Chen Jing, Lou Yan-Hui, Wang Zhao-Kui
Institute of Functional Nano & Soft Materials (FUNSOM), Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, Soochow University, Suzhou, 215123, China.
College of Energy, Soochow Institute for Energy and Materials Innovations, Soochow University, Suzhou, 215006, China.
Small. 2023 Dec;19(52):e2305064. doi: 10.1002/smll.202305064. Epub 2023 Aug 27.
Due to their greater opt electric performance, perovskite photovoltaics (PVs) present huge potential to be commercialized. Perovskite PV's high theoretical efficiency expands the available development area. The passivation of defects in perovskite films is crucial for approaching the theoretical limit. In addition to creating efficient passivation techniques, it is essential to direct the passivation approach by getting precise and real-time information on the trap states through measurements. Therefore, it is necessary to establish quantitative characterization methods for the trap states in energy and 3D spaces. The authors cover the characterization of the spatial and energy distributions of trap states in this article with an eye toward high-efficiency perovskite photovoltaics. After going over the strategies that have been created for characterizing and evaluating trap states, the authors will concentrate on how to direct the creative development of characterization techniques for trap states assessment and highlight the opportunities and challenges of future development. The 3D space and energy distribution mappings of trap states are anticipated to be realized. The review will give key guiding importance for further approaching the theoretical efficiency of perovskite photovoltaics, offering some future research direction and technological assistance for the development of appropriate targeted passivation technologies.
由于其更优异的光电性能,钙钛矿光伏电池具有巨大的商业化潜力。钙钛矿光伏电池的高理论效率拓展了可开发领域。钙钛矿薄膜中的缺陷钝化对于接近理论极限至关重要。除了开发高效的钝化技术外,通过测量获取关于陷阱态的精确实时信息来指导钝化方法也至关重要。因此,有必要建立能量和三维空间中陷阱态的定量表征方法。本文作者着眼于高效钙钛矿光伏电池,探讨了陷阱态的空间和能量分布表征。在回顾了已创建的用于表征和评估陷阱态的策略后,作者将专注于如何指导用于陷阱态评估的表征技术的创新发展,并突出未来发展的机遇和挑战。预计将实现陷阱态的三维空间和能量分布映射。该综述将为进一步接近钙钛矿光伏电池的理论效率提供关键指导,为开发合适的靶向钝化技术提供一些未来研究方向和技术支持。