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<p>A highly sensitive surface plasmon resonance (SPR)-based biosensor is introduced designed for the non-invasive detection of diabetes levels using urine samples. The proposed multilayer sensor architecture comprises a CaF<sub>2</sub> glass prism, a 12&#xa0;nm ZnO adhesion layer, a 40&#xa0;nm Ag plasmonic film, a 2&#xa0;nm TiO<sub>2</sub> dielectric layer, a 0.75&#xa0;nm BlueP/WS<sub>2</sub> heterostructure, and the sensing medium (urine). The sensor is engineered to detect glucose concentrations ranging from 0 to 15&#xa0;mg/dl (non-diabetic) to 10&#xa0;g/dl (severely diabetic), corresponding to refractive index values between 1.335 and 1.347. Structural optimization was performed via the Transfer Matrix Method (TMM) at a wavelength of 633&#xa0;nm, targeting key performance indicators such as angular sensitivity, figure of merit (FOM), full width at half maximum (FWHM), detection accuracy (DA), limit of detection (LOD), and quality factor (QF). To validate the TMM results, complementary Finite Element Method (FEM) simulations were carried out. The optimized biosensor demonstrated a peak angular sensitivity of 530 Deg/RIU. This result, to the best of our knowledge, represents the highest sensitivity reported to date for urine-based diabetes detection, while achieving a minimum reflectivity of 0.11622. The additional performance metrics achieved include an FOM of 103.721, FWHM of 4.516°, DA of 0.221 Deg<sup>-1</sup>, LOD of 1.887 × 10<sup>− 6</sup>, and a QF of 117.360 RIU<sup>-1</sup>. These findings underscore the proposed sensor’s potential for accurate, real-time glucose monitoring and highlight its promise for application in advanced clinical diagnostics.</p> Graphical Abstract <p></p>

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Ultra-sensitive surface plasmon resonance biosensor for non-invasive diabetes monitoring based on 2D nanomaterial heterostructures

  • 期刊论文

  • 发表日期：

    2026年3月23日

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  • Soumo Paul,
  • Tonima Ghosh,
  • Raihan Ahmed,
  • Faysal Nayan

摘要

A highly sensitive surface plasmon resonance (SPR)-based biosensor is introduced designed for the non-invasive detection of diabetes levels using urine samples. The proposed multilayer sensor architecture comprises a CaF2 glass prism, a 12 nm ZnO adhesion layer, a 40 nm Ag plasmonic film, a 2 nm TiO2 dielectric layer, a 0.75 nm BlueP/WS2 heterostructure, and the sensing medium (urine). The sensor is engineered to detect glucose concentrations ranging from 0 to 15 mg/dl (non-diabetic) to 10 g/dl (severely diabetic), corresponding to refractive index values between 1.335 and 1.347. Structural optimization was performed via the Transfer Matrix Method (TMM) at a wavelength of 633 nm, targeting key performance indicators such as angular sensitivity, figure of merit (FOM), full width at half maximum (FWHM), detection accuracy (DA), limit of detection (LOD), and quality factor (QF). To validate the TMM results, complementary Finite Element Method (FEM) simulations were carried out. The optimized biosensor demonstrated a peak angular sensitivity of 530 Deg/RIU. This result, to the best of our knowledge, represents the highest sensitivity reported to date for urine-based diabetes detection, while achieving a minimum reflectivity of 0.11622. The additional performance metrics achieved include an FOM of 103.721, FWHM of 4.516°, DA of 0.221 Deg-1, LOD of 1.887 × 10− 6, and a QF of 117.360 RIU-1. These findings underscore the proposed sensor’s potential for accurate, real-time glucose monitoring and highlight its promise for application in advanced clinical diagnostics.

Graphical Abstract