Fig. 3. (a) Evolutionary algorithm optimizes materials (or atomic configurations) by using three operations derived from biological evolution. Selection (black arrow) chooses stable materials after evaluating functionality. Mutation (orange arrow) introduces variation in original materials. Crossover (green arrow) mixes two different materials. Along with these operations, materials are optimized to have target functionality. To avoid costly first-principles evaluation of functionality, ML could greatly reduce the computational burden. (b) ML can be used to search through composition space to discriminate positive (i.e. promising, green circle) vs. negative (i.e. unpromising, red cross) cases.