Spatially resolved power conversion efficiency for perovskite solar cells via bias-dependent photoluminescence imaging

Anh Dinh Bui*, Dang Thuan Nguyen, Andreas Fell, Naeimeh Mozaffari, Viqar Ahmad, The Duong, Li Li, Thien N. Truong, Ary Anggara Wibowo, Khoa Nguyen, Oliver Fischer, Florian Schindler, Martin C. Schubert, Klaus J. Weber, Thomas P. White, Kylie R. Catchpole, Daniel Macdonald*, Hieu T. Nguyen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Hybrid organic-inorganic perovskite solar cells (PSCs) offer a highly promising solution for achieving low-cost, high-performance photovoltaics. However, to accelerate the development of the PSC technology, it is critical to quantify local performance losses and identify problematic regions across the device. Obtaining spatially resolved information is essential not only for device fabrication but also for material optimization, particularly when scaling up the perovskite technology. In this work, we propose an imaging-based approach to spatially resolve local series resistance, power conversion efficiency (PCE), and charge-transfer efficiency across PSCs by employing bias-dependent photoluminescence (PL). By analyzing these parameters' images, we find a significant correlation between the charge-transfer efficiency and the PCE. However, we observe a weak correlation between the intensity of the PL image taken under open-circuit conditions and the final PCE of the device. This finding highlights the risk of misinterpreting the device performance if using only PL intensities. Moreover, we demonstrate the impact of the voltage-dependent series resistance on the accuracy of the device simulation. This work presents another important contribution of luminescence imaging to the research and development of the perovskite solar cells technology.

Original languageEnglish
Article number101641
JournalCell Reports Physical Science
Volume4
Issue number11
DOIs
Publication statusPublished - 15 Nov 2023

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