Publication date: 15th December 2025
Luminescence-based optical imaging is a powerful, contactless, and non-destructive tool for investigating halide perovskite materials and solar cells across all stages of their development. In this talk, I will present how multimodal photoluminescence techniques enable microscopic, quantitative insights into perovskite stability, optoelectronic properties, and device performance. First, I will examine the response of halide perovskites to external stressors such as humidity and X-ray illumination, highlighting the emergence of self-healing behaviour after irradiation. I will then demonstrate how quantitative photoluminescence imaging links fundamental optoelectronic properties to device-level performance, with particular emphasis on interfacial passivation using organic cations to suppress non-radiative recombination. These methods are also extensible to the characterization of larger devices. We demonstrate this by applying a quantitatively calibrated hyperspectral PL/EL imaging approach to a 64 cm² perovskite mini-module, enabling spatially resolved EQE maps derived from EL measurements. This multimodal method reveals recombination hotspots, transport bottlenecks, and series-resistance variations that drive FF and PCE heterogeneity, highlighting key upscaling losses in interconnected modules. Finally, I will introduce an unsupervised deep-learning framework that overcomes noisy data and long acquisition times of time-resolved fluorescence imaging (TR-FLIM). By combining Noise2Noise training with physics-informed modelling, the method yields high-fidelity lifetime maps from short exposures, reducing sample degradation while enabling accurate extraction of bulk and surface recombination parameters. It is therefore suitable to performe operando experiment of fragile materials.
