钙钛矿(结构)
材料科学
能量转换效率
光致发光
等效串联电阻
光电子学
光伏
光伏系统
钙钛矿太阳能电池
制作
电压
纳米技术
计算机科学
电气工程
化学
医学
替代医学
病理
工程类
结晶学
作者
Anh Dinh Bui,Dang-Thuan Nguyen,Andreas Fell,Naeimeh Mozaffari,Viqar Uddin Ahmad,The Duong,Li Li,Thien N. Truong,Ary Anggara Wibowo,Khoa Dang Nguyen,Oliver Fischer,Florian Schindler,Martin C. Schubert,Klaus Weber,Thomas P. White,Kylie Catchpole,Daniel Macdonald,Hieu T. Nguyen
标识
DOI:10.1016/j.xcrp.2023.101641
摘要
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.
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