Accelerating Discovery of Ternary Chiral Materials via Large-Scale Random Crystal Structure Prediction

Chiral inorganic crystals, particularly semiconductors with Weyl points near the band edges or semimetals hosting Weyl points at the Fermi level, have attracted considerable interest; yet, they remain scarce in existing materials databases. This study presents a prediction pathway by combining universal machine-learning interatomic potentials (uMLIPs) for high-throughput structure optimization with the broad exploration capability of random structure search (RSS), enabling large-scale crystal st