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Investigation of recombination mechanisms in Cu(In,Ga)Se2 solar cells using numerical modelling

(2021) SOLAR ENERGY. 228. p.464-473
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Abstract
In this work, recombination mechanisms are investigated in Cu(In, Ga)Se-2 solar cells based on numerical modelling and verified by regression analysis of the dark and light current density-voltage (J-V) curves. Loss mechanisms such as a back contact barrier, deep level defects in the absorber layer are determined by fitting the simulated cell performance with the measurements using global optimisation algorithm differential evolution. The cell performance in the fitting process includes J-V curves recorded at different temperatures and opencircuit voltage(V-oc) under different illumination intensifies at 300K. The results show that for CIGSe solar cells with different preparation methods and absorber thickness, the main loss mechanisms are different. Based on the proposed numerical model and the observed loss mechanisms, suggestions are given for further improving the solar cell efficiency in each cell.
Keywords
LEVEL TRANSIENT SPECTROSCOPY, DEFECTS, CUINSE2, BULK, CIGSe solar cell, Recombination mechanisms, Numerical modelling, Regression analysis, Differential evolution

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MLA
Yang, Sheng, et al. “Investigation of Recombination Mechanisms in Cu(In,Ga)Se2 Solar Cells Using Numerical Modelling.” SOLAR ENERGY, vol. 228, 2021, pp. 464–73, doi:10.1016/j.solener.2021.09.041.
APA
Yang, S., Khelifi, S., de Wild, J., Vermang, B., & Lauwaert, J. (2021). Investigation of recombination mechanisms in Cu(In,Ga)Se2 solar cells using numerical modelling. SOLAR ENERGY, 228, 464–473. https://doi.org/10.1016/j.solener.2021.09.041
Chicago author-date
Yang, Sheng, Samira Khelifi, Jessica de Wild, Bart Vermang, and Johan Lauwaert. 2021. “Investigation of Recombination Mechanisms in Cu(In,Ga)Se2 Solar Cells Using Numerical Modelling.” SOLAR ENERGY 228: 464–73. https://doi.org/10.1016/j.solener.2021.09.041.
Chicago author-date (all authors)
Yang, Sheng, Samira Khelifi, Jessica de Wild, Bart Vermang, and Johan Lauwaert. 2021. “Investigation of Recombination Mechanisms in Cu(In,Ga)Se2 Solar Cells Using Numerical Modelling.” SOLAR ENERGY 228: 464–473. doi:10.1016/j.solener.2021.09.041.
Vancouver
1.
Yang S, Khelifi S, de Wild J, Vermang B, Lauwaert J. Investigation of recombination mechanisms in Cu(In,Ga)Se2 solar cells using numerical modelling. SOLAR ENERGY. 2021;228:464–73.
IEEE
[1]
S. Yang, S. Khelifi, J. de Wild, B. Vermang, and J. Lauwaert, “Investigation of recombination mechanisms in Cu(In,Ga)Se2 solar cells using numerical modelling,” SOLAR ENERGY, vol. 228, pp. 464–473, 2021.
@article{8736285,
  abstract     = {{In this work, recombination mechanisms are investigated in Cu(In, Ga)Se-2 solar cells based on numerical modelling and verified by regression analysis of the dark and light current density-voltage (J-V) curves. Loss mechanisms such as a back contact barrier, deep level defects in the absorber layer are determined by fitting the simulated cell performance with the measurements using global optimisation algorithm differential evolution. The cell performance in the fitting process includes J-V curves recorded at different temperatures and opencircuit voltage(V-oc) under different illumination intensifies at 300K. The results show that for CIGSe solar cells with different preparation methods and absorber thickness, the main loss mechanisms are different. Based on the proposed numerical model and the observed loss mechanisms, suggestions are given for further improving the solar cell efficiency in each cell.}},
  author       = {{Yang, Sheng and Khelifi, Samira and de Wild, Jessica and Vermang, Bart and Lauwaert, Johan}},
  issn         = {{0038-092X}},
  journal      = {{SOLAR ENERGY}},
  keywords     = {{LEVEL TRANSIENT SPECTROSCOPY,DEFECTS,CUINSE2,BULK,CIGSe solar cell,Recombination mechanisms,Numerical modelling,Regression analysis,Differential evolution}},
  language     = {{eng}},
  pages        = {{464--473}},
  title        = {{Investigation of recombination mechanisms in Cu(In,Ga)Se2 solar cells using numerical modelling}},
  url          = {{http://doi.org/10.1016/j.solener.2021.09.041}},
  volume       = {{228}},
  year         = {{2021}},
}

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