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<p>This study presents metasurface biosensor combining graphene and MoS₂ for high-precision hemoglobin detection. The sensor design incorporates a circular resonator surrounded by four square resonators on a SiO₂ substrate, with MoS₂ and graphene layers enabling tunable plasmonic responses. Comprehensive numerical simulations demonstrate exceptional sensing capabilities across hemoglobin concentrations of 10–40&#xa0;g/L, achieving a sensitivity of 400 GHzRIU<sup>−1</sup>, a quality factor of 16.738, and a figure of merit of 5.000 RIU⁻<sup>1</sup>. The sensor exhibits linear relationships between resonance frequency and both refractive index (R<sup>2</sup> = 99.982%) and hemoglobin concentration (R<sup>2</sup> = 98.911%). Integration of Random Forest Regression optimization further enhances performance prediction accuracy. The sensor’s robust performance metrics, including consistent FWHM of 0.080 THz and detection accuracy of 12.500, establish its potential for precise hemoglobin monitoring in clinical applications.</p>

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High-Sensitivity Graphene-MoS₂ Hybrid Metasurface Biosensor with Machine Learning Optimization for Hemoglobin Detection

  • 期刊论文

  • 发表日期：

    2025年3月13日

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  • Jacob Wekalao

摘要

This study presents metasurface biosensor combining graphene and MoS₂ for high-precision hemoglobin detection. The sensor design incorporates a circular resonator surrounded by four square resonators on a SiO₂ substrate, with MoS₂ and graphene layers enabling tunable plasmonic responses. Comprehensive numerical simulations demonstrate exceptional sensing capabilities across hemoglobin concentrations of 10–40 g/L, achieving a sensitivity of 400 GHzRIU−1, a quality factor of 16.738, and a figure of merit of 5.000 RIU⁻1. The sensor exhibits linear relationships between resonance frequency and both refractive index (R2 = 99.982%) and hemoglobin concentration (R2 = 98.911%). Integration of Random Forest Regression optimization further enhances performance prediction accuracy. The sensor’s robust performance metrics, including consistent FWHM of 0.080 THz and detection accuracy of 12.500, establish its potential for precise hemoglobin monitoring in clinical applications.