发表机构
King Abdullah University of Science and Technology (KAUST); Ludwig-Maximilians-University (LMU) Munich（阿卜杜拉国王科技大学; 慕尼黑路德维希-马克西米利安大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究开发了一种基于纳米红外光谱和机器学习图像分析的高通量成像框架，用于快速检测钙钛矿薄膜中的有害杂质，并将其作为稳定性筛选的早期预警指标。
AI 中文摘要
高质量、大面积钙钛矿薄膜的可扩展制造受到微观不均匀性的阻碍，特别是在加工过程中形成的残余成分杂质。识别这些杂质、理解其对器件操作的影响以及实现其快速检测对于扩大钙钛矿太阳能电池（PSCs）至关重要。在此，将纳米傅里叶变换红外光谱与高分辨率光学和扫描探针技术相结合，用于识别与叠层太阳能电池相关的宽带隙钙钛矿薄膜中的有害杂质。光应力实验揭示，钙钛矿层的退化始于杂质-钙钛矿界面，表明杂质充当失效成核位点。利用这些见解，开发了一种基于高分辨率反射光显微镜和机器学习支持的图像分析的快速、非侵入性且高通量的框架，能够在几秒钟内检测和量化制备薄膜中的有害杂质。具有较高杂质密度的薄膜表现出加速的早期退化，将该参数确立为稳定性筛选的早期预警指标。将该框架扩展到退化跟踪进一步揭示了光化学和热化学对杂质介导的不稳定性的耦合贡献。总体而言，这项工作建立了一种实用的经化学验证的诊断成像框架，用于钙钛矿薄膜的快速预筛选，以实现稳定且可扩展的PSCs。
英文摘要
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.
Comments20 pages, 4 figures
