt using the MIVM and machine learning algorithms

    International Communications in Heat and Mass Transfer · 2025-05-08

    Fen Zou, Zuhan Shan, Qunzhi Wang, Jijun Wu, Kuixian Wei, Zhengjie Chen, Wenhui Ma

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  21. Superior plastic flow stability of self-patterned carbide – amorphous ceramic nanostructures

    Materials Research Letters · 2025-05-20

    Wenqian Wu, Lin Shao, Nan Li, Lin Li, Jian Wang

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  22. Intelligent reconfiguration of production mechanism for anomalous-performance seamless steel tubes via dual optimization of production cycle and operational loss

    Journal of Iron and Steel Research International · 2025-05-26

    Ao Guo, Ting-song Yang, Jian Shao, Desheng Chen, Jing Hao, Hui-min Wang, Su-yue Wang, Can-kun Zhang

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  23. Machine Learning Approaches for Heat Treatment in Thermal Manufacturing Processes: A Review

    ASME Journal of Heat and Mass Transfer · 2025-07-31

    Adib Bazgir, Yuwen Zhang

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  24. Prediction of the tensile properties of ODS ferritic/martensitic steels under various temperature conditions using interpretable machine learning models

    Intermetallics · 2025-08-23

    Zhan-Xing Li, Tian-Xing Yang, Akihiko Kimura, Peng Dou

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  25. Machine Learning Applied to High Entropy Alloys under Irradiation

    Advanced Engineering Materials · 2025-11-04

    Amin Esfandiarpour, Sri Tapaswi Nori, Silvia Bonfanti, Mikko J. Alava, Antoni Wadowski, Wenyi Huo, Ł. Kurpaska, Michal Pecelerowicz, Jan S. Wróbel

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  26. Application and challenges of artificial intelligence technology in ODS steel research: A review

    Review of Materials Research · 2026-06-01

    Yuanchen Su, Conghui Zhang, Shuaiyang Liu, Wenguang Zhu

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