4.8 Article

Efficiency enhancement of hybridized solar cells through co-sensitization and fast charge extraction by up-converted polyethylene glycol modified carbon quantum dots

期刊

JOURNAL OF POWER SOURCES
卷 367, 期 -, 页码 158-166

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.jpowsour.2017.09.055

关键词

Dye-sensitized solar cell; Up-conversion; Light absorption; Solar energy utilization

资金

  1. National Natural Science Foundation of China [61774139, 21503202, 61604143]
  2. Shandong Provincial Natural Science Foundation [ZR2015EM024]
  3. Fundamental Research Funds for the Central Universities [201762018]

向作者/读者索取更多资源

Photovoltaics are promising solutions to energy crisis and environmental pollution problems. The dye sensitized solar cells with mesoscopic structures have attracted growing interests because of zero emissions, easy fabrication, scalable materials and techniques, etc. However, the state-of-the-art dye sensitized solar cells have narrow spectral absorption for photoelectric conversion and high electron hole recombination rate under sunlight illumination. Therefore, it is a persistent object to make wide spectral absorption and fast charge extraction solar cells for energy harvest in both solar and dark light conditions. To address this issue, we present here experimental realization of a category of solar cells converting visible and near-infrared light into electricity by co-sensitizing photoanode with N719 dye and polyethylene glycol (PEG) modified carbon quantum dots (PEG-m-CQDs), arising from up conversion and hole-transporting behaviors of PEG-m-CQDs as well as photofluorescence of green emitting long persistence phosphors. The optimized solar cell yields maximized photoelectric conversion efficiencies of 9.89% and 25.81% under simulated sunlight (air mass 1.5,100 mW cm(-2)) illumination and dark conditions, respectively. This work is far from optimization, but the physical proof-of-concept hybridized solar cell may markedly increase electricity generation time and total power output of photovoltaic platforms. (C) 2017 Elsevier B.V. All rights reserved.

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