Design and optimization of Ca3BiI3-based solar cells through a comprehensive analysis of optoelectronic properties and charge transport layers using simulation and ML

Abstract

Ca₃BiI₃ based solar cells have garnered interest owing to their superior semiconducting characteristics; however, achieving optimal interfacial band alignment with electron transport layers (ETLs) and hole transport layers (HTLs) continues to pose an obstacle for efficiency. This research employs first-principles density functional theory (DFT) to examine the optoelectronic characteristics of Ca₃BiI₃ perovskite and assess its viability for photovoltaic applications. The device configuration, Ag/FTO/ETL/Ca₃BiI₃/HTL/Ni, is examined using three ETLs and six HTLs to determine the optimal material combination. Device parameter optimization, encompassing layer thickness, doping, resistance, and others critical parameters, was performed utilizing the SCAPS-1D simulation tool under AM 1.5 circumstances. The best design, Ag/FTO/IGZO/Ca₃BiI₃/PTAA/Ni, exhibited enhanced performance with a power conversion efficiency (PCE) of 27.64 %, an open-circuit voltage (V_OC) of 0.8436 V, a short-circuit current density (J_SC) of 38.2142 mA/cm², and a fill factor (FF) of 85.74 %. This study combines machine learning with modeling approaches to enhance future photovoltaic developments.