A Multi-Objective Optimization of 2D Materials Modified Surface Plasmon Resonance (SPR) Based Sensors: An NSGA II Approach

Modifying the structure of surface plasmon resonance based sensors by adding 2D materials has been proven to considerably enhance sensor’s sensitivity in comparison a traditional three layer configuration. Moreover, thin semiconductor film placed on top metallic and stacked together with enhances even more sensitivity, but at cost worsening plasmonic couplic strength (minimum level reflectivity) broadening response. With each supplementary added, complexity optimizing performance increases due extended parameter space sensor. This study focused overcoming these difficulties design process employing multi-objective genetic algorithm (NSGA II) alongside transfer matrix method (TMM) and, same time, full width half maximum (FWHM), reflectivity for four sensor structure. Firstly, semiconductor’s refractive index was optimized obtain achievable narrow FWHM almost zero. Secondly, it shown that indices barium titanate (BaTiO3) silicon (Si) are closest optimal silver—graphene/WS2 MoS2 modified structures, respectively. Sensitivities up 302 deg/RIU were achieved Ag–BaTIO3–graphene/WS2 configurations an smaller than 8 deg less 0.5% resonance.