Predicting the grain boundary segregation energy of solute atoms in aluminum by first-principles calculation and machine learning-Reference-Cited by-同舟云学术

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Predicting the grain boundary segregation energy of solute atoms in aluminum by first-principles calculation and machine learning

Published:2024-12 Issue: Volume:41 Page:110326
ISSN:2352-4928
Container-title:Materials Today Communications
language:en
Short-container-title:Materials Today Communications

Author:

Zhang Xuan,Zhang Liang,Wan Yuxuan,Shibuta Yasushi,Huang Xiaoxu

Funder

Ministry of Science and Technology of the People's Republic of China

National Natural Science Foundation of China

Chongqing University State Key Laboratory of Mechanical Transmission for Advanced Equipment

Publisher

Elsevier BV

Reference81 articles.

1. Mechanical properties of nanocrystalline materials;Meyers;Prog. Mater. Sci.,2006

2. Toward a quantitative understanding of mechanical behavior of nanocrystalline metals;Dao;Acta Mater.,2007

3. Mechanical behavior of nanocrystalline metals and alloys11The Golden Jubilee Issue—selected topics in materials science and engineering: past, present and future, edited by S. Suresh;Kumar;Acta Mater.,2003

4. Toward a quantitative understanding of mechanical behavior of nanocrystalline metals;Dao;Acta Mater.,2007

5. On the room-temperature grain growth in nanocrystalline copper;Gertsman;Scr. Metall. Et. Mater.,1994

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