journal article·2024-11-19Open access

An Optimized Graphene-Based Surface Plasmon Resonance Biosensor for Detecting SARS-CoV-2

Talia Tene, Fabian Arias Arias, Karina I. Paredes-Páliz, Camilo Haro-Barroso, Cristian Vacacela Gomez

Applied Sciences· Volume 14· Issue 22

Abstract

Graphene-enhanced surface plasmon resonance (SPR) biosensors offer promising advancements in viral detection, particularly for SARS-CoV-2. This study presents the design and optimization of a multilayer SPR biosensor incorporating silver, silicon nitride, single-layer graphene, and thiol-tethered ssDNA to achieve high sensitivity and specificity. Key metrics, including SPR angle shift (Δθ), sensitivity (S), detection accuracy (DA), and figure of merit (FoM), were assessed across SARS-CoV-2 concentrations from 150 to 525 mM. The optimized biosensor achieved a sensitivity of 315.91°/RIU at 275 mM and a maximum Δθ of 4.2° at 400 mM, demonstrating strong responsiveness to virus binding. The sensor maintained optimal accuracy and figure of merit at lower concentrations, with a linear sensitivity response up to 400 mM, after which surface saturation limited further responsiveness. These results highlight the suitability of the optimized biosensor for real-time, point-of-care SARS-CoV-2 detection, particularly at low viral loads, supporting its potential in early diagnostics and epidemiological monitoring.
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Research context

OpenAlex topics: SARS-CoV-2 detection and testing · Advanced biosensing and bioanalysis techniques · SARS-CoV-2 and COVID-19 Research

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Chemistry, Universidad Técnica Particular de Loja, Loja 110160, Ecuador

Facultad de Ciencias, Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba 060155, Ecuador

Dipartimento di Chimica e Tecnologie Chimiche, University of Calabria, Via P. Bucci, Cubo 15D, 87036 Rende, Italy

Grupo de Investigación en Salud Pública, Facultad de Ciencias de la Salud, Universidad Nacional de Chimborazo, Riobamba 060108, Ecuador

INFN-Laboratori Nazionali di Frascati, Via E. Fermi 54, 00044 Frascati, Italy

Funding

Universidad Técnica Particular de Loja · LNF-INFN: Progetto HPSWFOOD Regione Lazio

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