Abstract

This study develops two predictive models to estimate the photocurrent density-voltage characteristics and electrochemical impedance spectroscopy of dye-sensitized solar cells (DSCs) incorporating TiO2/g-C3N4 nanocomposites. A diffusion differential model is formulated to predict the photocurrent density based on electron diffusion within the nanocomposite, considering the impact of g-C3N4 content. Moreover, a sensitivity analysis is conducted to examine the impact of key parameters, including photoanode thickness, operating temperature, equilibrium electron concentration in the dark, electron lifetime, electron diffusion coefficient, light intensity, light absorption coefficient of the photoanode, and ideality factors for DSCs containing 20 wt% g-C3N4. To establish design criteria and determine the optimal values for key parameters, the developed model is integrated with Monte Carlo simulations for predicting the device's photovoltaic performance. This integration enables the assessment of success probability as a function of key parameters. Furthermore, the Kerner model is employed to predict the electrochemical impedance of solar cells. The impact of g-C3N4 content on the real and imaginary components of electrical impedance is analyzed using Nyquist plots. The predictive performance of the proposed models is validated against experimental data, demonstrating strong agreement between the model results and experimental observations.