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<p>We investigate a one-dimensional photonic crystal (1D-PhC) structure with a central defect layer designed for optical biosensing applications, particularly for algae detection. The structure consists of alternate layers of silicon dioxide (SiO<sub>2</sub>) and titanium dioxide (TiO<sub>2</sub>). A defect layer, representing the biological sample, is introduced at the center generating a confined defect mode within the PBG. Using the transfer matrix method, we explore the effects of structural parameters, including the number of unit cells, defect layer thickness, and angle of incidence, on the transmission spectra to optimize the structural parameter. Finally, the biosensor’s performance is evaluated by simulating various algae species as defect layers. It is to mention that Green algae offers a peak shift to 584.1477&#xa0;nm and FWHM of 0.060993&#xa0;nm with QF of 9577.32. Other species show similar tunability and further cause redshifts in the resonance wavelength. Distinct shifts in the resonance wavelength confirm the sensor’s high sensitivity and selectivity demonstrating the potential of the device as a robust, label-free platform for environmental biosensing. Hence, such new idea is based on the detection of the presence of Aquatic Algae in water that creates water pollution hazardous for human and animals and plants.</p>

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Light-based detection of aquatic algae using one-dimensional photonic crystals

  • 期刊论文

  • 发表日期：

    2025年9月12日

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  • Bhuvneshwer Suthar,
  • Abhilasha Choudhary,
  • Ravi Parihar,
  • Anami Bhargava

摘要

We investigate a one-dimensional photonic crystal (1D-PhC) structure with a central defect layer designed for optical biosensing applications, particularly for algae detection. The structure consists of alternate layers of silicon dioxide (SiO2) and titanium dioxide (TiO2). A defect layer, representing the biological sample, is introduced at the center generating a confined defect mode within the PBG. Using the transfer matrix method, we explore the effects of structural parameters, including the number of unit cells, defect layer thickness, and angle of incidence, on the transmission spectra to optimize the structural parameter. Finally, the biosensor’s performance is evaluated by simulating various algae species as defect layers. It is to mention that Green algae offers a peak shift to 584.1477 nm and FWHM of 0.060993 nm with QF of 9577.32. Other species show similar tunability and further cause redshifts in the resonance wavelength. Distinct shifts in the resonance wavelength confirm the sensor’s high sensitivity and selectivity demonstrating the potential of the device as a robust, label-free platform for environmental biosensing. Hence, such new idea is based on the detection of the presence of Aquatic Algae in water that creates water pollution hazardous for human and animals and plants.