Accelerated composition-process-properties design of precipitation-strengthened copper alloys using machine learning based on Bayesian optimization
Designing new alloys with high performance is challenging due to the large search space for composition and process parameters. We propose an alloy design strategy based on machine learning algorithms for navigating the enormous search space. Specifically, feature engineering was applied to screen t...
Saved in:
| Main Authors: | Longjian Li, Jinchuan Jie, Xiaoyu Guo, Gaojie Liu, Huijun Kang, Zongning Chen, Enyu Guo, Tongmin Wang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-02-01
|
| Series: | Materials Research Letters |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/21663831.2024.2424933 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Effects of Heat Treatment and Deformation on Microstructure and Properties of Cu–Ni–Si Alloy/AA8030 Alloy Composite Wires
by: Shuke Tian, et al.
Published: (2024-11-01) -
Pre-aging combined with multi-stage rolling processing: Enhancing precipitate-dislocation interaction for strengthening of Cu-Cr-Zr-Ni-Si alloy
by: Xiangyi Jiao, et al.
Published: (2025-08-01) -
Study of the stress relaxation resistance and microstructural evolution of a Cu–Ni–Si alloy strip
by: Yanmin Zhang, et al.
Published: (2024-11-01) -
The Microstructures and Properties of Cu-Ni-Co-Si Alloys: A Critical Review
by: Fang Li, et al.
Published: (2025-05-01) -
Influence of different rolling passes and deformation amounts on the microstructure evolution and strengthening mechanism of Cu–Ni–Si alloy
by: Yunqi Shan, et al.
Published: (2024-11-01)