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<p>The current work examines the theoretical aspects of a very sensitive surface plasmon resonance sensor for detecting the chikungunya virus. Silver and zinc selenide are the only material layers comprising the sensing structure. They are deposited one on top of the other on the surface of the BK7 glass prism. For best sensing performance, the geometric characteristics of each layer are tuned. The chikungunya virus detection capacity of the proposed sensor structure is demonstrated by its results. The obtained simulated results give a high sensitivity of 384.7 degree/RIU with a detection accuracy of 0.471 degree<sup>−1</sup>, the figure of merit of 181.19 RIU<sup>−1</sup>. These parameters support our assertion that we have designed a high-performance-based sensor to identify the chikungunya virus in the blood sample. The results are simulated using MATLAB programming based on the transfer matrix method (TMM), and they are then examined further to assess the sensor’s performance.</p>

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Early Detection of Chikungunya Virus Using Silver and Zinc Selenide Multilayer Structure Utilizing the Surface Plasmon Resonance: A Numerical Approach

  • 期刊论文

  • 发表日期：

    2025年5月3日

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  • Gufranullah Ansari,
  • Rami Oweis,
  • Lalji Baldaniya,
  • Muna Barakat,
  • Renuka Jyothi S,
  • Irwanjot Kaur,
  • Shaker Al-Hasnaawei,
  • Laxmidhar Maharana,
  • Ashish Singh Chauhan,
  • Bilakshan Purohit,
  • Arun Uniyal

摘要

The current work examines the theoretical aspects of a very sensitive surface plasmon resonance sensor for detecting the chikungunya virus. Silver and zinc selenide are the only material layers comprising the sensing structure. They are deposited one on top of the other on the surface of the BK7 glass prism. For best sensing performance, the geometric characteristics of each layer are tuned. The chikungunya virus detection capacity of the proposed sensor structure is demonstrated by its results. The obtained simulated results give a high sensitivity of 384.7 degree/RIU with a detection accuracy of 0.471 degree−1, the figure of merit of 181.19 RIU−1. These parameters support our assertion that we have designed a high-performance-based sensor to identify the chikungunya virus in the blood sample. The results are simulated using MATLAB programming based on the transfer matrix method (TMM), and they are then examined further to assess the sensor’s performance.