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Related Experiment Video

Updated: Apr 3, 2026

Patterning via Optical Saturable Transitions - Fabrication and Characterization
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Modified sequential algorithm for the on-line characterization of optical coatings.

A V Tikhonravov, A Gorokh

    Optics Express
    |September 15, 2015
    PubMed
    Summary

    A new algorithm refines optical monitoring for thin film deposition. It improves accuracy by recalculating previous layer thicknesses during coating production, enhancing real-time quality control.

    Area of Science:

    • Materials Science
    • Optical Engineering
    • Thin Film Technology

    Background:

    • Accurate determination of deposited layer thicknesses is crucial for thin film coating production.
    • Existing sequential algorithms have limitations in real-time precision.
    • Broadband optical monitoring is a standard technique in coating processes.

    Purpose of the Study:

    • To introduce a novel algorithm for on-line thickness determination in thin film deposition.
    • To enhance the accuracy of real-time thickness measurements during coating production.
    • To improve upon the capabilities of traditional sequential algorithms.

    Main Methods:

    • Modification of the sequential algorithm for on-line thickness determination.
    • Incorporation of analytical estimations for recalculating layer thicknesses.

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  • Utilizing broadband optical monitoring data for real-time analysis.

    • Main Results:

    • The new algorithm allows for the recalculation of previously deposited layer thicknesses.
    • It identifies and refines thicknesses that can be determined with improved accuracy.
    • Simulations and experimental manufacturing confirm the algorithm's high accuracy.

    Conclusions:

    • The proposed algorithm offers enhanced precision for on-line thickness determination in thin film coatings.
    • It represents a significant improvement over existing methods for real-time monitoring.
    • The algorithm is validated for practical application in coating manufacturing.