Machine learning-assisted composition design of W-free Co-based superalloys with high γ′-solvus temperature and low density

Machine learning-assisted composition design of W-free Co-based superalloys with high γ′-solvus temperature and low density

Developing materials with multiple desired characteristics is a tremendous challenge, particularly in an elaborate material system. Herein, a machine learning assisted material design strategy was applied to simultaneously optimize dual target attributes by considering γ′ solvus temperature and allo...

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Bibliographic Details
Main Authors: Linlin Sun, Bin Cao, Qingshuang Ma, Qiuzhi Gao, Jiahao Luo, Minglong Gong, Jing Bai, Huijun Li
Format: Article
Language:English
Published: Elsevier 2024-03-01
Series:Journal of Materials Research and Technology
Subjects:
W-free Co-based superalloys
Machine learning
Dual-target optimization
γ′-solvus temperature
Alloy density
Online Access:http://www.sciencedirect.com/science/article/pii/S2238785424000401

Internet

http://www.sciencedirect.com/science/article/pii/S2238785424000401

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