Parameter Estimation of AI/p-Si Schottky Barrier Diode Using Different Meta-Heuristic Optimization Techniques

Abstract

Schottky barrier diodes (SBD) are crucial in the electronics sector. The electronic properties of SBD are characterized by three basic electrical parameters as the ideality factor (n), barrier height (ΦSB) and series resistance (RS). These parameters are significant in designing and producing SBD. This paper presents a comprehensive review of metaheuristic optimization techniques used to determine the fundamental electrical parameters of SBD using experimental forward current–voltage (I-V) characteristics. In the study, popular meta-heuristic optimization techniques, such as GA, PSO, ALO, EO, DA, HHO, GWO, WOA, MFO, MVO, and SCA algorithms, are employed for the parameter estimation of SBD. Among these chosen algorithms, meta-heuristic optimization techniques, such as GWO, WOA, HHO and AHA, have been used for the first time in the literature for parameter estimation of SBD. Firstly, parameter values have been calculated using experimental (I-V) characteristics. Following that, the findings were compared to the values that had been estimated utilizing optimization techniques. Moreover, the performance of meta-heuristic optimization algorithms in determining the basic parameters of SBD was evaluated statistically. Results show that AHA has higher and symmetrical estimation performance than other presented algorithms in determining the basic parameters of SBD with R2 = 0.999925806, MAE = 2.79065 × 10−7, RMSE = 7.49521 × 10−7, RE = 0.422088668, and STD = 7.68031 × 10−7 statistical values.