| Autor: |
Jicheng Guo, Logan Ward, Yadu Babuji, Nathaniel Hoyt, Mark Williamson, Ian Foster, Nicholas Jackson, Chris Benmore, ganesh sivaraman |
| Rok vydání: |
2022 |
| Popis: |
Unraveling the liquid structure of multi-component molten salts is challenging due to the difficulty in conducting and interpreting high temperature diffraction experiments. Motivated by this challenge, we developed composition-transferable Gaussian Approximation Potentials (GAP) for molten LiCl-KCl. A DFT-SCAN accurate GAP is active learned from only ~1100 training configurations drawn from 10 unique mixture compositions enriched with metadynamics. The GAP-computed structures show strong agreement across HEXRD experiments, including for a eutectic not explicitly included in model training, thereby opening the possibility for composition discovery. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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