Machine learning accelerates quantum mechanics predictions of molecular crystals

Quantum mechanics (QM) approaches (DFT, MP2, CCSD(T), etc.) play an important role in calculating molecules and crystals with a high accuracy and acceptable efficiency. In recent years, with the development of artificial intelligence technology, machine learning (ML) has played an increasingly essential role in accelerating the QM calculations and predictions of molecular crystals, as well as the discovery of novel materials. This review...