Optimization of Transport Layers and Physical Properties in Mg3BiCl3 Solar Cells via Cutting‐Edge Numerical Simulations and Machine Learning

This research examines the optoelectronic properties of Mg 3 BiCl 3 through density function theory (DFT) simulations. The photovoltaic efficacy of solar cells using Mg 3 BiCl 3 as the absorber is evaluated through the SCAPS 1D tool, with WS 2 and C 60 as electron transport layers (ETLs), alongside various hole transport layers (HTLs), including Cu 2 O, CFTS, CuO, Cuss, NiO, and P3HT, and is thoroughly examined. Cu 2 O is identified as the ideal HTL, and its performance is subsequently simulated utilizing the SCAPS 1D tool. Two separate device architectures are assessed: Device‐I (Al/ITO/WS 2 /Mg 3 BiCl 3 /Cu 2 O/Ni) and Device‐II (Al/ITO/C 60 /Mg 3 BiCl 3 /Cu 2 O/Ni). To attain optimal device performance, numerous parameters are optimized, encompassing doping densities, defect density, series and shunt resistances, layer thickness, carrier generation‐recombination, temperature, and quantum efficiency. Among the two configurations, Device‐I demonstrates superior performance, achieving a power conversion efficiency (PCE) of 30.23%, with an open‐circuit voltage (V OC ) of 1.1411 V, a short‐circuit current density (J SC ) of 30.31 mA cm −2 , and a fill factor (FF) of 87.29%. Additionally, optimal PCE is predicted by analyzing multiple semiconductor attributes using a random forest machine learning model. A mean correlation coefficient (R 2 ) of ≈0.8475 is attained by the model, indicating robust predictive accuracy and reliability. The findings underscore significant potential for high‐performance Mg 3 BiCl 3 ‐based solar cells.