YC startup puts $1M on 5 unsolved materials science problems for AI

discovered materials, a san francisco startup part of yc's spring 2026 batch, announced a $1 million challenge for ai models to solve five critical problems in materials science. the problems include: a theory to explain cuprate superconductivity, a numerical method to predict the structures of interfaces between silicon and silicon dioxide, a numerical method to map grain structure to thermal properties, a theory to predict why shining light on materials can change their behavior, and a numerical method to improve density functional theory. the startup, which focuses on developing new materials for semiconductors, partnered with academics to define these challenges and will track efforts to solve them to gauge progress in the field. this reflects a new approach to scientific inquiry, where challenges are defined first and then ai models are used to find solutions.