Metaheuristic-based decision maker framework for the development of multispectral IGZO thin-film phototransistors

Abstract

A new multispectral InGaZnO (IGZO) thin-film phototransistor (TF PT) based on a graded band-gap (GBG) SiGe capping layer with metallic nanoparticles (MNPs) is proposed. An accurate drain-current model is developed to investigate the device performances, where the optical characteristics under different light excitations (530 nm, 820 nm, and 1550 nm) are analyzed using the 3-D Finite-difference time-domain method (FDTD). It is found that the proposed device shows high photoresponse characteristics. Besides, it is revealed that the GBG configuration, MNPs spatial distribution and size can induce a complex behavior, which influences the device photoresponse over multiple spectral bands. Importantly, an iterative decision-maker framework based on the Multi-Objective Genetic Algorithm (MOGA) metaheuristic approach is implemented to design efficient multispectral IGZO TF PT. It is demonstrated that the proposed MOGA-based scheme paves the way for the designer to identify the appropriate GBG profile and MNPs spatial distribution for highly-responsive devices at selective Visible and IR wavelengths and to realize high-performance multispectral sensors. The proposed approach based on combining the proposed IGZO TF PT structure with MOGA metaheuristic computation opens up a new strategy for the design and experimental fabrication of high-performance multispectral optoelectronic devices.