| About this Abstract |
| Meeting |
2025 TMS Annual Meeting & Exhibition
|
| Symposium
|
Chemistry and Physics of Interfaces
|
| Presentation Title |
Molecular Dynamics and Machine Learning Investigation of Segregation Effects on the Mechanical Behavior of Σ5 Cu-Ag Grain Boundaries |
| Author(s) |
Shimanta Das, Chongze Hu |
| On-Site Speaker (Planned) |
Shimanta Das |
| Abstract Scope |
The segregation of solutes or impurities at grain boundaries (GBs) is a crucial interfacial phenomenon that significantly influence a wide range of materials properties in structural alloys. Using Cu-Ag as a model system, we performed molecular dynamic (MD) and hybrid Monte Carlo/MD (MC/MD) simulations to examine the segregation behavior of Ag at four distinct types of Cu Σ5 GB structures. Our MD simulations reveal that the mixed-type (tilt + twist) GB has the lowest value of GB excess of Ag, which can be ascribed to the minimal GB free volume compared to the other three types. Subsequent MD tensile tests suggested that the mixed-type GB exhibits the highest ultimate tensile strength and GB toughness. The superior performance of this GB can be attributed to the lowest tendency for solute segregation. These findings demonstrate the critical roles of GB segregation in controlling the mechanical properties of structural alloys. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Computational Materials Science & Engineering, Mechanical Properties, Modeling and Simulation |