Perovskite Solar Cell Optimization via Polynomial Differential Quadrature Analysis with Block Marching

This paper introduces a novel numerical model for analyzing and optimizing the performance of perovskite solar cells, a technology with rapidly growing potential for high-efficiency energy conversion. The model focuses on a CH3NH3GeI3 absorber layer sandwiched between ZnO and PEDOT:PSS transport layers. It employs Poisson's and continuity equations, solved using the Polynomial Differential Quadrature (PDQ) method in conjunction with block marching and iterative techniques. This approach offers enhanced accuracy and computational efficiency compared to traditional methods, enabling more detailed device simulations. A MATLAB program is implemented to obtain numerical solutions, validated against experimental data and other numerical methods, demonstrating the model's reliability. A comprehensive parametric study is conducted to investigate the influence of critical parameters on the fill factor and efficiency of the solar cell. The results provide valuable, quantitatively precise insights for optimizing perovskite solar cell design, potentially accelerating the development of higher-performance, cost-effective solar energy solutions.