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Characterisation of multi-layered structures using a vector-based gradient descent algorithm at terahertz

Amlan Kusum Mukherjee, Sven Wassmann, Konstantin Wenzel

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    This study introduces a novel gradient descent algorithm for terahertz material characterization. The method accurately extracts layer properties and enables high-resolution imaging of thin films.

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    Area of Science:

    • Physics
    • Materials Science
    • Engineering

    Background:

    • Terahertz (THz) radiation offers unique properties for material characterization and imaging.
    • Advancements in THz spectrometers and cameras are driving industrial applications.
    • Accurate material property extraction is crucial for THz-based analysis.

    Purpose of the Study:

    • To develop a novel, robust algorithm for analyzing THz spectroscopic data from multilayered materials.
    • To achieve precise extraction of layer thicknesses and refractive indices.
    • To demonstrate high-resolution imaging of nanoscale structures using THz radiation.

    Main Methods:

    • Implementation of a vector-based gradient descent algorithm.
    • Fitting measured transmission and reflection coefficients to a scattering parameter model.
    • Utilizing the algorithm without analytical error function formulation.

    Main Results:

    • Extraction of layer thicknesses and refractive indices with a maximum 2% error margin.
    • Successful imaging of a 50 nm-thick Siemens star using THz wavelengths (>300 µm).
    • Demonstration of the algorithm's ability to find error minima in analytically intractable optimization problems.

    Conclusions:

    • The developed vector-based gradient descent algorithm provides accurate material characterization in the terahertz domain.
    • This method enables precise thickness estimation for advanced imaging applications.
    • The algorithm's versatility extends beyond terahertz applications for complex optimization problems.