Electrical Behavior of Solar Cell based on ZnO/PS

Authors

  • Z.Yamlahi Alami laboratoire de la matière condensée, dept .de physique, faculté de sciences Avenue de Sebta, Mhannech I 93002 - Tétouan – Maroc
  • J.El Khamkhami laboratoire de la matière condensée, dept .de physique, faculté de sciences Avenue de Sebta, Mhannech I 93002 - Tétouan – Maroc
  • M. Salem Laboratoire de Photovoltaïque Centre de Recherches et des Technologies de l’Energie, Technopole de Borj-Cédria, BP 95, 2050 Hammam-Lif, Tunisia
  • M. Gaidi Laboratoire de Photovoltaïque Centre de Recherches et des Technologies de l’Energie, Technopole de Borj-Cédria, BP 95, 2050 Hammam-Lif, Tunisia

DOI:

https://doi.org/10.14738/tmlai.54.3195

Keywords:

component, ZnO, PC1D, Characteristic I-V.

Abstract

Because of high loss of photovoltaic conversion due to reflection of incident photon by the silicon surface, we proposed in this work a single heterojunction solar cell model based on porous silicon (PS) and Zinc oxide to minimize this loss, which the ZnO could act like front n-layer as well as antireflection coating saving processing cost and complexity. In the experiment the ZnO layer was deposited by spray pyrolysis method on porous silicon (PS) using nitrate precursors with different molar concentration. The proposed treatment has also demonstrated a significant decrease in the reflectivity of ZnO/PS. To simulate a solar cell based on porous silicon and zinc oxide, we have used PC1D software. The variation of internal and external quantum efficiency, and I-V characteristics have been done by changing the reflectivity of ARC layer, The I-V results obtained by PC1D simulation was compared with the experiment results: Simulations anticipated conversion efficiency  was 14,5% while by  experiments was 12% for the device fabricated with 0.25 M.

 

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Published

2017-09-01

How to Cite

Alami, Z., Khamkhami, J., Salem, M., & Gaidi, M. (2017). Electrical Behavior of Solar Cell based on ZnO/PS. Transactions on Engineering and Computing Sciences, 5(4). https://doi.org/10.14738/tmlai.54.3195

Issue

Section

Special Issue : 1st International Conference on Affective computing, Machine Learning and Intelligent Systems