Publication date: 16th July 2025
Photoluminescence (PL) based methods are powerful tools to investigate and understand the different physical mechanisms governing the performance of perovskite devices. In this contribution, we highlight the different methods that can be derived from bias-dependent absolute calibrated hyperspectral imaging and time-resolved PL and VOC decay.
First, we discuss the absolute calibration of a hyperspectral imaging tool that features LED-based illumination. This enables spatially resolved extraction of photoluminescence quantum yield, quasi-Fermi level splitting (QFLS) and implied VOC. Next, with the ability to apply a bias-voltage PL, measurements can be performed also under short-circuit conditions and the calculation of a charge extraction coefficient is possible. Measurements at varying voltages result in reconstructed local implied J(V) curves. Further, illumination intensity variations yield both suns-VOC and local suns-PL curves, such that losses from interfaces and from transport can be disentangled. Measurements at different temperature levels finally reveal complex spatial variations in recombination phenomena. Overall, by assessing the QFLS, charge extraction quality, and reconstructed JV characteristics, we are able to gain insights on the essential solar cell parameters, VOC, JSC, and FF, with microscopic spatial resolution.
Additionally, we performed also time-resolved PL measurements. The setup has two distinct features: First, the illumination is quasi-continuous and has a rapid shut-off capability, allowing for PL decay measurements from a defined illumination level. Next, the VOC decay can be tracked parallel to the PL signal. From the direct comparison, the impact of ion movements can be derived.
Applied to both pristine and especially samples subjected to accelerated aging, the combination of this powerful set of tools allows for the investigation of the fundamental causes of performance limitations.
The project was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under project numbers 506702510 and 506701742, and by the European Regional Development Fund as part of the Union's response to the COVID-19 pandemic.
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