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    This study introduces a learning-assisted method for thin film characterization using multi-angle polarized microscopy. The technique efficiently measures film parameters with high resolution and speed, offering a cost-effective solution.

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    Area of Science:

    • Materials Science
    • Optical Physics
    • Nanotechnology

    Background:

    • Thin film characterization is crucial for semiconductor and nanodevice fabrication.
    • Accurate measurement of film parameters is essential for device performance.

    Purpose of the Study:

    • To develop a learning-assisted method for efficient thin film characterization.
    • To enable low-cost, high-resolution, and time-efficient measurement of film parameters.

    Main Methods:

    • Utilizing multi-angle polarized microscopy with a tightly focused vectorial beam.
    • Encoding angle-dependent reflection coefficients into reflected intensity distribution.
    • Transforming measurement into an optimization problem to minimize feature discrepancies.

    Main Results:

    • The proposed learning-assisted method was validated through numerical simulations and experimental measurements.
    • Demonstrated the ability to encode reflection coefficients into intensity distribution.
    • Achieved high spatial resolution and time efficiency in film parameter measurement.

    Conclusions:

    • The learning-assisted multi-angle polarized microscopy offers a cost-effective solution for thin film characterization.
    • The method is easily implementable with conventional microscopes.
    • Provides a valuable tool for the semiconductor industry and nanodevice fabrication.