Abstract

This work presents the development of two computational models aimed at predicting the electrical performance and impedance behavior of TiO2 dye-sensitized solar cells (DSSCs) containing Ag nanoparticles (NPs). A model based on diffusion principles is developed to estimate photovoltaic characteristics of devices with various contents of Ag NPs. The impact of mercaptopropionic acid (MPA) as a capping agent of silver NPs on conversion efficiency of the cells is analyzed. Furthermore, an investigation is carried out to determine various key factors, including photoanode thickness, operating temperature, dark electron concentration, carrier lifetime, electron diffusion coefficient, light intensity, absorption coefficient of the photoanode, and ideality factors for the optimum Ag content of 1.56 x 10-5 M on device behavior. To optimize these parameters and quantify their reliability, the model is coupled with Monte Carlo simulations, enabling probabilistic performance predictions. Furthermore, electrochemical impedance is examined using the Kerner model, where Nyquist plots illustrate how MPA affects both the real and imaginary components. The accuracy of the developed models is confirmed by comparing their predictions with experimental results, revealing a reliable performance.