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Multi-objective optimization framework for designing photonic crystal sensors.

Mohammad Javad Safdari, Seyed Mohammad Mirjalili, Pablo Bianucci

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    This summary is machine-generated.

    This study introduces an automated framework for designing photonic crystal (PhC) sensors, eliminating the need for manual input. The novel approach efficiently optimizes sensor parameters for diverse applications.

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    Area of Science:

    • Photonics
    • Sensor Technology
    • Materials Science

    Background:

    • Designing complex photonic crystal (PhC) structures lacks analytical methods.
    • Manual design processes are time-consuming and may not yield optimal results.

    Purpose of the Study:

    • To propose a novel, automated framework for designing optimized PhC sensors.
    • To enable the automatic determination of optimal structural parameters without human intervention.

    Main Methods:

    • Development of a comprehensive framework for PhC sensor design.
    • Utilization of multi-objective optimization algorithms, exemplified by the gray wolf optimizer.
    • Application of the framework to design a PhC liquid sensor.

    Main Results:

    • The framework successfully designs various types of PhC sensors.
    • A wide range of optimal designs suitable for general and specific applications were identified.
    • Demonstrated the framework's capability in optimizing PhC liquid sensor parameters.

    Conclusions:

    • The proposed framework offers a simple, straightforward, and automated solution for PhC sensor design.
    • It significantly broadens the scope of achievable optimal sensor designs.
    • The framework is adaptable for any PhC sensor design task.