Publication date: 28th August 2024
Lead halide perovskite-based photovoltaics has attracted great attention in the last decade since silicon PV as the dominating technology is approaching its theoretical efficiency limit. Combined in a silicon-perovskite (Si-Pero) tandem solar cell, they promise a substantial leap in power conversion efficiency beyond the single-junction limit without increasing cost significantly. However, realizing high performance in module-sized formats is, in part, held back by the practical challenge of producing uniform high-quality perovskite layers onto large scale silicon bottom cells. Perovskite thin films are highly poly-crystalline and mechanically soft resulting in high defect concentration and inhibiting efficient carrier extraction if not properly controlled.
In pursuit of a non-invasive and robust in-line imaging method that locally resolves the quality of the perovskite thin film absorber processed over a silicon bottom solar cell, we advanced the k-imaging method developed by Hacene et al. [1] also for Si-Pero tandem solar cells. K-imaging is based on intensity dependent perovskite photoluminescence, eliminating the effect from constant optical in- and out-coupling effects. With a basic power law model a single effective parameter k is extracted which reflects the complex superposition of competing recombination processes, i.e. radiative band-to-band, non-radiative trap-assisted bulk (Shockley-Read-Hall) and interface recombination. This parameter k allows for quantitative analysis simplifying the interpretation significantly in contrast to qualitative PL imaging, while barely raising setup complexity and cost.
We show that k-imaging reproducibly identifies general quality discrepancies as well as local inhomogeneities, which clearly correlate with typical defects in the thin film. Further, we proved its applicability regardless of specific perovskite processing techniques and its compatibility with flat as well as industrially relevant textured Silicon bottom cells. Overall, k-imaging is a valuable and unique technique meeting the requirements for efficient optimization in academic research as well as quality assessment in large-scale industrialized production of Si-Pero tandem solar cells.
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