Measuring metal halide perovskite single cell degradation consistent with module-based conditions

Literature Information

Publication Date 2024-01-02
DOI 10.1039/D3SE01268A
Impact Factor 6.367
Authors

Robert Tirawat, Mengjin Yang, Severin N. Habisreutinger, Soňa Uličná, Ross A. Kerner, Kai Zhu, Laura T. Schelhas, Axel F. Palmstrom


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Abstract

In past years, there has been progress towards increasing the efficiency of metal halide perovskite solar cells (PSCs) without sacrificing long-term stability. However, preventing or mitigating degradation remains one of the major challenges for the commercialization of PSCs. Researchers must ensure that information learned from cell-level studies is relevant to the ultimate target of module application. In this work, we demonstrate that the bias condition used during aging studies has a measurable impact on degradation. We compared the performance of a large number of devices (n = 486) which were aged either under open-circuit (OC) or quasi-maximum power point (qMPP) conditions. The performance losses between the two conditions are found to be correlated, but notably, aging at OC leads to a more rapid performance decrease. Furthermore, this faster degradation in the OC condition compared with the qMPP condition occurs regardless of device stack design, treatments, or additives as demonstrated across approximately 160 variants of the p-i-n device stack. The OC condition is an important factor for field stability because partial shading of a module can result in individual cells going into OC. The fact that the degradation dynamics between qMPP and OC conditions are highly correlated indicates that aging studies at OC are related to relevant degradation processes. Consequently, stability studies to generate relevant insights into the degradation processes of PSCs can be executed without requiring sophisticated electronic infrastructure. However, care must be taken with cell-level experimental configurations because unintended, artificial degradation mechanisms may arise that are either not relevant to the application (e.g., modules) or obfuscate the results of the study being undertaken.

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