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<p>This paper presents a dual-resonator gas sensing platform that combines MXene and graphene materials in a simple architectural design. The sensor consists of a MXene-coated circular ring resonator positioned within a larger graphene-coated circular resonator.Through COMSOL Multiphysics simulations, the sensor demonstrates sensitivities of 400 GHzRIU<sup>−1</sup> to 500 GHzRIU<sup>−1</sup> across a refractive index range of 1.00–1.07 RIU, with a consistent FWHM of 0.133 THz. The design&#xa0;also achieves figures of merit between 3.008–3.759 RIU⁻<sup>1</sup> and quality factors ranging from 9.451 to 9.226. Integration of Random Forest Regression enhances the sensor's predictive capabilities, achieving 100% R<sup>2</sup> scores for both geometric and refractive index variations. The proposed sensor outperforms several existing detection systems while also offering dual-band operation at 0.1–0.4 THz and 1.0–1.6 THz ranges.</p>

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Dual-Resonator MXene Metasurface-Based Gas Sensor with Machine Learning-Enhanced Surface Plasmon Resonance Detection

  • 期刊论文

  • 发表日期：

    2025年3月29日

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  • Jacob Wekalao,
  • Oumaymah Elamri

摘要

This paper presents a dual-resonator gas sensing platform that combines MXene and graphene materials in a simple architectural design. The sensor consists of a MXene-coated circular ring resonator positioned within a larger graphene-coated circular resonator.Through COMSOL Multiphysics simulations, the sensor demonstrates sensitivities of 400 GHzRIU−1 to 500 GHzRIU−1 across a refractive index range of 1.00–1.07 RIU, with a consistent FWHM of 0.133 THz. The design also achieves figures of merit between 3.008–3.759 RIU⁻1 and quality factors ranging from 9.451 to 9.226. Integration of Random Forest Regression enhances the sensor's predictive capabilities, achieving 100% R2 scores for both geometric and refractive index variations. The proposed sensor outperforms several existing detection systems while also offering dual-band operation at 0.1–0.4 THz and 1.0–1.6 THz ranges.