A machine-learning-based alloy design platform that enables both forward and inverse predictions for thermo-mechanically controlled processed (TMCP) steel alloys.

Lee, Jin-Woong; Park, Chaewon; Do Lee, Byung; Park, Joonseo; Goo, Nam Hoon; Sohn, Kee-Sun

Lee, Jin-Woong; Park, Chaewon; Do Lee, Byung; Park, Joonseo; Goo, Nam Hoon; Sohn, Kee-Sun.

Afiliação

Lee JW; Nanotechnology & Advanced Materials Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul, 143-747, South Korea.
Park C; Nanotechnology & Advanced Materials Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul, 143-747, South Korea.
Do Lee B; Nanotechnology & Advanced Materials Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul, 143-747, South Korea.
Park J; Nanotechnology & Advanced Materials Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul, 143-747, South Korea.
Goo NH; Advanced Research Team, Hyundai Steel DangJin Works, DangJin, Chungnam, 31719, South Korea.
Sohn KS; Nanotechnology & Advanced Materials Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul, 143-747, South Korea. kssohn@sejong.ac.kr.

Sci Rep ; 11(1): 11012, 2021 05 26.

Article em En | MEDLINE | ID: mdl-34040040

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Rep Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Coréia do Sul

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