Surface plasmon resonance biosensors for SARS-CoV-2 sensing: The role of silicon nitride and graphene

We present a systematic optimization and analysis of SPR biosensors, focusing on the influence of design parameters such as silver (Ag), silicon nitride (Si₃N₄), graphene, and ssDNA layer thicknesses. Two configurations, Sys₃ and Sys₅, were developed and numerically evaluated under varying SARS-CoV-2 concentrations in PBS solution, ranging from 0.01 nM to 100 nM. Sys₃, optimized with Ag at 55 nm, Si₃N₄ at 13 nm, and ssDNA at 10 nm, demonstrated exceptional sensitivity (371.7°/RIU), low limit of detection, and high detection accuracy, making it suitable for precision applications. In contrast, Sys₅, incorporating a graphene layer (0.34 nm) alongside Ag at 50 nm, Si₃N₄ at 10 nm, and ssDNA at 10 nm, exhibited superior robustness and a higher figure of merit (2287.2 RIU⁻ 1 ), offering consistent performance across a broader dynamic range. These results highlight the versatility of SPR biosensors in adapting to diverse diagnostic needs. • The SPR biosensors achieve sensitivities of 371.67°/RIU (Sys₃) and 177.93°/RIU (Sys₅), evidencing exceptional performance in detecting refractive index changes associated with SARS-CoV-2. • The detection accuracy reaches values of 14.14 × 10 −2 RIU⁻ 1 for Sys₃ and 7.34 × 10 −2 RIU⁻ 1 for Sys₅, highlighting the biosensors' ability to resolve variations effectively. • The quality factor achieves a peak of 93.4 RIU⁻ 1 for Sys 3 at 0.01 nM, demonstrating the sharpness and reliability of the resonance curve for precise diagnostics.

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Publication Details

Journal
Biosensors and Bioelectronics X
Published
2025-01-29
DOI
https://doi.org/10.1016/j.biosx.2025.100586
Citations
11
Primary Topic
SARS-CoV-2 detection and testing
Type
article
Field-Weighted Citation Impact
15.36

Funders

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article

Surface plasmon resonance biosensors for SARS-CoV-2 sensing: The role of silicon nitride and graphene

Cristian Vacacela Gómez, Stefano Bellucci, Talía Tene, Fabián Londo et al.
11 citations
Biosensors and Bioelectronics X
SARS-CoV-2 detection and testing
15.36
article

Surface plasmon resonance biosensors for SARS-CoV-2 sensing: The role of silicon nitride and graphene

Cristian Vacacela Gómez, Stefano Bellucci, Talía Tene, Fabián Londo, Myrian Borja, Diana Coello-Fiallos, Narcisa Sánchez
article en
11 citations

Abstract

We present a systematic optimization and analysis of SPR biosensors, focusing on the influence of design parameters such as silver (Ag), silicon nitride (Si₃N₄), graphene, and ssDNA layer thicknesses. Two configurations, Sys₃ and Sys₅, were developed and numerically evaluated under varying SARS-CoV-2 concentrations in PBS solution, ranging from 0.01 nM to 100 nM. Sys₃, optimized with Ag at 55 nm, Si₃N₄ at 13 nm, and ssDNA at 10 nm, demonstrated exceptional sensitivity (371.7°/RIU), low limit of detection, and high detection accuracy, making it suitable for precision applications. In contrast, Sys₅, incorporating a graphene layer (0.34 nm) alongside Ag at 50 nm, Si₃N₄ at 10 nm, and ssDNA at 10 nm, exhibited superior robustness and a higher figure of merit (2287.2 RIU⁻ 1 ), offering consistent performance across a broader dynamic range. These results highlight the versatility of SPR biosensors in adapting to diverse diagnostic needs. • The SPR biosensors achieve sensitivities of 371.67°/RIU (Sys₃) and 177.93°/RIU (Sys₅), evidencing exceptional performance in detecting refractive index changes associated with SARS-CoV-2. • The detection accuracy reaches values of 14.14 × 10 −2 RIU⁻ 1 for Sys₃ and 7.34 × 10 −2 RIU⁻ 1 for Sys₅, highlighting the biosensors' ability to resolve variations effectively. • The quality factor achieves a peak of 93.4 RIU⁻ 1 for Sys 3 at 0.01 nM, demonstrating the sharpness and reliability of the resonance curve for precise diagnostics.

Biosensors and Bioelectronics XVol. 23
Universidad Técnica Particular de Loja (EC), Escuela Superior Politécnica del Chimborazo (EC), Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di Frascati (IT), Universidad Nacional de Chimborazo (EC), University of Calabria (IT)
Universidad Técnica Particular de Loja
Affordable and clean energy
Openalex Percentile: Top 1%
SARS-CoV-2 detection and testing
15.36
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