Active-learned potentials reveal the interplay between the structure and dynamics in thorium molten salts

Short summary

An active-learning framework created a machine-learned potential (MLIP) that enabled large-scale simulations of thorium molten salts, revealing how thorium clusters fundamentally alter transport properties.

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