Numerical Analysis of a Highly Sensitive Surface Plasmon Resonance Sensor for SARS-CoV-2 Detection

Area of Science:

• Optoelectronics
• Biosensing
• Nanotechnology

Background:

• Accurate and rapid detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial for pandemic control.
• Surface plasmon resonance (SPR) biosensors offer label-free and real-time detection capabilities.
• Enhancing SPR sensor performance is key to improving diagnostic sensitivity and specificity.

Purpose of the Study:

• To propose and numerically analyze a novel SPR sensor architecture for enhanced SARS-CoV-2 detection.
• To investigate the sensor's performance using silicon and BaTiO3 layers on an Ag substrate.
• To evaluate the sensor's sensitivity, figure-of-merit, and applicability for various biomolecular interactions.

Main Methods:

• Numerical simulations using transfer matrix theory and finite-difference time-domain (FDTD) methods.
• Design of an SPR structure based on Kretschmann configuration with integrated silicon and BaTiO3 layers.
• Characterization of sensor response, including sensitivity, full width at half maxima, and minimum reflection.

Main Results:

• Achieved a 7.6-fold enhancement in sensitivity for SARS-CoV-2 detection compared to the basic Kretschmann configuration.
• Demonstrated consistent performance enhancement for both angular and wavelength interrogations.
• Obtained a high figure-of-merit (FOM) of 692.28, indicating superior sensing performance.
• Validated robust performance improvements across various ligate-ligand pairs.

Conclusions:

• The proposed SPR sensor design offers a highly sensitive and rapid biosensing platform.
• The integration of silicon and BaTiO3 layers significantly boosts SPR sensor performance.
• This architecture holds promise for noninvasive biosensing and can be adopted for experimental protocols.