# Researchers Use AI to Accelerate Superconductor Discovery > Source: > Published: 2026-07-07 06:39:51+00:00 An **Aalto-led SuperC** team reported on June 29, 2026 that machine-learning-guided screening helped identify and experimentally confirm two kagome superconductors, **YRu3B2** and **LuRu3B2**. The Physical Review Research paper reports superconducting critical temperatures of **0.81 K and 0.95 K**, so this is not a room-temperature result; the practitioner value is the workflow. The team used ML to narrow a large chemical search space, then applied first-principles calculations before Rice University collaborators synthesized and tested the candidates. For data-science and materials teams, the useful lesson is that physics-informed features, high-precision candidate ranking, and experiment-ready validation loops can matter more than broad benchmark accuracy when ML systems must produce lab-verifiable discoveries.