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Genetic algorithm for ellipsometric data inversion of absorbing layers.

G Cormier1, R Boudreau

  • 1Ecole de génie, Université de Moncton, Nouveau-Brunswick, Canada.

Journal of the Optical Society of America. A, Optics, Image Science, and Vision
|January 21, 2000
PubMed
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A novel genetic algorithm effectively reduces data for single-wavelength ellipsometry. This method accurately models single absorbing layers on substrates, offering a versatile approach for optical characterization.

Area of Science:

  • Materials Science
  • Optical Physics
  • Computational Methods

Background:

  • Ellipsometry is a powerful optical technique for characterizing thin films.
  • Data analysis in ellipsometry often requires robust inversion methods.
  • Single-wavelength ellipsometry simplifies measurements but demands efficient data reduction.

Purpose of the Study:

  • To introduce a new data reduction method for single-wavelength ellipsometry.
  • To apply a genetic algorithm for fitting ellipsometric data.
  • To evaluate the performance of the genetic algorithm for a specific sample structure.

Main Methods:

  • A genetic algorithm was employed to optimize the fit of ellipsometric data.
  • The sample model comprised a single absorbing layer on a semi-infinite substrate.

Related Experiment Videos

  • The algorithm was tested for convergence and applicability to various measurement scenarios.
  • Main Results:

    • The genetic algorithm demonstrated good convergence properties.
    • The method successfully determined the optical properties of the absorbing layer.
    • Results were comparable to those obtained using established inversion techniques.

    Conclusions:

    • Genetic algorithms provide an effective and versatile approach for single-wavelength ellipsometry data reduction.
    • This method is adaptable to complex measurement configurations and diverse sample types.
    • The technique offers a reliable alternative for optical thin-film analysis.