Design of highly sensitive guided-wave surface plasmon resonance biosensor with deep dip using genetic algorithm

In this paper, we presented a genetic algorithm (GA) based design method of highly sensitive guided-wave surface plasmon resonance (GWSPR) biosensor with deep dip. A constraint condition of reflectivity at resonance angle was used in a sensitivity based merit function (MF) of GA to achieve simultaneous optimization of sensitivity and depth of dip of GWSPR biosensor. Using the proposed method, we designed a GWSPR biosensor with Ag-TiO2-graphene hybrid structure at first, and compared its performance with a same structure based SPR biosensor but designed by conventional method (CM). The results indicated that the sensitivity of the GA designed GWSPR biosensor was nearly the same as the one of CM designed biosensor, but its reflectivity at resonance angle was much lower. In addition, GWSPR biosensors with different layers of graphene were also designed and analyzed. It was found that the optimal sensitivity of the proposed GWSPR biosensor decreased with increasing layers of graphene. Furthermore, the effect of target reflectivity at resonance angle on the design of GWSPR biosensor was also investigated. The proposed design method based on GA can be further applied to SPR biosensors with arbitrary multilayer structures, making it helpful for high-performance SPR sensors development.