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Next-generation COVID-19 detection using a metasurface biosensor with machine learning-enhanced refractive index

N A Natraj1, Azath Mubarakali2, Manjunathan Alagarsamy3

  • 1Symbiosis Institute of Digital and Telecom Management (SIDTM), Symbiosis International (Deemed University), Pune, India. natraj@sidtm.edu.in.

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Summary

A novel graphene-silver biosensor offers rapid, label-free COVID-19 detection. This metasurface sensor, enhanced by machine learning, achieves high sensitivity and accuracy for pandemic preparedness.

Keywords:
COVID-19 detectionGraphene metasurfaceMachine learningSurface plasmon resonanceTerahertz biosensor

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Area of Science:

  • Nanotechnology
  • Biosensing
  • Terahertz (THz) technology

Background:

  • Conventional COVID-19 tests like RT-PCR and antigen tests face limitations including delays, high costs, and reduced sensitivity, especially in asymptomatic cases.
  • There is a critical need for rapid, accurate, and cost-effective diagnostic tools for effective pandemic response and preparedness.

Purpose of the Study:

  • To develop and characterize a high-performance graphene-silver hybrid metasurface biosensor for fast and precise COVID-19 detection.
  • To leverage machine learning for enhanced predictive reliability of the biosensor across varying refractive indices.
  • To demonstrate a scalable and practical fabrication strategy for the proposed biosensor.

Main Methods:

  • Parametric optimization of the graphene-silver metasurface using COMSOL Multiphysics.
  • Fabrication involving Chemical Vapor Deposition (CVD) graphene growth, electron beam lithography, and silver deposition.
  • Implementation of a machine learning framework to improve predictive accuracy and reliability.

Main Results:

  • Achieved high sensitivity (400 GHz/RIU), figure of merit (FOM) of 5.000 RIU⁻¹, and Q factor of 12.7 within a specific refractive index range.
  • Machine learning model demonstrated high predictive reliability with a coefficient of determination (R²) of 0.90.
  • The proposed sensor surpasses the performance of existing optical and terahertz biosensors in terms of sensitivity, FOM, and predictive accuracy.

Conclusions:

  • The synergistic integration of a graphene-silver metasurface with machine learning enables rapid, label-free, and highly accurate COVID-19 detection.
  • The developed biosensor offers a superior balance of performance metrics compared to conventional diagnostic methods.
  • This novel, portable, and cost-effective diagnostic tool holds significant potential for next-generation pandemic preparedness.