The champion efficiency of small area perovskite solar cells is marginally behind their silicon counterpart. However, when up-scaled to large area modules, the performance of perovskite solar cells drops significantly due primarily to the inclusion of defects during fabrication. The future of perovskite solar cells depends greatly on the ability to fabricate high efficiency large area devices which requires methods for rapidly and reliably identifying the presence of damage or imperfections that limit their performance. In this work we employ, for the first time, intensity modulated photoluminescence to spatially map the series resistance of perovskite solar cells with high spatial resolution. The technique permits the rapid identification of a range of different macroscopic defects and quantifies the impact on the local series resistance. It is performed under steady-state conditions to avoid complications of transient behaviour occurring in the perovskite film. The robustness of the approach is demonstrated by characterising an entire batch of perovskite solar cells with the mean series resistance values validated using established electrical analysis methods. Our method can be readily applied by other research groups for device optimisation or scaled to large areas for automated process control and validation.

小面积钙钛矿太阳能电池的最高效率仅次于其硅同类产品。然而，当按比例放大到大面积模块时，钙钛矿太阳能电池的性能显着下降，这主要是由于在制造过程中包含了缺陷。钙钛矿太阳能电池的未来很大程度上取决于制造高效率大面积器件的能力，这需要快速而可靠地识别出限制其性能的损坏或缺陷的方法。在这项工作中，我们首次使用强度调制的光致发光来以高空间分辨率在空间上映射钙钛矿型太阳能电池的串联电阻。该技术可以快速识别一系列不同的宏观缺陷，并量化对局部串联电阻的影响。它在稳态条件下进行，以避免钙钛矿薄膜中发生瞬态行为的复杂性。通过对整批钙钛矿型太阳能电池进行表征，证明了该方法的鲁棒性，并使用已建立的电分析方法验证了平均串联电阻值。我们的方法可以很容易地被其他研究小组用于设备优化，也可以扩展到大面积进行自动化过程控制和验证。