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AI Breakthrough Deciphers Nanocrystal Structures, Solving Century-Old Crystallography Challenge

Columbia Engineering's PXRDnet uses generative AI to reconstruct atomic structures from degraded diffraction patterns, unlocking advancements in materials science, medicine, and archaeology.

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Overview

  • PXRDnet, a new AI algorithm developed by Columbia Engineering, reconstructs atomic structures of nanocrystals from degraded X-ray diffraction patterns.
  • The method combines diffusion generative modeling, trained on 40,000 known atomic structures, with Rietveld refinement to polish predictions for accuracy.
  • Published in *Nature Materials* on April 28, 2025, the breakthrough overcomes a century-old limitation requiring large, pure crystals for structural analysis.
  • The tool can resolve features as small as 10 angstroms, enabling progress in next-generation batteries, drug discovery, and archaeological material identification.
  • The project was led by Gabe Guo, Simon Billinge, and Hod Lipson, marking a significant leap for AI in solving long-standing scientific challenges.