Customized development of promising Cu-Cr-Ni-Co-Si alloys enabled by integrated machine learning and characterization

Pan，Shaobin1; Yu，Jinxin3; Han，Jiajia1; Zhang，Yanqing1; Peng，Qinghua1; Yang，Mujin4; Chen，Youheng1; Huang，Xiang1; Shi，Rongpei3; Wang，Cuiping1; Liu，Xingjun1,2,3

2023-01-15

10.1016/j.actamat.2022.118484

ACTA MATERIALIA   影响因子和分区

1359-6454

1873-2453

Two types of alloys, Cu-Ni-Co-Si and Cu-Cr-Zr, are considered candidate materials for next-generation integrated circuits due to their superior comprehensive performance. However, the rapid development of these two types of alloys remains difficult using conventional simulation techniques. Machine learning offers a new tool for accelerating the design and discovery of new materials with required property profiles. Herein, composition-process-property database of the six-element Cu-Cr-Ni-Co-Si-Zr alloys were established, and a novel strategy of customized performance design for different application environments was proposed. Then, four alloys with different performance characteristics were rapidly screened from 850,500 candidates using a multi-property segmented screening method, and the predicted results agreed well with the experimental results. Importantly, the developed Cu-1.0Cr-1.0Ni-2.5Co-0.8Si alloy was used as a bridge alloy to link the Cu-Ni-Co-Si and Cu-Cr-Zr alloys together, filling the gap in the mid-segment performance (220–240 HV, 45–65% IACS) of Cu-based alloys. Interestingly, the studied alloy was a dual-phase precipitation-strengthened alloy. It was found that the small spherical (Co, Ni)Si phase was the main influence on the micro-hardness and strength, while the large rod-shaped CrCoSi phase was the main reinforcing phase that affected ductility and electrical conductivity. The design method proposed in this paper accelerates the development of the Cu-Cr-Ni-Co-Si alloy system, which has great potential for application in integrated circuits and heat sinks.

Alloy design Cu-based alloy Microstructure Precipitate Property

SCI

英语

其他

Key-area Research and Development Program of Guangdong Province[2019B010943001] ; Major-Special Science and Technology Project in Shandong Province[2019JZZY010303] ; National Post-doctoral Program for Innovative Talents[BX20200103]

Materials Science ; Metallurgy & Metallurgical Engineering

Materials Science, Multidisciplinary ; Metallurgy & Metallurgical Engineering

WOS:000899525600001

PERGAMON-ELSEVIER SCIENCE LTD

MATERIALS SCIENCE

2-s2.0-85142535123

Scopus

1.College of Materials and Key Laboratory of High Performance Metals and Materials,Xiamen University,Xiamen,361005,China
2.State Key Laboratory of Advanced Welding and Joining,Harbin Institute of Technology,Shenzhen,518055,China
3.Institute of Materials Genome and Big Data,Harbin Institute of Technology,Shenzhen,518055,China
4.Department of Mechanical and Energy Engineering,Southern University of Science and Technology,Shenzhen,518055,China

Pan，Shaobin,Yu，Jinxin,Han，Jiajia,et al. Customized development of promising Cu-Cr-Ni-Co-Si alloys enabled by integrated machine learning and characterization[J]. ACTA MATERIALIA,2023,243.

Pan，Shaobin.,Yu，Jinxin.,Han，Jiajia.,Zhang，Yanqing.,Peng，Qinghua.,...&Liu，Xingjun.(2023).Customized development of promising Cu-Cr-Ni-Co-Si alloys enabled by integrated machine learning and characterization.ACTA MATERIALIA,243.

Pan，Shaobin,et al."Customized development of promising Cu-Cr-Ni-Co-Si alloys enabled by integrated machine learning and characterization".ACTA MATERIALIA 243(2023).