Discovered Materials, a San Francisco startup from Y Combinator‘s spring 2026 batch, has put $1 million behind five open materials science problems it wants AI models to solve. Frontier AI models have already solved a series of outstanding math problems and made progress in life sciences, but they have not yet plumbed the complex physics of advanced materials. Materials science problems are also harder to specify than math because they do not reduce to a clear yes or no, and the field lacks an equivalent of the Millennium Prize Problems. The company, which uses AI to find new substances for building advanced chips, recruited an advisory group of academics from leading global universities to define five challenges: a theory explaining cuprate superconductivity; a numerical method for predicting silicon-silicon dioxide interface structures; a numerical method for mapping grain structure to thermal properties so heat-dissipation materials can be better designed; a theory predicting why light changes material behavior, especially around superconductivity; and a numerical method improving Density Functional Theory.

Before announcing the challenge, Discovered Materials let frontier lab models work autonomously for days on each problem, giving the AI agents internet access and other resources. The models spent several days on each problem without making much headway. Stanford professor Felipe Jornada, who helped develop the challenges, said in a statement that materials science has phenomena we observe but cannot explain, and solving them would improve our understanding of physics while directly shaping how we build electronics, store energy, and manufacture materials. Sridhar said it does not matter whether Discovered Materials, a professor, or a frontier lab finds the solutions; the goal is to create measurable goalposts for whether AI models are actually progressing in this domain.

Sridhar also described the challenge as a new way of thinking about science: define the verification and the challenges first, then let someone else supply the explanatory ideas. He said knowing the right questions is difficult in this domain, and the academic advisors helped shape those questions. Discovered Materials‘ main focus is semiconductor materials; the startup partners with chip companies on research projects and funds its own scientific work. When its seed round was announced in August, Sridhar hoped the company would generate a useful material within a year. He now says those timelines have accelerated, and he is more confident that industrially useful materials will be found in less than a year.