An Optimization of Cs2TiBr6 Perovskite Solar Cell Using SCAPS‐1D Simulation Based on Genetic Algorithm

A genetic algorithm (GA) was used in this simulation work and a well-studied double perovskite structure was chosen to verify the feasibility of the algorithm. To pursue excellent efficiency and stability of the perovskite solar cell, the experimental and simulation data were summarized to determine the adjustable range of parameters for the simulated cell structure. The GA can help us to determine the best combination among a wide range of potential possibilities. The optimal solution was obtained by substituting the best combination data into SCAPS-1D and the open circuit voltage (V-OC) was 1.08 V, fill factor (FF) was 88.81%, short circuit current (J(SC)) was 37.06 mA/cm(2), and the power conversion efficiency (PCE) was 35.54%. Compared to the initial simulation results, the efficiency was improved by 10 percentage points and the J(SC) increased by 12 mA/cm(2). From these conclusions, it was clear that the GA provides a faster and more accurate way to find the optimal solution for perovskite solar cells.