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Heavy metals biosensor based on defective one-dimensional phononic crystals.

Z A Alrowaili1, Hamza Makhlouf Fathy2, Hussein A Elsayed2

  • 1Physics Department, College of Science, Jouf University, P.O. Box 2014, Sakaka, Saudi Arabia.

Ultrasonics
|January 13, 2023
PubMed
Summary

This study introduces a novel sensor using one-dimensional phononic crystals (1D-PnCs) for highly sensitive heavy metal detection in freshwater. The proposed sensor effectively detects cadmium chloride (CdCl2) pollution with remarkable sensitivity.

Keywords:
Acoustic wavesCadmium chloride (CdCl(2))Heavy metalsPhononic band gapPhononic crystalsSensitivitySensorTransmission coefficient

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Area of Science:

  • Materials Science
  • Acoustics
  • Environmental Science

Background:

  • Heavy metal water pollution poses a significant threat to human health and ecosystems.
  • Accurate and sensitive detection methods for heavy metals are crucial for environmental monitoring.
  • Existing detection techniques may lack the sensitivity required for low-level pollutant identification.

Purpose of the Study:

  • To develop a novel theoretical approach for highly sensitive heavy metal detection in freshwater.
  • To investigate the use of one-dimensional phononic crystals (1D-PnCs) with a defect layer as a sensor platform.
  • To demonstrate the sensor's capability in detecting cadmium chloride (CdCl2) concentrations.

Main Methods:

  • Utilizing one-dimensional phononic crystals (1D-PnCs) with a central defect layer.
  • Employing the 2x2 transfer matrix method to analyze acoustic properties.
  • Optimizing sensor parameters for enhanced performance and sensitivity.

Main Results:

  • A resonant peak in the transmittance spectrum was observed, sensitive to CdCl2 concentration changes.
  • The proposed sensor demonstrated high sensitivity (S = 1904.25 Hz/ppm) over a wide concentration range (0-10000 ppm).
  • Achieved a high quality factor (QF) of 1771.318 and a figure of merit of 7.35 x 10^-5 ppm^-1.

Conclusions:

  • The developed 1D-PnC sensor offers a promising platform for detecting low concentrations of heavy metal ions in freshwater.
  • The theoretical framework and optimized parameters provide a foundation for practical environmental monitoring tools.
  • This approach contributes to advancements in sensor technology for water quality assessment.