About this Abstract |
Meeting |
2023 TMS Annual Meeting & Exhibition
|
Symposium
|
Advances in Magnetic Materials
|
Presentation Title |
High Throughput Evaluation of Magnetic Alloys for Energy Applications |
Author(s) |
Li Ping Tan, Shakti Prasad Padhy, Vijaykumar B. Varma, Zviad Tsakadze, Varun Chaudhary, Raju V. Ramanujan |
On-Site Speaker (Planned) |
Li Ping Tan |
Abstract Scope |
The emerging use of artificial intelligence makes accelerated methodologies a linchpin for modern materials development.
A device was developed in-lab and high throughput (HT) chemical flow synthesis was carried out. Fe-Co-Ni alloy libraries were rapidly prepared by tuning the flow rates of the precursors. These synthesized alloy powders were compacted into compositionally graded cylindrical samples via spark plasma sintering and characterized using HT methodologies. Multiple properties were measured.
Specific novel attractive compositions were identified: Fe36.5Co55Ni8.5 exhibited a high Ms of 191 emu/g and Hc of 23.9 Oe while Fe26.9Co22.3Ni50.8 had a Ms of 131 emu/g and relatively low Hc of 14.5 Oe. The electrical resistivity of both samples was ~20 µΩ.cm.
These results could be utilized in machine learning approaches to discover novel material compositions for energy applications.
This work is supported by the AME Programmatic Fund by the Agency for Science, Technology and Research, Singapore under Grant No. A1898b0043. |
Proceedings Inclusion? |
Planned: |
Keywords |
Magnetic Materials, Machine Learning, |