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Machine learning enhanced metal 3D printing:high throughput optimization and material transfer extensibility

Yuanjie Zhang Cheng Lin Yuan Tian Jianbao Gao Bo Song Hao Zhang Min Wang Kechen Song Binghui Deng Dezhen Xue Yonggang Yao Yusheng Shi Kun Kelvin Fu

International Journal of Extreme Manufacturing2025，Vol.7Issue(4)：P.297-310,14.

International Journal of Extreme Manufacturing2025，Vol.7Issue(4)：P.297-310,14.DOI:10.1088/2631-7990/adbb96

Machine learning enhanced metal 3D printing:high throughput optimization and material transfer extensibility

Yuanjie Zhang ¹Cheng Lin ¹Yuan Tian ²Jianbao Gao ¹Bo Song ¹Hao Zhang ¹Min Wang ¹Kechen Song ³Binghui Deng ¹Dezhen Xue ²Yonggang Yao ¹Yusheng Shi ¹Kun Kelvin Fu⁴

作者信息

1. State Key Laboratory of Materials Processing and Die&Mould Technology,School of Materials Science and Engineering,Huazhong University of Science and Technology,Wuhan 430074,People’s Republic of China
2. State Key Laboratory for Mechanical Behavior of Materials,Xi’an Jiaotong University,Xi’an 710049,People’s Republic of China
3. Revochemix Technologies Company Limited,Hangzhou 310000,People’s Republic of China
4. Department of Mechanical Engineering,University of Delaware,Newark,DE 19716,United States of America
折叠

摘要

关键词

high throughput 3D printing/machine learning/316L stainless steel/rapid optimization/corrosion resistance

分类

医药卫生

引用本文复制引用

Yuanjie Zhang,Cheng Lin,Yuan Tian,Jianbao Gao,Bo Song,Hao Zhang,Min Wang,Kechen Song,Binghui Deng,Dezhen Xue,Yonggang Yao,Yusheng Shi,Kun Kelvin Fu..Machine learning enhanced metal 3D printing:high throughput optimization and material transfer extensibility[J].International Journal of Extreme Manufacturing,2025,7(4):P.297-310,14.

基金项目

sponsored by the National Key Research and Development Program of China(No.2023YFB4604800,2021YFA1202300) （No.2023YFB4604800,2021YFA1202300）

the Natural and Science Foundation of China(Grant Nos.52201041,52275331,52205358) （Grant Nos.52201041,52275331,52205358）

the Key Research and Development Program of Hubei Province(Nos.2024BCB091,2022CFA031) （Nos.2024BCB091,2022CFA031）

the Hong Kong Scholars Program(No.XJ2022014)。（No.XJ2022014）

International Journal of Extreme Manufacturing

ISSN：2631-8644

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