Materials informatics - Recommender system for discovery of new oxides and nitrides

Prof. Tanaka and his team have adopted methods to establish recommender systems useful for efficient discovery of currently unknown chemically relevant compositions (CRCs) of inorganic ionic compounds from vast candidates. Using information of compounds registered in inorganic crystal structure database (ICSD) and tensor-based recommender system, they systematically calculated recommendation scores for chemical compositions of up to 23 billion five-element ionic systems. The high success rate, despite not using any prior knowledge or first principle theoretical results, proves the powerfulness of current recommendation systems. Synthesis experiments were made at the chemical compositions with high recommendation scores. Novel oxides and nitrides were efficiently discovered accordingly. Their recommender system was also used to predict successful processing conditions for new compounds based on our parallel experiment-dataset.