About this Abstract |
| Meeting |
2027 TMS Annual Meeting & Exhibition
|
| Symposium
|
Radiation Effects in Solid-State Materials: An SMD Symposium Honoring William J Weber
|
| Presentation Title |
Machine-Learning Molecular Dynamics Simulations of Radiation Damage at Metallic Interfaces |
| Author(s) |
Takuji Oda |
| On-Site Speaker (Planned) |
Takuji Oda |
| Abstract Scope |
Components in nuclear energy systems often combine dissimilar materials to satisfy the stringent requirements for operation under harsh environments, including neutron irradiation. Consequently, engineered material interfaces play a key role in their performance and reliability. Despite their importance, radiation damage processes at material interfaces remain poorly understood because of their structural and chemical complexity. In this study, we developed a machine-learning interatomic potential for a highly incoherent bcc-W/fcc-Cu interface, representative of plasma-facing components in fusion reactors, and performed molecular dynamics recoil simulations. The simulations reveal significant interfacial mixing, defect formation, and interfacial stress relaxation. Irradiation-induced interfacial defects also significantly alter hydrogen transport and retention compared with the non-irradiated interface. These findings advance the atomistic understanding of radiation damage and hydrogen behavior at metallic interfaces, suggesting that interface engineering may help mitigate the adverse effects of radiation damage and hydrogen. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Computational Materials Science & Engineering, Nuclear Materials, Modeling and Simulation |