Synergistic optimization strategy for high-performance multilayer SPR biosensor

Area of Science:

• Nanotechnology
• Biosensing
• Materials Science

Background:

• Surface Plasmon Resonance (SPR) biosensors are crucial for label-free biomolecular detection but struggle with low-molecular-weight analytes like urinary glucose.
• Conventional SPR sensor designs are often empirically guided, limiting optimization and overall device performance.

Purpose of the Study:

• To develop a high-sensitivity SPR biosensor utilizing a ZnO/Au/Ag/Si/WSe2 multilayer structure for improved glucose detection.
• To optimize the multilayer structure using a genetic algorithm for enhanced refractive index sensitivity and biomolecule adsorption.

Main Methods:

• Proposed a novel multilayered ZnO/Au/Ag/Si/WSe2 configuration for SPR biosensing.
• Employed a genetic algorithm-based multi-objective optimization to fine-tune layer thicknesses, focusing on sensitivity, Figure of Merit (FOM), and resonance peak depth.
• Simulated sensor performance for detecting urinary glucose across various concentrations.

Main Results:

• The optimized sensor achieved a sensitivity of 362.96 °/RIU, FOM of 60.00 RIU⁻¹, and DFOM of 33.28 RIU⁻¹, significantly outperforming traditional Cr/Au sensors.
• For urinary glucose samples, the sensor demonstrated a maximum sensitivity of 284.85 °/RIU, FOM of 60.10 RIU⁻¹, and DFOM of 42.15 RIU⁻¹.
• The multilayer design effectively enhances both refractive index sensitivity and biomolecule adsorption efficiency.

Conclusions:

• The proposed ZnO/Au/Ag/Si/WSe2 SPR biosensor offers a significant advancement in sensitivity and performance for glucose detection.
• This high-performance biosensor holds considerable potential for noninvasive applications in diabetes diagnosis, early cancer screening, food safety, and environmental monitoring.