| About this Abstract |
| Meeting |
3rd World Congress on High Entropy Alloys (HEA 2023)
|
| Symposium
|
HEA 2023
|
| Presentation Title |
High-entropy Materials Design by Integrating the First-principles Calculations and Machine Learning: A Case Study in the Al-Co-Cr-Fe-Ni System |
| Author(s) |
Guangchen Liu, Songge Yang, Yu Zhong |
| On-Site Speaker (Planned) |
Guangchen Liu |
| Abstract Scope |
The first-principles calculation is widely used in high-entropy materials. However, this approach may consume many computational resources for complex systems, limiting the development of property maps for the related materials across the whole composition range. This work chooses the most prevalent Al-Co-Cr-Fe-Ni system (FCC and BCC) for our investigation. A comprehensive database of properties (e.g., phase stabilities and elastic properties) was established by combining the first-principles calculation results and machine learning: starting from unary, binary, ternary, and quaternary, then extending into quinary systems. A comparable software program was also developed by utilizing this database. Furthermore, the information/mechanism that underlies the database was thoroughly studied by screening and statistical analysis. |
| Proceedings Inclusion? |
Planned: Metallurgical and Materials Transactions |