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<p>This investigation presents a sensing platform for the quantitative real-time detection of isoquercitrin in phytopharmaceutical preparations. The biosensor architecture incorporates graphene into a heterogeneous resonator array comprising gold rectangular, silver circular, and bismuth square resonators fabricated on a silicon dioxide substrate. Computational electromagnetic simulations demonstrate that the sensor’s spectral response exhibits precise tunability through modulation of graphene’s chemical potential, enabling transmittance variation from 98.45% to 34.26% across the 0.1–0.4 THz frequency domain. The device demonstrates exceptional sensitivity parameters of up to 400 GHzRIU<sup>−1</sup> for isoquercitrin quantification within a refractive index range of 1.333–1.385 RIU, maintaining a consistent figure of merit of 6.897 RIU⁻<sup>1</sup>.Machine learning optimization via one-dimensional convolutional neural networks (1D-CNN) significantly enhanced the analytical performance, yielding prediction coefficients of determination (R<sup>2</sup>) of 0.95 across varying graphene chemical potentials and 0.92 across multiple incident electromagnetic wave angles. This convergence of advanced nanomaterials with computational intelligence establishes a robust analytical platform for point-of-care quality assessment in phytopharmaceuticals, addressing critical deficiencies in standardization protocols with superior sensitivity, spectral tunability, and analytical reliability compared to conventional chromatographic and spectroscopic techniques.</p>

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Graphene-integrated Multiresonator Architecture with Machine Learning Enhancement for Enhanced Isoquercitrin Detection System in Phytopharmaceutical Formulations

  • 期刊论文

  • 发表日期：

    2025年6月11日

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  • Jacob Wekalao,
  • S. Premalatha,
  • P. Prabakaran,
  • C. R. Rathish

摘要

This investigation presents a sensing platform for the quantitative real-time detection of isoquercitrin in phytopharmaceutical preparations. The biosensor architecture incorporates graphene into a heterogeneous resonator array comprising gold rectangular, silver circular, and bismuth square resonators fabricated on a silicon dioxide substrate. Computational electromagnetic simulations demonstrate that the sensor’s spectral response exhibits precise tunability through modulation of graphene’s chemical potential, enabling transmittance variation from 98.45% to 34.26% across the 0.1–0.4 THz frequency domain. The device demonstrates exceptional sensitivity parameters of up to 400 GHzRIU−1 for isoquercitrin quantification within a refractive index range of 1.333–1.385 RIU, maintaining a consistent figure of merit of 6.897 RIU⁻1.Machine learning optimization via one-dimensional convolutional neural networks (1D-CNN) significantly enhanced the analytical performance, yielding prediction coefficients of determination (R2) of 0.95 across varying graphene chemical potentials and 0.92 across multiple incident electromagnetic wave angles. This convergence of advanced nanomaterials with computational intelligence establishes a robust analytical platform for point-of-care quality assessment in phytopharmaceuticals, addressing critical deficiencies in standardization protocols with superior sensitivity, spectral tunability, and analytical reliability compared to conventional chromatographic and spectroscopic techniques.