GSS unifies diffusion models and random structure search as limiting regimes of one sampling process to recover diverse metastable structures at over tenfold lower cost than RSS, including for compositions outside the training data.
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MatterSim delivers a single deep learning force field that simulates inorganic materials across elements, 0-5000 K, and up to 1000 GPa with near first-principles accuracy for lattice dynamics, mechanics, and Gibbs free energies.
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Generative structure search for efficient and diverse discovery of molecular and crystal structures
GSS unifies diffusion models and random structure search as limiting regimes of one sampling process to recover diverse metastable structures at over tenfold lower cost than RSS, including for compositions outside the training data.
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MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
MatterSim delivers a single deep learning force field that simulates inorganic materials across elements, 0-5000 K, and up to 1000 GPa with near first-principles accuracy for lattice dynamics, mechanics, and Gibbs free energies.