Improved Glucose Detection in Urine Using a Silver-Based Plasmonic Sensor with Ni and TiO2 Thin Films in Kretschmann Configuration
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Surface plasmon resonance (SPR) sensors have emerged as powerful tools for label-free and real-time detection of biomolecules, yet their performance often depends on optimizing the sensing structure. This work proposes and analyzes a silver-based SPR sensor in the Kretschmann configuration, enhanced with thin layers of Ni and TiO2, for non-invasive glucose detection in urine. The optical response was calculated using the transfer matrix method, while sensitivity and figure of merit (FOM) were employed as performance indicators. The incorporation of ultrathin Ni and TiO2 layers atop the silver film induces a pronounced shift in the SPR toward higher incidence angles, accompanied by an enhanced angular response to refractive index variations, thereby indicating improved sensitivity. However, further increases in the thickness of these layers lead to an excessive redshift of the resonance dip toward the extreme angular range, reducing resonance definition and ultimately limiting the sensor's detection capability. The results show that the introduction of Ni and TiO2 significantly improves both sensitivity and spectral sharpness, with the optimal BK7/Ag(30 nm)/Ni(14 nm)/TiO2(5 nm) structure achieving a maximum sensitivity of 432 deg/RIU. This configuration detected glucose concentrations as low as 0.625 g/dL, corresponding to a refractive index change of only 0.001 RIU. Finite-difference time-domain analysis further confirmed that the performance enhancement originates from stronger localization of the electric field at the TiO2 interface, as evidenced by the presence of the Ni layer. These findings demonstrate the effectiveness of Ni and TiO2 layers in enhancing plasmonic responses and highlight the strong potential of this sensor design for practical biomedical applications. In particular, the proposed structure offers a promising pathway for developing simple, non-invasive urine-based glucose monitoring systems.
Copyright (c) 2026 Yuant Tiandho, Erna Julianti, Zamziri Zamziri, Putri Cahyani, Fitri Afriani (Author)

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