| About this Abstract |
| Meeting |
2023 TMS Annual Meeting & Exhibition
|
| Symposium
|
Magnesium Technology 2023
|
| Presentation Title |
E-22: Investigation of Transformation-mediated Nanotwin Nucleation Mechanisms in Magnesium Using Deep Neural Network Interatomic Potentials |
| Author(s) |
Mehrab Lotfpour, Iyyappa Rajan, Amir Hassan Zahiri, Jamie Ombogo, Lei Cao |
| On-Site Speaker (Planned) |
Mehrab Lotfpour |
| Abstract Scope |
Recently we reported the discovery of a rigorous nucleation mechanism for {101 ̅2} twins in hexagonal close-packed (hcp) magnesium through reversible hcp-tetragonal-hcp martensitic phase transformations. The evanescent nature of the intermediate tetragonal phase hinders its direct observation via experiments, so molecular dynamics simulation served as a unique tool in these studies. However, conventional interatomic potentials suffer notable inaccuracies, so we have developed a high-accuracy deep neural network interatomic potential using ab initio molecular dynamics data. The results were compared with those from molecular dynamics simulations using conventional embedded atom method potentials. Specifically, we confirmed that extensive twinning processes follow the transformation-mediated twinning mechanism and follow strict orientation relations between the parent hcp phase, intermediate phase, and twin hcp phases. This work will be important for a better understanding of the twinning mechanism and thus the development of novel strategies for enhancing the ductility of magnesium alloys. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Magnesium, Computational Materials Science & Engineering, Modeling and Simulation |