An iterative scheme using foundation models and SSCHA enables efficient crystal structure prediction with anharmonic effects, shown to match DFT benchmarks on the H3S system from 50 to 200 GPa.
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HPCSD compiles 77,346 pressure-resolved crystal structures for 89 elements with consistent DFT re-optimization and analysis showing ubiquitous pressure-induced polymorphism with family-dependent trends.
An ensemble of XGBoost regression models trained on ~2000 hydrides screens ternary A-B-H compositions for high-Tc superconductivity at 100-300 GPa and flags promising systems such as Ca-Ti-H, Li-K-H, and Na-Mg-H.
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Iterative learning scheme for crystal structure prediction with anharmonic lattice dynamics
An iterative scheme using foundation models and SSCHA enables efficient crystal structure prediction with anharmonic effects, shown to match DFT benchmarks on the H3S system from 50 to 200 GPa.
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High-Pressure Crystal Structure Database
HPCSD compiles 77,346 pressure-resolved crystal structures for 89 elements with consistent DFT re-optimization and analysis showing ubiquitous pressure-induced polymorphism with family-dependent trends.
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Composition-Based Machine Learning for Screening Superconducting Ternary Hydrides from a Curated Dataset
An ensemble of XGBoost regression models trained on ~2000 hydrides screens ternary A-B-H compositions for high-Tc superconductivity at 100-300 GPa and flags promising systems such as Ca-Ti-H, Li-K-H, and Na-Mg-H.