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Surface sensing with integrated optical waveguides: a design guideline.

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    This study introduces a surface sensitivity metric for optimizing waveguide-based biochemical sensors. It provides design guidelines for silicon nitride and silicon-on-insulator platforms to maximize detection influence on the guided mode.

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    Area of Science:

    • Photonics and Sensor Technology
    • Biochemical Sensing
    • Materials Science

    Background:

    • Waveguide-based sensors detect molecules via surface binding.
    • Optimizing sensitivity requires maximizing the surface layer's influence on the guided mode's effective refractive index.
    • Common material platforms include silicon nitride and silicon-on-insulator (SOI).

    Purpose of the Study:

    • To define a surface sensitivity metric for quantifying the impact of surface binding on waveguide modes.
    • To systematically analyze and optimize various waveguide types (strip, slot, double slot, SWG) for enhanced sensitivity.
    • To provide universal design guidelines for selecting and optimizing waveguide platforms for biochemical sensing.

    Main Methods:

    • Development of a surface sensitivity metric.
    • Systematic analysis and optimization of silicon nitride and SOI waveguides.
    • Comparison of different waveguide designs including simple strips, slot, double slot, and sub-wavelength gratings (SWG).

    Main Results:

    • Quantification of surface sensitivity across different waveguide types and material platforms.
    • Identification of optimal waveguide designs for maximizing surface layer influence.
    • Establishment of universal design guidelines based on physical trends and limitations.

    Conclusions:

    • The defined surface sensitivity metric enables effective comparison of waveguide platforms.
    • Optimized waveguide designs, particularly slot and SWG structures, offer superior sensitivity.
    • Findings facilitate the selection of appropriate waveguide platforms and optimization for specific biochemical sensing tasks.