About this Abstract |
| Meeting |
2027 TMS Annual Meeting & Exhibition
|
| Symposium
|
Algorithms Development in Materials Science and Engineering
|
| Presentation Title |
Quantification of microstructures in polycrystalline materials from atomistic calculations |
| Author(s) |
Younggak Shin, Vichhika Moul, Keonwook Kang, Byeongchan Lee |
| On-Site Speaker (Planned) |
Byeongchan Lee |
| Abstract Scope |
Material properties are the basis of systems design but useful only when the corresponding microstructures are understood. Naturally, a study on microstructure-property relationships is two-fold. One is accurate quantification of microstructural components, most notably grain boundaries (GBs), and the other is accurate prediction of the resulting properties. Here, we focus on the former not only because it is a prerequisite to the latter but also it is still a rough task for atomistic calculations. Available defect detection algorithms are compared and contrasted including the ones we have recently developed based on graph theory [Shin et al. 2026 Nanotechnology 37 195701]. The graph-theoretical approaches successfully separate grain-boundary atoms from other bulk defects, and provide defect types and the corresponding number densities. We also present preliminary results beyond the state-of-the-art techniques, and conclude with a future outlook on realistic property prediction in the coming era of exascale computing. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Modeling and Simulation, Computational Materials Science & Engineering, Nuclear Materials |