About this Abstract |
| Meeting |
MS&T25: Materials Science & Technology
|
| Symposium
|
Grain Boundaries, Interfaces, and Surfaces: Fundamental Structure-Property-Performance Relationships
|
| Presentation Title |
Atomic and electronic structure of impurity-segregated grain boundaries in α-Al2O3 |
| Author(s) |
Tatsuya Yokoi, Yu Ogura, Katsuyuki Matsunaga |
| On-Site Speaker (Planned) |
Tatsuya Yokoi |
| Abstract Scope |
A neural-network potential (NNP) trained on density-functional-theory (DFT) data was constructed to determine atomic structures of impurity-segregated grain boundaries (GBs) in α-Al2O3. It was predicted that impurity atoms preferentially occupy specific Al sites at GBs, corresponding to the lowest GB energy. The NNP accurately predicted the relationship between atomic structure and GB energy at the DFT level. In addition, the predicted structure was consistent with previous experimental images obtained from scanning transmission electron microscopy. These results suggest that the NNP enables accurate prediction of impurity-segregated GB structures, paving the way for uncovering the fundamental mechanisms of impurity segregation to GBs in α-Al2O3. Furthermore, the obtained atomic structures were used to understand their electronic structures via DFT calculations. |