Potential Method to Distinguish Copper Molten Marks Using Boundary and Grain Characteristics.

Park, Jinyoung; Kang, Joo-Hee; Jang, Hyo-Sun; Ko, Young Ho; Bang, Sun Bae

Park, Jinyoung; Kang, Joo-Hee; Jang, Hyo-Sun; Ko, Young Ho; Bang, Sun Bae.

Afiliación

Park J; Korea Electrical Safety Corporation Research Institute, 111, Anjeon-ro, Iseo-myeon, Wanju-gun 55365, Jeollabuk-do, Korea.
Kang JH; Korea Institute of Materials Science, 797, Changwon-daero, Seongsan-gu, Changwon-si 51508, Gyeongsangnam-do, Korea.
Jang HS; Korea Institute of Materials Science, 797, Changwon-daero, Seongsan-gu, Changwon-si 51508, Gyeongsangnam-do, Korea.
Ko YH; Jeonbuk National University, 567, Baekje-daero, Deokjin-gu, Jeonju-si 54896, Jeollabuk-do, Korea.
Bang SB; Korea Electrical Safety Corporation Research Institute, 111, Anjeon-ro, Iseo-myeon, Wanju-gun 55365, Jeollabuk-do, Korea.

Materials (Basel) ; 15(13)2022 Jun 28.

Article en En | MEDLINE | ID: mdl-35806659

Palabras clave

electron-backscatter diffraction; grain size; machine learning; molten mark; primary-arc bead; secondary-arc bead; Σ3 boundary

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Materials (Basel) Año: 2022 Tipo del documento: Article Pais de publicación: Suiza

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