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Design of Graphene Metasurface Sensor for Efficient Detection of COVID-19

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Abstract

The COVID-19 pandemic has underscored the essential need for quick and precise virus detection techniques, to stop the virus from spreading. In this paper, we have proposed a brand-new graphene metasurface sensor for effective COVID-19 detection. We have used graphene metasurfaces to increase the sensitivity of the proposed sensor. The suggested sensor architecture takes advantage of the plasmonic characteristics of graphene metasurfaces to enable the detection of particular COVID-19-related biomarkers. Strong light-graphene interactions are achieved through careful tailoring of the graphene metasurface geometry, resulting in improved sensing capabilities. The suggested graphene metasurface sensor has a number of benefits, including its small size, low cost, and ability to work with current detecting systems. Additionally, its label-free detection methodology does away with the need for laborious sample preparation stages, enabling quick on-site testing. The sensor's performance is compared to current state-of-the-art detection techniques in order to demonstrate its higher sensitivity and effectiveness. The sensor achieves a maximum sensitivity of sensitivity of 600 GHz/RIU and an excellent FOM value of 4.959 RIU−1.

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The data supporting the findings in this work are available from the corresponding author with a reasonable request.

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Acknowledgements

Researchers Supporting Project number (RSPD2023R654), King Saud University, Riyadh, Saudi Arabia.

Funding

Researchers Supporting Project number (RSPD2023R654), King Saud University, Riyadh, Saudi Arabia.

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Authors and Affiliations

  1. Department of Physics, Marwadi University, Rajkot, 360003, India

    Jacob Wekalao

  2. Department of Electrical Engineering, College of Engineering, King Saud University, P.O.Box 800, Riyadh, 11421, Saudi Arabia

    Osamah Alsalman

  3. Symbiosis Institute of Digital and Telecom Management (SIDTM), Symbiosis International (Deemed University), Pune, India

    N. A. Natraj

  4. Department of Electrical Engineering, Marwadi University, Rajkot, 360003, India

    Jaymit Surve

  5. Department of Mechanical and Materials Engineering, University of Nebraska-Lincoln, 1400 R St. Nebraska, Lincoln, 68588, USA

    Juveriya Parmar

  6. Department of Computer Engineering, Marwadi University, Rajkot, 360003, India

    Juveriya Parmar & Shobhit K. Patel

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  1. Jacob Wekalao
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Contributions

“Conceptualization, Osamah Alsalman, Shobhit K. Patel, and Jaymit Surve, methodology, Osamah Alsalman, Shobhit K. Patel, Jaymit Surve, software, Jacob Wekalao and Osamah Alsalman, validation, Jaymit surve, N. A. Natraj, Shobhit K. Patel, Juveriya Parmar, writing—original draft preparation, Jacob Wekalao, Osamah Alsalman, Jaymit surve, N. A. Natraj, Shobhit K. Patel, Juveriya Parmar, writing—review and editing, Jacob Wekalao, Osamah Alsalman, Jaymit surve, N. A. Natraj, Shobhit K. Patel, Juveriya Parmar, All authors have read and agreed to the published version of the manuscript.”

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Correspondence to Shobhit K. Patel.

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Wekalao, J., Alsalman, O., Natraj, N.A. et al. Design of Graphene Metasurface Sensor for Efficient Detection of COVID-19. Plasmonics 18, 2335–2345 (2023). https://doi.org/10.1007/s11468-023-01946-2

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