Design of a plasmonic optical biosensor based on a metal-insulator-metal ring resonator for the detection of various bacterial pathogens

Abstract

Rapid and sensitive detection of pathogenic bacteria is essential for healthcare, food safety, and environmental monitoring. However, conventional detection techniques often fall short in terms of the speed and sensitivity required for real-time applications. In this study, we propose a label-free plasmonic optical biosensor based on a metal-insulator-metal (MIM) dual-ring resonator structure for the efficient detection of bacterial species. The sensor geometry was optimized using Particle Swarm Optimization (PSO) and evaluated through three-dimensional finite-difference time-domain (3D-FDTD) simulations to enhance both sensitivity and figure of merit (FOM). Gold nanorings integrated with a gold back reflector were employed due to their superior plasmonic resonance characteristics. The optimized design achieved a sensitivity of 324.76 nm·RIU^-1, a FOM of 10.187 RIU^-1, and a detection limit (LoD) of 0.075 RIU. The biosensor maintained high performance under varying operational conditions, including temperature (0-500 K), incident angle (0°-50°), and polarization states. Strong field confinement in the dielectric gap significantly enhanced the interaction between light and the analyte. The device demonstrated the ability to detect and differentiate between Vibrio cholerae (n = 1.365), Escherichia coli (n = 1.388), and Pseudomonas species (n = 1.437-1.526), highlighting its potential for quantitative bacterial identification. By addressing key limitations in sensitivity and specificity in complex biological environments, this MIM-based sensor offers a robust platform for rapid, high-throughput bacterial detection in clinical diagnostics and beyond.

Keywords: Bacteria; MIM resonator rings; Optical biosensor; Sensitivity.

Fig. 1

Schematic of the designed MIM structure as a plasmonic biosensor(LibreOffice version 25.2.3 (URL: https://www.libreoffice.org/download/download-libreoffice/) and GIMP version 3.0.4 (URL: https://www.gimp.org/)).

Fig. 2

PSO optimization results (a) reflectance spectra for different back reflector thicknesses, (b) reflectance spectra for different dielectric layer thicknesses, (c) reflectance spectra for different nanoring thicknesses, and (d) reflectance spectra for different sensing medium thicknesses.

Fig. 3

PSO optimization results. (a) Sensitivity and FOM for different back reflector thicknesses, (b) sensitivity and FOM for different dielectric layer thicknesses, (c) sensitivity and FOM for different nanoring thicknesses, and (d) Sensitivity and FOM for different sensing medium thicknesses.

Fig. 4

(a) Reflectance spectra with different back reflector materials and (b) reflectance spectra with different nanoring materials.

Fig. 5

(a) Reflectance spectra at different temperatures, (b) reflectance spectra at different incident angles and (c) reflectance spectra for TE and TM polarization modes.

Fig. 6

(a) Electric field distribution in the XY-plane and (b) electric field distribution in the XZ-plane.

Fig. 7

(a) Reflectance spectra of the structure and detection of Vibrio cholera bacteria at n = 1.365 (red curve), E. coli bacteria at n = 1.388 (blue curve), Pseudomonas bacteria at n = 1.437, 1.493 and 1.526 (violet-green and turquoise curves) and (b) changes in resonance wavelength versus changes in the refractive index of the sensor’s sensing medium in the presence of different bacteria as a curve fit.