Boosted Graphene/SiC MSM Photodetector Performance Using Genetic Algorithm Approach and Embedded Plasmonic Nanoparticles

Abstract

AbstractIn this work, we investigate systematically the benefits of incorporating random metallic nanoparticles in 4H-SiC thin film active area of an MSM photodetector. Several candidates (Al, Cr, Cu, Ni, W, Ti, Be, Pd, Pt) are examined to find the suitable metal nanoparticles that improve the sensing capability of 4H-SiC based UV photodetector. An effective dielectric approach based on the Maxwell–Garnet hypothesis is utilized to evade the intricacy of considering all random nanoparticles. 4H-SiC MSM UV photodetector with graphene electrodes and embedded titanium nanoparticles displays the maximum figures of merit, in terms of responsivity (683), PDCR (4.5 × 106), time response (13.45 µs) and detectivity of (1.56 × 1014 Jones). Besides, the developed model constitutes a fitness function for multi objective genetic algorithm optimization approach in order to optimize the device optical performance. The optimized design using Ti nanoparticles surpasses the conventional design in terms of speed and sensitivity, this fact renders our strategy very efficient for such problem.KeywordsPlasmonicsGraphene electrodes4H-SiC photodetectorLight trapping