| About this Abstract |
| Meeting |
2025 TMS Annual Meeting & Exhibition
|
| Symposium
|
Advances in Multi-Principal Element Alloys IV: Mechanical Behavior
|
| Presentation Title |
Predicting and Understanding Peierls Stress Spectrum in Multi-Principal Element Alloys |
| Author(s) |
Kourosh Jafari Ghalejooghi, Penghui Cao |
| On-Site Speaker (Planned) |
Kourosh Jafari Ghalejooghi |
| Abstract Scope |
Peierls stress, the intrinsic lattice resistance to dislocation, is a fundamental material property as it reflects the near-ideal strength of the material. For a pure crystalline metal, the magnitude of the Peierls stress associated with screw dislocation motion, is constant. In multi-principal element alloys (MPEAs), however, the magnitude of Peierls stress can vary significantly due to the vast compositional space and local chemical fluctuations. In this study, we propose a neural network model to efficiently predict Peierls stresses over the entire ternary space of Nb-Mo-Ta alloys by accurately capturing the chemistry and structure of dislocations. The physical implications of Peierls stress and Peierls barrier in pure element and MPEAs will be discussed. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
High-Entropy Alloys, Machine Learning, Mechanical Properties |