Li, Ag Co‐Doping Enables Efficient Kesterite Solar Cell with a High Fill Factor of 74.30%

锌黄锡矿 材料科学 兴奋剂 载流子寿命 辐射传输 萃取(化学) 光电子学 太阳能电池 光学 化学 色谱法 物理 捷克先令
作者
Xinyi Zhong,Jinlin Wang,Litao Han,Jun-hong Chi,Tong Liu,Dongxing Kou,Wenhui Zhou,Zhengji Zhou,Shengjie Yuan,Yuena Meng,Yafang Qi,Qingbo Meng,Sixin Wu
出处
期刊:Advanced Functional Materials [Wiley]
标识
DOI:10.1002/adfm.202418548
摘要

Abstract In addition to open‐circuit voltage (V OC ) loss, fill factor (FF) loss is considered another major factor restricting the further optimization of Cu 2 ZnSn(S,Se) 4 (CZTSSe) device efficiency. In this work, a comprehensive investigation into the loss mechanisms of FF has been conducted, and implemented a Li&Ag co‐doping approach to enhance FF. The results indicate that the FF loss caused by insufficient carrier extraction is higher than that caused by non‐radiative recombination. The carrier extraction capability is significantly influenced by the band alignment of the CdS/CZTSSe interface and has little relationship with the carrier concentration of the absorber. Therefore, although Ag doping reduces the hole concentration and conductivity, it reduces the FF loss caused by carrier extraction due to the improvement of band alignment. Ag doping is also superior to Li in passivating harmful defects, which helps reduce FF losses caused by non‐radiative recombination. Correspondingly, Li performs better than Ag in increasing the hole carrier concentration and optimizing band alignment, greatly reducing FF losses caused by insufficient carrier transport. Finally, the Li and Ag co‐doping strategy enables a 14.91% efficient kesterite solar cell with the highest reported FF to date of 74.30% through collaborative optimization of carrier extraction and suppression of non‐radiative recombination.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
气945完成签到,获得积分20
1秒前
zyy发布了新的文献求助10
1秒前
Sarah发布了新的文献求助10
1秒前
2秒前
2秒前
搜集达人应助Membranes采纳,获得10
2秒前
传奇3应助小小采纳,获得10
3秒前
善学以致用应助气945采纳,获得10
4秒前
负责的煎蛋完成签到,获得积分10
5秒前
siyarn发布了新的文献求助10
5秒前
Sarah完成签到,获得积分10
5秒前
7秒前
ccboom完成签到 ,获得积分10
7秒前
8秒前
潇洒的擎苍完成签到,获得积分10
9秒前
完美世界应助FLMXene采纳,获得10
9秒前
Why顺利完成签到,获得积分10
10秒前
12秒前
13秒前
青山完成签到,获得积分10
13秒前
fap完成签到,获得积分10
15秒前
健康的涵蕾完成签到,获得积分10
15秒前
斯文败类应助北风采纳,获得10
17秒前
17秒前
勤奋幻姬发布了新的文献求助20
18秒前
19秒前
19秒前
险胜应助科研通管家采纳,获得10
19秒前
星辰大海应助科研通管家采纳,获得10
19秒前
科研通AI2S应助科研通管家采纳,获得10
19秒前
毛豆应助科研通管家采纳,获得10
20秒前
20秒前
Qiao应助科研通管家采纳,获得10
20秒前
QDU应助科研通管家采纳,获得10
20秒前
今后应助科研通管家采纳,获得10
20秒前
Lyncus应助科研通管家采纳,获得50
20秒前
20秒前
hyd发布了新的文献求助10
20秒前
20秒前
maox1aoxin应助科研通管家采纳,获得30
20秒前
高分求助中
Licensing Deals in Pharmaceuticals 2019-2024 3000
Cognitive Paradigms in Knowledge Organisation 2000
Effect of reactor temperature on FCC yield 2000
Very-high-order BVD Schemes Using β-variable THINC Method 1020
Near Infrared Spectra of Origin-defined and Real-world Textiles (NIR-SORT): A spectroscopic and materials characterization dataset for known provenance and post-consumer fabrics 610
Mission to Mao: Us Intelligence and the Chinese Communists in World War II 600
Promoting women's entrepreneurship in developing countries: the case of the world's largest women-owned community-based enterprise 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3307038
求助须知:如何正确求助?哪些是违规求助? 2940878
关于积分的说明 8499088
捐赠科研通 2615019
什么是DOI,文献DOI怎么找? 1428599
科研通“疑难数据库(出版商)”最低求助积分说明 663478
邀请新用户注册赠送积分活动 648318