Ryota Tomioka

Jan 16, 2025 | nature.com | Claudio Zeni |Robert Pinsler |Daniel Zügner |Andrew Fowler |Matthew Horton |Xiang Fu | +8 more

AbstractThe design of functional materials with desired properties is essential in driving technological advances in areas like energy storage, catalysis, and carbon capture1–3. Generative models provide a new paradigm for materials design by directly generating novel materials given desired property constraints, but current methods have low success rate in proposing stable crystals or can only satisfy a limited set of property constraints 4−11.

Dec 7, 2023 | microsoft.com | Andrew Fowler |Matthew Horton |Ryota Tomioka |Robert Pinsler

Generative AI has revolutionized how we create text and images. How about designing novel materials? We at Microsoft Research AI4Science are thrilled to announce MatterGen, our generative model that enables broad property-guided materials design. The central challenge in materials science is to discover materials with desired properties, e.g., high Li-ion conductivity for battery materials.