AQVolt26 is a new high-temperature halide dataset that improves universal ML interatomic potentials for distorted configurations while showing that near-equilibrium relaxation data is not universally helpful.
Wood, Tuan Anh Pham, and Shyue Ping Ong
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Pretrained UMA model reproduces chemisorbed S and O coverage under 15 eV O+ and O2+ bombardment on WS2 without fine-tuning; fine-tuning lowers energy MAE to 4.5e-3 eV/atom and force MAE to 0.076 eV/Å.
citing papers explorer
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AQVolt26: High-Temperature r$^2$SCAN Halide Dataset for Universal ML Potentials and Solid-State Batteries
AQVolt26 is a new high-temperature halide dataset that improves universal ML interatomic potentials for distorted configurations while showing that near-equilibrium relaxation data is not universally helpful.
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Fine-Tuning a Universal Machine-Learned Interatomic Potential for Oxygen Plasma Interactions with WS$_2$
Pretrained UMA model reproduces chemisorbed S and O coverage under 15 eV O+ and O2+ bombardment on WS2 without fine-tuning; fine-tuning lowers energy MAE to 4.5e-3 eV/atom and force MAE to 0.076 eV/Å.