| About this Abstract |
| Meeting |
2023 TMS Annual Meeting & Exhibition
|
| Symposium
|
Advances in Multi-Principal Element Alloys II
|
| Presentation Title |
J-38: High-throughput Calculation of the Alloying Effects on the Thermodynamic Properties of Al2Cu10Fe20MnxNiyCrz High Entropy Alloys |
| Author(s) |
Md Abdullah Al Hasan, Xuesong Fan, Seungha Shin, Peter K. Liaw |
| On-Site Speaker (Planned) |
Md Abdullah Al Hasan |
| Abstract Scope |
High-entropy alloys (HEAs) offer huge compositional and microstructural spaces to explore for desirable physical properties while facing challenges due to high computational costs. Thermodynamic properties, specifically lower thermal expansion coefficients (CTEs) in HEAs are desirable, however, scarce in literature. In this research, we will implement high-throughput calculations by combining first-principles calculations and state-of-the-art machine learning techniques to examine the alloying effects on the HEAs to predict desirable thermodynamic properties. From both of our simulations and experiments, it was observed that increasing Cr or reducing Mn content in Al2Cu10Fe20MnxNiyCrz HEAs resulted in lowering CTEs at room temperature. Therefore, multiple alloying contents will be considered, and our approach will work as a closed-loop, integrating machine learning with these simulations and experiments to find lower CTEs over a wide temperature range of 300-1200 K. This work will enable fast and automated discovery of HEAs with optimal thermodynamic properties as well as high-temperature applications. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
High-Entropy Alloys, Modeling and Simulation, Machine Learning |