Artificial neural network assisted numerical analysis on performance enhancement of Sb2(S,Se)3 solar cell with SnS as HTL

Abstract

This paper presents the design and investigation of a highly efficient photovoltaic (PV) device comprising antimony sulfide-selenide (Sb2(S,Se)3) absorber utilizing the SCAPS-1D simulator. Initially, the validity of this simulation process is justified by reproducing the experimental structure, and a comparison is made between the experimental and simulation outcomes. Then we have inserted tin sulfide (SnS) as a hole transport layer (HTL) and zinc sulfide (ZnS) as a buffer at the back and front parts of the suggested new heterojunction structure. In addition, to explore the role of intrinsic parameters on performances of the designed device, an artificial neural network-based machine learning (ML) algorithm is applied. It is revealed that the proposed SnS HTL and ZnS buffer form better band alignment with the promising Sb2(S,Se)3 absorber than others. Thus, the efficiency improves by diminishing recombination loss in the proposed Sb2(S,Se)3 solar device. The PV parameters are also thoroughly assessed by varying crucial factors including absorber thickness, acceptor concentration, defects in absorber, defects at SnS/Sb2(S,Se)3 and Sb2(S,Se)3/ZnS interfaces, temperature, work function, and cell resistances. To achieve the best performances, the thicknesses of HTL, absorber, and buffer are optimized to be 0.1 μm, 1.0 μm, and 0.05 μm, respectively. The simulation predicts an efficiency of 28.20 % accompanied by open-circuit voltage (Voc) of 0.94 V, short-circuit current density (Jsc) of 34.65 mA/cm2, and fill-factor (FF) of 86.22 %. Implementation of ML algorithms uncovers that the predicted performance for both training and testing data is correlated with the actual PCE generated by the SCAPS-1D. The optimized physical parameters derived in this simulation will be very useful for researchers to establish an environmentally friendly, cost-effective, and highly efficient Sb2(S,Se)3-based thin-film PV devices.