Photonic Crystal Fiber Pollution Sensor based on Surface Plasmon Resonance

Authors

  • Fatima Fadhil Abbas Department of Physical, College of Science, University of Baghdad, Baghdad, Iraq https://orcid.org/0000-0003-4578-1819
  • Soudad S. Ahmed Department of Physical, College of Science, University of Baghdad, Baghdad, Iraq

DOI:

https://doi.org/10.24996/ijs.2023.64.2.15

Keywords:

Photonic crystal fiber sensor, Pollution sensor, Optical fiber sensor based surface plasmon resonance, Surface plasmon resonance

Abstract

       In this work, a pollution-sensitive Photonic Crystal Fiber (PCF) based on Surface Plasmon Resonance (SPR) technology is designed and implemented for sensing refractive indices and concentrations of polluted  water . The overall construction of the sensor is achieved by splicing short lengths of PCF (ESM-12) solid core on one side with traditional multimode fiber (MMF) and depositing a gold nanofilm of 50nm thickness on the end of the PCF sensor. The PCF- SPR experiment was carried out with various samples of polluted water including(distilled water, draining water, dirty pond water, chemical water, salty  water and oiled water). The location of the resonant wavelength peaks is seen to move to longer wavelengths (red shift) as the refractive index increases due to the transfer of maximum energy from the reflected power of the light guided through the fiber to the surface plasmons. The experimental results show that the highest sensitivity reached 4202.6nm/RIU for oiled water, the signal to noise ratio was 0.625, the resolution was 2.4*10-5 RIU, and the figure of merit was 22.8. The prepared sensor exhibited excellent performance features, making it an excellent element for detecting water pollutants.

Downloads

Published

2023-02-28

Issue

Section

Physics

How to Cite

Photonic Crystal Fiber Pollution Sensor based on Surface Plasmon Resonance. (2023). Iraqi Journal of Science, 64(2), 658-667. https://doi.org/10.24996/ijs.2023.64.2.15

Similar Articles

1-10 of 1361

You may also start an advanced similarity search for this article.