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Related Experiment Video

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Replacing libraries in scatterometry.

Jonas Skovlund Møller Madsen, Søren Alkærsig Jensen, Jesper Nygård

    Optics Express
    |January 18, 2019
    PubMed
    Summary

    This study introduces new models to detect defects in diffraction gratings, improving performance in optics and sensing. A semi-analytical model and neural network efficiently identify grating defects without time-consuming library searches.

    Area of Science:

    • Optics and Photonics
    • Materials Science
    • Computational Science

    Background:

    • Diffraction gratings are crucial components in various applications, including optics, sensing, and diagnostics.
    • Performance degradation in diffraction gratings can be caused by scattering effects from surface and interface defects.
    • Accurate characterization of these defects is essential for maintaining grating functionality.

    Purpose of the Study:

    • To develop and validate novel methods for modeling and reconstructing defects in diffraction gratings.
    • To investigate three distinct classes of defects: two at the grating/air interface and one at the grating/substrate interface.
    • To offer a more efficient alternative to traditional scatterometry techniques for defect analysis.

    Main Methods:

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  • Rigorous Coupled Wave Analysis (RCWA) was employed to model grating scattering properties.
  • A new semi-analytical model was developed to approximate defect behavior.
  • A neural network approach was utilized for defect reconstruction, particularly for complex defect types.

    • Main Results:

    • Two defect classes were effectively characterized using the semi-analytical model.
    • The third defect class, a sinusoidal variation at the grating/substrate interface, was accurately reconstructed by the neural network.
    • The neural network demonstrated superior speed and versatility compared to conventional library search methods in scatterometry.

    Conclusions:

    • The developed semi-analytical model and neural network provide efficient and accurate methods for analyzing diffraction grating defects.
    • These novel approaches overcome the limitations of time-consuming library generation and search strategies.
    • The findings enable improved grating reconstruction, especially for challenging short-pitch gratings, enhancing their reliability in critical applications.