Startup offers $1 million for five unsolved materials science problems

Discovered Materials, a San Francisco startup from Y Combinator’s spring 2026 batch, has launched a $1 million challenge for solutions to five open problems in materials science. The company, which uses AI to search for substances suitable for advanced chips, is offering $200,000 for each solution.

The questions include a theory explaining cuprate superconductivity; a numerical way to predict silicon–silicon dioxide interface structures; and a method linking grain structure with thermal properties. The remaining challenges concern how light changes material behavior, particularly near superconductivity, and improvements to Density Functional Theory, used to model atoms and molecules.

The problems were defined with help from academics at universities including Stanford. Before announcing them, Discovered Materials gave frontier AI models internet access and other resources and ran them for several days on each task, without significant progress. Co-founder Advaith Sridhar said the challenges are intended to provide benchmarks for measuring AI advances in materials science, regardless of who eventually solves them.

The startup works with chip companies and conducts its own research. Sridhar said it now expects to find industrially useful materials in less than a year.