High-Throughput Imaging of Degradation-Inducing Microscopic Impurities in Perovskite Solar Cells
The scalable fabrication of high-quality, large-area perovskite thin films is hindered by microscopic inhomogeneities, particularly residual compositional impurities formed during processing. Identifying these impurities, understanding their impact on device operation, and enabling their rapid detection are essential for upscaling perovskite solar cells (PSCs). Here, nano-Fourier transform infrared spectroscopy combined with high-resolution optical and scanning probe techniques was used to identify detrimental impurities in wide-bandgap perovskite films relevant to tandem solar cells. Photo-stress experiments revealed that degradation of the perovskite layer initiates at impurity-perovskite interfaces, demonstrating that impurities act as failure nucleation sites. Leveraging these insights, a rapid, non-invasive, and high-throughput framework based on high-resolution reflected light microscopy and machine learning-supported image analysis was developed, enabling detection and quantification of harmful impurities in as-prepared films within seconds. Films with higher impurity density show accelerated early degradation, establishing this parameter as an early-warning metric for stability screening. Extending this framework to degradation tracking further reveals coupled photo- and thermo-chemical contributions to impurity-mediated instability. Overall, this work establishes a practical chemically-validated diagnostic imaging framework for rapid pre-screening of perovskite films to enable stable and scalable PSCs.