Enhanced Sensitivity in Optical Sensors through Self-Image Theory and Graphene Oxide Coating

Area of Science:

• Optical Sensing
• Biomedical Engineering
• Materials Science

Background:

• Accurate glucose monitoring is crucial for diabetes management.
• Existing optical sensors often lack sufficient sensitivity for real-world applications.
• Graphene oxide offers unique optical and material properties for sensor enhancement.

Purpose of the Study:

• To develop a highly sensitive optical sensor for quantitative glucose detection.
• To leverage self-image theory and graphene oxide coating for improved sensor performance.
• To validate the sensor's efficacy in measuring glucose concentrations relevant to human saliva.

Main Methods:

• Theoretical validation of self-image points using Multiphysics COMSOL 6.0 software.
• Fabrication of an optical sensor based on the second self-image point (29.12 mm).
• Coating the sensor with graphene oxide film (80 µm/mL) via the Layer-by-Layer technique.

Main Results:

• Achieved a wavelength sensitivity of 200 ± 6 nm/RIU for refractive index characterization.
• Demonstrated an eightfold increase in sensitivity for glucose detection compared to uncoated sensors.
• The final graphene oxide-based sensor exhibited a sensitivity of 10.403 ± 0.004 pm/(mg/dL).

Conclusions:

• The integrated approach of self-image theory and graphene oxide coating significantly enhances optical sensor sensitivity.
• The developed sensor provides stable and precise quantitative measurements of glucose concentrations.
• This technology holds potential for non-invasive glucose monitoring applications.