Discovery of Lead-Free Perovskites for High-Performance Solar Cells via Machine Learning: Ultrabroadband Absorption, Low Radiative Combination, and Enhanced Thermal Conductivities.

ABSTRACT: Exploring lead-free candidates and improving efficiency and stability remain the obstacle of hybrid organic-inorganic perovskite-based devices commercialization. Traditional trial-and-error methods seriously restrict the discovery especially for large search space, complex crystal structure and multi-objective properties. Here, the authors propose a multi-step and multi-stage screening scheme to accelerate the discovery of hybrid organic-inorganic perovskites A₂ BB'X₆ from a large number of candidates through combining machine learning with high-throughput calculations for pursuing excellent efficiency and thermal stability in solar cells. Followed by a series of screenings, the structure-property relationships mapping A₂ BB'X₆ properties are bui

SUBMITTER: Cai X 

PROVIDER: S-EPMC8811845 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature