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Graphene-metasurface-based biosensor for SARS-CoV-2 detection
High Contrast Metastructures XI 2022 ; 12011, 2022.
Article in English | Scopus | ID: covidwho-1891710
ABSTRACT
The COVID-19 pandemic attributed to the SARs-Cov-2 virus has disrupted the lives of individuals in every corner of the world, causing millions of infections and numerous deaths worldwide. Identifying and isolating infected people is very crucial to slow down the spread of the disease. In this paper, we report a design of highly sensitive, graphene-metasurface based biosensor for detecting the S1 spike protein expressed on the surface of the SARSCoV-2 virus in the terahertz band. Our structure consists of a silicon dioxide substrate sandwiched between a complete gold layer at the bottom, and a graphene monolayer on top etched with a phi-shaped slot tilted at 45 degree, which performs a wideband reflective-type cross-polarization conversion of the incident electromagnetic (EM) wave. The optimized polarization conversion ratio (PCR) has been achieved at 0.75eV chemical potential value of the graphene layer. When samples of Sars-CoV-2 virus contained in a phosphate buffer saline (PBS) solvent is put on top of proposed design of the sensing surface, the spike proteins of the virus interact with the spike antibody grown on the sensing surface;and it changes the refractive index of the overall system (Biosensor + Analyte), which in turn changes the PCR and the corresponding frequency of the reflected wave. The biosensor response has been computed using the Finite Integration Technique (FIT) in the terahertz region. The sensitivity of the biosensor is found to be 354 GHz/RIU at the PCR of 0.9. © COPYRIGHT SPIE. Downloading of the is permitted for personal use only.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: High Contrast Metastructures XI 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: High Contrast Metastructures XI 2022 Year: 2022 Document Type: Article