| About this Abstract |
| Meeting |
2025 TMS Annual Meeting & Exhibition
|
| Symposium
|
Advances in Bcc-Superalloys
|
| Presentation Title |
Atomistic simulation of dislocation behavior in a model BCC-B2 alloy using machine learning interatomic potentials |
| Author(s) |
Junxin Wang, Maryam Ghazisaeidi |
| On-Site Speaker (Planned) |
Junxin Wang |
| Abstract Scope |
Refractory multicomponent alloys with a BCC/B2 microstructure show promise as alternatives to the current state-of-the-art Ni-based superalloys for high-temperature applications. We utilize our recently developed Multi-Cell Monte Carlo method combined with first principles calculations to identify stable B2 structures among refractory metals. One promising new combination is the Ta-Re system. We develop machine learning interatomic potentials trained with first principles data, to perform large-scale atomistic simulations of deformation mechanisms in TaRe. Specifically, we examine the dislocation motion and slip transfer between the BCC and B2 phases in this binary alloy. The results provide insight into the mechanical behavior of refractory alloys with a similar microstructure. |
| Proceedings Inclusion? |
Planned: |