Robust Parameter Estimation of Organic Thin-Film Transistor Models Using Multi-Objective Portia Spider Optimization

Abstract

The increasing need for flexible and cost-effective electronic devices has highlighted the significance of the accuracy in modeling organic thin-film transistors for effective circuit design. Conventional parameter extraction techniques have been found inadequate in modeling these devices effectively, especially when variations in the channel length and carrier mobility occur. To overcome the challenges faced by the current parameter extraction technique in accurately estimating the parameters, this paper proposes a novel parameter extraction technique based on the multi-objective portia spider optimization algorithm for modeling organic thin-film transistors. To make sure that the simulated data match experimental results, this technique involves the utilization of experimental mobility in the multi-objective optimization process. The efficacy of the proposed algorithm be assessed by applying the method to extract the parameters of both P-type and N-type organic thin-film transistors with different channel lengths. From the obtained outcomes, it is evident that the suggested methodology offers a solution that ensures reduced normalized root-mean-square error with better estimation of the threshold voltage than other methods. The approach also guarantees consistent performance regardless of the variations in the device settings. Thus, the proposed approach offers a feasible option for the extraction of parameters in organic thin-film transistors.