Applications of machine learning in perovskite materials

Machine learning (ML) offers the opportunities to discover certain unique properties for typical material. Taking perovskite materials as an example, this review summarizes the applications of ML in predicting their bandgap, stability, electronic transport, catalytic, ferroelectric, photovoltaic, light emitting, and sensing properties. This proves that ML can accelerate the screening and discovery of novel materials with potential properties for certain applications.

Automated summary

This review presents the applications of machine learning in predicting the properties of perovskite materials, including bandgap, stability, electronic transport, etc. Machine learning proves to be valuable in accelerating the screening and discovery of new materials, offering potential for various applications.