Optimizing Zn-doped CuO for ecofriendly solar cells: A hybrid SCAPS-1D/machine learning approach

Addressing the critical demand for high-efficiency, thermally stable, and low-cost photovoltaics, this highly impactful work presents a breakthrough solar cell architecture featuring WS 2 as the electron transport layer and CuI as the hole transport layer. We rigorously analyzed WS 2 /CuO and CuO/CuI interfaces to optimize charge transport using SCAPS-1D simulations. To accelerate parameter exploration, six machine-learning models were evaluated, with Random Forest and Gradient Boosting achieving superior predictive accuracy (MAE <1%, R 2 =0.90). Feature importance analysis revealed zinc doping concentration as the dominant performance driver (72% contribution), with efficiency declining beyond 6–8% doping. Under standard conditions (300 K), the optimized device achieved a remarkable PCE of 25.88% (Jsc=20.10 mA/cm², Voc=1.447 V, FF=89.05%), further rising to 26.45% with WS 2 layer tuning. These results provide insights into the relationship between Zn concentration, defect density, interface quality, and photovoltaic performance, highlighting 8% Zn-doped CuO/ WS2 as a promising and potentially low-cost absorber material for thin-film solar-cell applications.