About this Abstract |
Meeting |
2022 TMS Annual Meeting & Exhibition
|
Symposium
|
Phase Stability, Phase Transformations, and Reactive Phase Formation in Electronic Materials XXI
|
Presentation Title |
Data-driven Rational Design of Conductive Copper-based Alloys with High Performance |
Author(s) |
Jianxin Xie, Huadong Fu |
On-Site Speaker (Planned) |
Jianxin Xie |
Abstract Scope |
To overcome the challenges of low efficiency and high cost of traditional trial and error alloy design method, this study proposes a data-driven rational alloy design strategy and three rational alloy design methods are developed taking high strength conductive copper-based alloys as an example. One is the rapid and accurate design method of the complex alloy composition oriented to required properties, which breaks through the problem of alloy composition design according to given properties with the realization of meet-demand alloy designs. The second method is put forward to realize the optimized alloy design with screening key features affecting alloy properties first, and then designing alloy composition according to the influence mechanism and degree of elements on properties. The third method is machine learning-assisted adaptive deformation-aging process design to solve the problem of large-amount and long-time experiments, which realizes the rapid design of alloy preparation processes. |
Proceedings Inclusion? |
Planned: |
Keywords |
Machine Learning, Copper / Nickel / Cobalt, Electronic Materials |