Key facts
- Discovered Materials said the total prize pool for the five problems is $1 million.
- The five problems were defined by an advisory group of academics at universities, the company said.
- The problems include a theory of cuprate superconductivity and a method to predict silicon and silicon dioxide interfaces.
- Discovered Materials said it ran frontier AI models on the problems for several days without much headway.
- Co-founder Advaith Sridhar said the challenges are meant to serve as goalposts for measuring AI progress.
- Stanford professor Felipe Jornada, who helped develop the challenges, said the answers would shape electronics and energy storage.
Discovered Materials, a months-old San Francisco startup that uses AI models to find new substances for advanced chips, announced a $1 million prize pool on November 5, 2026 for AI models that solve five open problems in materials science.
The company said it recruited an advisory group of academics at leading global universities to spell out the five problems, since materials science has no equivalent of the Millennium Prize Problems. The problems are: a theory to explain cuprate superconductivity, the ability of certain materials to carry current with zero resistance at ultra-low temperatures; a numerical method to predict the structures of interfaces between silicon and silicon dioxide, a combination found in almost all semiconductors; a numerical method to map grain structure to thermal properties for designing heat dissipation materials; a theory to predict why light changes material behavior, particularly around superconductivity; and a numerical method to improve Density Functional Theory, a technique used to model atomic and molecular structures.
"Across materials science, there are phenomena we observe but cannot explain," Felipe Jornada, a Stanford professor who helped develop the challenges, said in a statement. He said explaining them would improve understanding of physics and "directly shape how we build electronics, store energy, and manufacture the materials of the future."
Before announcing the challenges, Discovered Materials gave frontier lab models internet access and other resources to work autonomously for days, the company said. The models spent several days on each problem without making much headway.
"It's not particularly a concern to us whether we find it, or someone else finds it, or a professor finds it, or the frontier labs find it," co-founder Advaith Sridhar said. He said the challenges are meant to serve as goalposts and that tracking efforts would show "whether the models are climbing in this domain."
Discovered Materials focuses on new materials for semiconductors and partners with chip companies on research projects while funding its own scientific work. When it announced its seed round in August, Sridhar told TechCrunch he hoped the company would generate a useful material within a year; he said those timelines have accelerated and he is more confident the company will find industrially useful materials in less than a year.