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<p>Chikungunya is an RNA virus transmitted through mosquito bites, leading to symptoms such as fever, joint swelling, discomfort, and muscle soreness. This article proposes a surface plasmon resonance (SPR)-based biosensor for chikungunya virus detection, utilizing the Kretschmann configuration. The sensor’s structure includes a BK7 prism, silver (Ag), and dual layers of aluminum oxide nitride (AION). The proposed sensor is used for analyte detection by investigating refractive index (RI) changes. Numerical analysis of the proposed sensor’s reflectivity is conducted using the transfer matrix method (TMM). Optimal sensor parameters show maximum sensitivity for platelets and plasma cells of 438 °/RIU and 321 °/RIU, respectively, with figures of merit (FOM) of 143 RIU<sup>−1</sup> and 188 RIU<sup>−1</sup>, detection accuracy (DA) of 0.33 /°and 0.58 /°, and signal-to-noise ratio (SNR) of 1.43 and 1.88. Sensitivity enhancement is explored by varying the number and thickness of layers. The sensor performance is justified by finite element method (FEM) based COMSOL software. The sensor’s high sensitivity and stability make it potentially useful for biomedical applications.</p>

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Sensitivity Enhancement of Plasmonic Sensor Using Dual Aluminum Oxide Nitride Layers for Chikungunya Virus Detection: A Numerical Analysis

  • 期刊论文

  • 发表日期：

    2025年1月23日

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  • Hussein S. Gumaih,
  • Md. Aslam Mollah,
  • Yousif S. Adam,
  • Abdulkarem H. M. Almawgani

摘要

Chikungunya is an RNA virus transmitted through mosquito bites, leading to symptoms such as fever, joint swelling, discomfort, and muscle soreness. This article proposes a surface plasmon resonance (SPR)-based biosensor for chikungunya virus detection, utilizing the Kretschmann configuration. The sensor’s structure includes a BK7 prism, silver (Ag), and dual layers of aluminum oxide nitride (AION). The proposed sensor is used for analyte detection by investigating refractive index (RI) changes. Numerical analysis of the proposed sensor’s reflectivity is conducted using the transfer matrix method (TMM). Optimal sensor parameters show maximum sensitivity for platelets and plasma cells of 438 °/RIU and 321 °/RIU, respectively, with figures of merit (FOM) of 143 RIU−1 and 188 RIU−1, detection accuracy (DA) of 0.33 /°and 0.58 /°, and signal-to-noise ratio (SNR) of 1.43 and 1.88. Sensitivity enhancement is explored by varying the number and thickness of layers. The sensor performance is justified by finite element method (FEM) based COMSOL software. The sensor’s high sensitivity and stability make it potentially useful for biomedical applications.