Multi-layer SPR biosensor for in-Situ Amplified monitoring of the SARS-CoV-2 omicron (B.1.1.529) variant

This article represents an analysis of the performance of multi-layer surface plasmon resonance (SPR) biosensors in detecting the transferable human SARS-CoV-2 Omicron (B.1.1.529) variant. The proposed multi-layer SPR biosensor performance is enhanced by integrating fine-tuning prisms, plasmonic met...

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Bibliographic Details
Published inBiosensors and bioelectronics. X Vol. 16; p. 100434
Main Authors Akib, Tarik Bin Abdul, Rana, Md Masud, Mehedi, Ibrahim M.
Format Journal Article
LanguageEnglish
Published Elsevier 01.02.2024
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ISSN2590-1370
2590-1370
DOI10.1016/j.biosx.2023.100434

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Summary:This article represents an analysis of the performance of multi-layer surface plasmon resonance (SPR) biosensors in detecting the transferable human SARS-CoV-2 Omicron (B.1.1.529) variant. The proposed multi-layer SPR biosensor performance is enhanced by integrating fine-tuning prisms, plasmonic metals, and two-dimensional (2D) transition metal dichalcogenides (TMDs) materials. To evaluate the performance of the multi-layer SPR sensor, the transfer matrix method (TMM) is employed. In numerical result, the proposed (CaF2/Cu/BP/Graphene) structure demonstrates the most favorable sensitivity and detection accuracy, characterized by a 410° angle shift sensitivity/refractive index unit (RIU). Additionally, the sensor achieves a detection accuracy (DA) of 0.4713, a quality factor (QF) of 94.25 RIU−1, a figure of merit (FOM) of 91.87, and a combined sensitivity factor (CSF) of 90.36. The presented sensor is also capable of detecting target biomolecule binding interactions between ligands and analytes at a range of concentrations (from 0 nM to 1000 nM), implying its potential use for detecting the omicron virus strain. The outcomes highlight the effectiveness of the presented sensor for real time, and label free detection, particularly in identifying the Omicron viral strain. Eventually, this research promises advanced biosensor technology, crucial for rapid viral variant detection and diagnostics.
ISSN:2590-1370
2590-1370
DOI:10.1016/j.biosx.2023.100434