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<p>This study presents an innovative biosensor design featuring a simple architecture of resonators for non-invasive glucose detection. The proposed sensor integrates cutting-edge nanomaterials including MXene-coated circular ring resonators, gold-plated main resonator structures, and a graphene-functionalized base platform on a silicon dioxide substrate. Operating in the terahertz frequency, the sensor demonstrates exceptional performance with a sensitivity of 1000 GHzRIU<sup>−1</sup> and a figure of merit of 10.638 RIU⁻<sup>1</sup>. Parametric optimization demonstrates the significant impact of graphene chemical potential on the transmittance behavior with values ranging from 88.100 to 22.071% as chemical potential increases. The sensor also exhibits a remarkable frequency tuning range of 40&#xa0;GHz in response to glucose concentration variations. Polynomial regression analysis confirms the sensor’s predictive accuracy of 100% with <i>R</i><sup>2</sup> values ranging from 99 to 100% across different refractive index values. The linear relationship between resonance frequency and refractive index validates the sensor’s reliability for quantitative glucose measurements.</p>

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AI-Enhanced Glucose Detection Using a Circular based SPR Biosensor with Graphene-Mxene-Au-Architecture

  • 期刊论文

  • 发表日期：

    2025年6月19日

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  • S. Vidhya,
  • Jacob Wekalao,
  • Ganta Raghotham Reddy

摘要

This study presents an innovative biosensor design featuring a simple architecture of resonators for non-invasive glucose detection. The proposed sensor integrates cutting-edge nanomaterials including MXene-coated circular ring resonators, gold-plated main resonator structures, and a graphene-functionalized base platform on a silicon dioxide substrate. Operating in the terahertz frequency, the sensor demonstrates exceptional performance with a sensitivity of 1000 GHzRIU−1 and a figure of merit of 10.638 RIU⁻1. Parametric optimization demonstrates the significant impact of graphene chemical potential on the transmittance behavior with values ranging from 88.100 to 22.071% as chemical potential increases. The sensor also exhibits a remarkable frequency tuning range of 40 GHz in response to glucose concentration variations. Polynomial regression analysis confirms the sensor’s predictive accuracy of 100% with R2 values ranging from 99 to 100% across different refractive index values. The linear relationship between resonance frequency and refractive index validates the sensor’s reliability for quantitative glucose measurements.