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Rough surface effect in terahertz near-field microscopy: 3D simulation analysis.

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    Applied Optics
    |September 14, 2023
    PubMed
    Summary
    This summary is machine-generated.

    Terahertz scattering-type scanning near-field optical microscopy (THz-s-SNOM) imaging is affected by surface roughness. This study introduces a 3D model to analyze how sample morphology influences THz-s-SNOM signals, revealing insights into scattering effects.

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    Area of Science:

    • Physics
    • Materials Science
    • Nanotechnology

    Background:

    • Terahertz scattering-type scanning near-field optical microscopy (THz-s-SNOM) offers high-resolution imaging capabilities.
    • Existing models often simplify surfaces, neglecting realistic roughness from sample preparation.
    • Surface roughness significantly impacts the accuracy and interpretation of THz-s-SNOM data.

    Purpose of the Study:

    • To develop a novel 3D model for investigating the influence of sample morphology on THz-s-SNOM.
    • To analyze the effects of protrusions, depressions, and random roughness on scattered THz signals.
    • To understand the role of higher-order scattering in mitigating surface roughness effects in THz-s-SNOM.

    Main Methods:

    • Development of a novel 3D model combining the point dipole model and the finite element method.
    • Simulation of THz-s-SNOM signals scattered from surfaces with varying morphologies (protrusion, depression, random roughness).
    • Characterization of scattered signal variations based on different surface features.

    Main Results:

    • The study quantifies variations in scattered THz signals due to different sample morphologies.
    • Higher-order scattering phenomena were identified as crucial in reducing the impact of surface roughness.
    • The developed model accurately predicts signal changes influenced by surface topography.

    Conclusions:

    • Sample morphology, including surface roughness, critically affects THz-s-SNOM imaging outcomes.
    • The novel 3D model provides a robust framework for analyzing these morphological influences.
    • Understanding these effects is essential for accurate interpretation and application of THz-s-SNOM in materials characterization.