journal article·2024-04-15Open access

Effect of defect density, bandgap profile, material composition, thickness, and doping density of the absorber layer on the performance of thin film solar cell based on antimony selenosulfide Sb2(Se1-ySy)3

Laboratory of Electrical Engineering (LAGE), Department of Electrical Engineering, Kasdi Merbah University Ouargla, Ouargla 30000, Algeria, A. Benmir, M. L. Louazene, Laboratory of Electrical Engineering (LAGE), Department of Electrical Engineering, Kasdi Merbah University Ouargla, Ouargla 30000, Algeria

Chalcogenide Letters· Volume 21· Issue 4

Abstract

This article deals with the optimization by simulation of a graded bandgap thin film solar cell based on antimony selenosulfide Sb2(Se1-ySy)3 having the following structure: Front contact/n-ZnO/i-ZnO/p-SbSSe/n-CdS/Back contact. The simulation is performed using SCAPS-1D software. The optimization process includes optimizing the bulk defect density, bandgap profile, material composition, thickness, and doping density of the absorber layer of thin film solar cell based on antimony selenosulfide Sb2(Se1-ySy)3. We found that for a bulk defect density below 1013 cm-3 , using an absorber material with a graded bandgap profile leads to an efficiency of 25.33 % (For a bulk defect density of 1010 cm-3 ) higher than that with a uniform bandgap profile. However, for a bulk defect density of 1013 cm-3 , both profiles provide almost the same maximum solar cell conversion efficiencies of about 13.6 %. Ultimately, for a bulk defect density above 1013 cm-3 , the graded bandgap profile is not useful, and a maximum solar cell conversion efficiency of 10.5 % (For a bulk defect density of 1014 cm-3 ) is achieved with a uniform bandgap profile. These optimization results help to improve the efficiency of low-cost fabricated thin-film solar cells.
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Research context

OpenAlex topics: Chalcogenide Semiconductor Thin Films · Quantum Dots Synthesis And Properties · solar cell performance optimization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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