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Sensitivity Improvement of Surface Plasmon Resonance Sensor for Glucose Detection in Urine Samples Using Heterogeneous Layers: An Analytical Perspective

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Abstract

A surface plasmon resonance sensor has been proposed in this study. The proposed sensor can detect glucose concentration in the urine samples and can detect a concentration of 0.15 mg/dL. Kretschmann configuration has been modified by adding the dielectric material layer between the prism and metals layer. MXene, ZnO, and graphene have been placed between a prism and bimetallic Ag layer. The sensor's performance depends on the thickness of the layers. The layer's thickness has also been optimized to obtain the minimum reflectance. The optimized thickness of the first and second Ag layers is 35 nm and 7 nm, respectively. The thickness of the monolayer of MXene, ZnO, and graphene has been taken as 0.993 nm, 2 nm, and 0.34 nm, respectively. The characteristics parameters are also computed and obtained highest at the concentration of 10 g/dL. The maximum sensitivity of 184 Degree/RIU with values of detection accuracy (DA), full width at half maximum (FWHM), and quality factor as 0.148 Degree−1, 6.756 Degree, and 27.23 RIU−1 has been obtained.

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BK formulated the problem statement, giving the theoretical background and mathematical modeling for the SPR biosensor. He also helped in drafting and finalizing the manuscript. AU provided the theoretical background to biosensing and the importance of Optical Biosensing. He also helped in finalizing the design of the proposed sensor. PS worked towards the complete manuscript, formatting, and finalizing the manuscript. AP provided statistical analysis for the results. He provided the theoretical background to SPR biosensors. He also helped in formatting the manuscript. RBY worked towards revising the manuscript and formatting design and finalization towards developing this work.

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Correspondence to Bhishma Karki.

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Karki, B., Uniyal, A., Sarkar, P. et al. Sensitivity Improvement of Surface Plasmon Resonance Sensor for Glucose Detection in Urine Samples Using Heterogeneous Layers: An Analytical Perspective. J Opt (2023). https://doi.org/10.1007/s12596-023-01418-0

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