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Modeling of highly improved SPR sensor for formalin detection

  • Md Moznuzzaman*
  • , Md Rafiqul Islam
  • , Md Biplob Hossain
  • , Ibrahim Mustafa Mehedi
  • *Corresponding author for this work
  • Khulna University of Engineering and Technology
  • Jashore University of Science and Technology
  • Electrical and Computer Engineering (ECE)
  • King Abdulaziz University
  • Center of Excellence in Intelligent Engineering Systems (CEIES)

Research output: Contribution to journalArticlepeer-review

73 Citations (Scopus)

Abstract

Consumption of formalin with food is a worldwide concern and has become a serious social problem in recent years, especially in the developing societies, which are at a higher risk of danger because of the lack of satisfactory monitoring and policies. The Frequent consumption of formalin causes severe health issues that lead to critical and fatal diseases like chronic cancer. Formalin detection in food is an urgent concern, which is becoming a national issue in developing countries. In this article, a graphene-MoS2 composite 2D sheets with a TiO2-SiO2 nano-layered surface plasmon resonance (SPR) based sensor is presented for formalin detection. Analytical analysis is carried out on the performance parameters of the sensor using MATLAB commercial software. The effect of amalgamation of Graphene-MoS2 with TiO2-SiO2 layers has been studied. The sensitivity and quality factor of the sensor are found to be 98 deg. RIU−1 and 88.89 RIU−1, respectively. This sensor detects the existence of formalin by using attenuated total reflection (ATR) and evaluating the reflectance vs SPR angle and transmittance vs surface plasmon resonance frequency (SPRF) attributes. It is found that, the sensitivity of the traditional SPR based sensor is 70°/RIU, on the other hand, the graphene-MoS2 based sensor improves this sensitivity to 76°/RIU. Finally, a comparative performance study of the traditional SPR sensors and the proposed sensor is also presented.

Original languageEnglish
Article number102874
JournalResults in Physics
Volume16
DOIs
Publication statusPublished - Mar 2020
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Formalin
  • Numerical modelling
  • Quality factor
  • Sensitivity
  • Sensor
  • Surface plasmon resonance

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