Optimization methodology for structural multiparameter surface plasmon resonance sensors in different modulation modes based on particle swarm optimization

One of the main challenges in designing plasmonic biosensors is maximizing their sensing performance. This study proposes heuristic algorithms based on surface plasmon resonance-particle swarm optimization (SPR-PSO), which were investigated for the optimization of the sensing performance of structural multiparameter SPR sensors in four modulation modes (phase, intensity, wavelength, and angle). Different fitness functions were designed for different modulation modes that comprised a variety of evaluation indicators (such as sensitivity, figure of merit, full-width-at-half-maximum, electric field intensity, and penetration depth). Four types of available experimental structures representing the various modulation schemes were compared with the corresponding optimized structure by algorithms. The results showed that the introduced algorithms have a considerable efficiency. Furthermore, the algorithms also showed some potential in aiding the parametric design of negative refractive index materials.