Researchers report an integrated AI–DFT framework that couples machine learning with density functional theory to accelerate materials discovery, moving from trial-and-error to intelligent design. The approach enables closed-loop prediction, verification, and learning, improving computational efficiency across semiconductors, perovskites, and 2D materials.
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