Optimizing the Reproducibility of Organic-Inorganic Hybrid Perovskite Thin-Films via Robotic Precision Control for High-Efficiency Solar Cells

Abstract

Organic–Inorganic Hybrid Perovskites （OIHPs） have emerged as a premier next-generation photovoltaic material, achieving power conversion efficiencies （PCEs） exceeding 27%. [1~2] However, the conventional fabrication process predominantly relies on manual trial-and-error methods, which are inherently prone to operator-dependent variability and low throughput. [3~5] This stochastic nature of manual dripping and coating leads to significant performance fluctuations, hindering the reliable transition from lab-scale research to industrial production. In this work, we address these challenges by employing a fully automated robotic system designed to explore and optimize complex process-parameter spaces under ambient air conditions. By systematically investigating the correlation between mechanical execution and device performance, we identified that the sub-millimeter precision in positioning and meticulously calibrated dispensing rates of anti-solvent dripping speed and height is a critical determinant of film morphology and crystallinity. Through this robotic optimization, we successfully achieved a peak PCE of over 25% with remarkable reproducibility, demonstrating a minimized performance deviation of only 1.5% across 100 device data points. Our findings prove that transitioning from human-dependent fabrication to a standardized robotic platform effectively eliminates the inherent limitations of manual processes, establishing a new benchmark for the reliable and large-scale production of high-performance perovskite solar cells.