Machine learning-driven halide perovskite photovoltaics: from data screening to accelerated industrialization

Machine learning integrates multi-source data, active learning, and automated experiments into closed-loop workflows for halide perovskite photovoltaics. This review assesses screening, process/stability optimization, and industrial translation.