Accelerated Discovery of Targeted Environmentally Friendly A(II)B(I)X 3 -Type Three-Dimensional Hybrid Organic-Inorganic Perovskites for Potential Light Harvesting via Machine Learning.

The engineered hybrid organic-inorganic perovskites (HOIPs) with outstanding multifunctionalities have realized overarching targeted-driven applications and thus aroused intense research interest. The emergence of three-dimensional (3D) A(II)B(I)X 3 -type HOIPs in 2018 brought a breakthrough to extend the 3D perovskite family and successfully realized prominent ferroelectricity at the same time. Here, we focus on these new-type HOIPs to perform machine-learning (ML)-based molecular design to screen promising candidates for versatile light harvesting, involving photovoltaics (77 ones), water splitting (216 ones), and photodetection (178 ones), out of 3180 A(II)B(I)X 3 perovskites in total. These candidates await future experimental synthesis and characterization. Our high-throughput ML-based screening of 3D A(II)B(I)X 3 HOIPs would enrich the material inventory by successfully introducing a class of new 3D HOIPs to realize property-oriented light harvesting and additional versatile energy harvesting due to their potential multifunctionalities such as ferroelectricity and electrocaloricity.