About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Chemistry and Physics of Interfaces
|
| Presentation Title |
Grain boundary segregation spectra for HCP metals from augmented multiscale machine learning potentials |
| Author(s) |
Nutth Tuchinda, Changle Li, Christopher Schuh |
| On-Site Speaker (Planned) |
Nutth Tuchinda |
| Abstract Scope |
Hexagonal closed-packed metals are the basis of many lightweight structural alloys, medical implants and nuclear materials. Here we construct a framework to evaluate grain boundary segregation spectra for more than 70 substitutional solute elements in Mg, Ti and Zr binary alloys. To achieve this set of computations, we adapt the “augmented potential method”, which combines two potentials together for maximum efficiency and accuracy, to the case of HCP structures. The resulting database allows bulk thermodynamic modeling of GB stabilization at an accuracy beyond what classical potentials offer and demonstrates potential directions beyond dilute GB spectra such as dislocation, stacking fault and solute-solute interactions at defects in polycrystalline ensembles. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Computational Materials Science & Engineering, Thin Films and Interfaces, Modeling and Simulation |