Kernels from pretrained MLIP latent spaces outperform standard acquisition methods in active learning for reactive chemistry, reducing required labels by 38% for energy error and 28% for force error.
Himanen , author M
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Tensile strain boosts Li+ diffusivity in Li3YCl6 while compressive strain reduces it, but the critical temperature separating 1D hopping from 3D cooperative diffusion remains unchanged.
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Pretrained Model Representations as Acquisition Signals for Active Learning of MLIPs
Kernels from pretrained MLIP latent spaces outperform standard acquisition methods in active learning for reactive chemistry, reducing required labels by 38% for energy error and 28% for force error.
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Strain-Dependent Ionic Transport in Li3YCl6 Solid Electrolytes
Tensile strain boosts Li+ diffusivity in Li3YCl6 while compressive strain reduces it, but the critical temperature separating 1D hopping from 3D cooperative diffusion remains unchanged.