| About this Abstract |
| Meeting |
2025 TMS Annual Meeting & Exhibition
|
| Symposium
|
Bridging Scale Gaps in Multiscale Materials Modeling in the Age of Artificial Intelligence
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| Presentation Title |
Study of Xe Binding in Ag-Exchange Chabazite for Radio-Nuclide Absorption |
| Author(s) |
Soham Ketan Savarkar, Preston Vargas, Richard Hennig, Juan Claudio Nino |
| On-Site Speaker (Planned) |
Soham Ketan Savarkar |
| Abstract Scope |
Silver-exchanged zeolites have been suggested as potential materials for xenon gas adsorption, to detect nuclear weapons tests by capturing radio-nuclides. Although these materials have demonstrated promising performance, the full range of xenon binding configurations had not yet been investigated. We employ density functional theory to identify key combinations of silver exchange and xenon binding, creating a representative sample of the configuration space for xenon binding in silver-exchange Chabazite. The DFT data does highlight some important characteristics, although it examines only a single material, hence to reduce computational time and high throughput screening of materials we need machine learning inter-atomic potentials. A dynamic study using molecular dynamics would aim at studying pore & channel importance along with the selectivity. Hence we use UF3 machine learning potentials to fit DFT data for these configurations and conduct MD studies using LAMMPS for dynamic study which will have key findings of other aspects. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Computational Materials Science & Engineering, Machine Learning, Modeling and Simulation |