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IFAI

MatterGen

Product2 stories

  1. ResearchReach 32

    XtalPaint borrows image inpainting to find missing crystal atoms

    Researchers at Switzerland's Paul Scherrer Institute just built XtalPaint, an open-source model that reconstructs missing atoms in crystal lattices with a 97% success rate. Adapted from Microsoft's MatterGen, it treats crystal gaps like erased parts of an image, applying diffusion noise only to unknown spots while using known atoms as anchors. Why it matters: X-rays often miss light elements like hydrogen, locking thousands of promising compounds out of computer simulations; this tool could unlock them for battery and clean-energy research.

  2. ResearchReach 36

    Microsoft's AI can now generate entirely new physical materials

    Microsoft Research just published and open-sourced MatterGen, a generative diffusion model that designs novel physical materials directly from property prompts instead of screening databases. Working with SIAT researchers, the team successfully synthesized a completely new material (TaCr2O6) in the lab with under 20% error against specifications. Why it matters: It shifts material discovery from brute-force search to generative design for batteries and solar cells.