Silver, silicon, and selenium-based surface plasmon resonance sensor for pathogen bacteria detection in visible region

• Published in: Optical and quantum electronics Vol. 57; no. 3
• Main Authors: Uniyal, Arun, Kumar, Manoj, Kumar, Rajeev, Dhiman, Gaurav, Ansari, Gufranullah, Pal, Amrindra, Ahmed, Mohammad Z.
• Format: Journal Article
• Language: English
• Published: New York Springer US 12.03.2025; Springer Nature B.V
• Subjects: Characterization and Evaluation of Materials; Computer Communication Networks; Electrical Engineering; Figure of merit; Incident light; Lasers; Multilayers; Optical Devices; Optics; Pathogens; Photonics; Physics; Physics and Astronomy; Plasmons; Selenium; Sensitivity; Sensors; Silicon; Silver; Surface plasmon resonance; Pathogen detection; Sensitivity; Surface plasmon resonance; Selenium; Figure of merit
• ISSN: 1572-817X; 0306-8919; 1572-817X
• DOI: 10.1007/s11082-025-08118-y

The proposed study reported a numerical simulation of a surface plasmon resonance (SPR) sensor for pathogen detection using a layered structure that includes a prism, silver (Ag), silicon (Si), selenium (Se), and sensing medium. The materials are selected and arranged along the z-direction with maximum efficiency to improve the sensor’s sensitivity and accuracy. The Ag layer strengthens surface plasmon waves, and the SF11 prism makes it easier for incident light to be efficiently coupled to the plasmonic surface. Through improved performance over the propagation and confinement of the surface plasmons (SPs), the addition of Si and Se layers enhances overall performance. We could assess the sensor’s performance parameters by examining the SPR curves, which provide important details about the sensor’s sensitivity, resonance angle shift, and detection accuracy (DA). Our simulation results show that our multi-layered SPR sensor demonstrates exceptional sensitivity and specificity for pathogen detection, with a maximum sensitivity of 147.68 degree/RIU, a DA of 0.1290 degree −1 , and a figure of merit (FoM) of 19.035 RIU −1 , which makes it a valuable tool for early infectious illness diagnosis and analysis.