A joint diffusion framework for crystal structures and local electronic descriptors improves inverse materials design success rates and structural quality over structure-only models under band-gap and formation-energy conditioning.
Inverse molecular design using machine learning: Generative models for matter engineer- ing.Science, 361(6400):360–365
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Inverse Materials Design via Joint Generation of Crystal Structures and Local Electronic Descriptors
A joint diffusion framework for crystal structures and local electronic descriptors improves inverse materials design success rates and structural quality over structure-only models under band-gap and formation-energy conditioning.