钝化
材料科学
钙钛矿(结构)
制作
碲化镉光电
光电子学
光伏
太阳能电池
纳米技术
能量转换效率
工程物理
薄脆饼
硅
镓
光伏系统
电气工程
图层(电子)
冶金
化学工程
工程类
病理
医学
替代医学
作者
Zhifang Wu,Enbing Bi,Luis K. Ono,Deng‐Bing Li,Osman M. Bakr,Yanfa Yan,Yabing Qi
出处
期刊:Nano Energy
[Elsevier]
日期:2023-07-22
卷期号:115: 108731-108731
被引量:50
标识
DOI:10.1016/j.nanoen.2023.108731
摘要
Because of high efficiencies and low-cost fabrication, perovskite solar cells (PSCs) have drawn great attention. Although an impressive power conversion efficiency (PCE) of 26.1% has been achieved, there is still room for further improvements before these cells reach their theoretical limit. One major factor limiting the PCE of PSCs is defect-induced recombination. Defect passivation strategies have proven useful in improving the PCE of PSCs. In this review, we first briefly summarize the passivation methods and theories for other solar cell technologies, including silicon solar cells, cadmium telluride solar cells and copper indium gallium selenide solar cells. We then introduce the various types of defects present in PSCs and the corresponding passivation methods. Finally, we provide future perspectives and propose that it is exigent to establish a better understanding of the relationship between the properties of passivation materials and their defect passivation effects on perovskite materials and device performance. To understand this relationship, machine learning can be a powerful tool to advance the design and synthesis of passivation materials to enhance device performance of PSCs.
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