研究目的
To enhance the sensitivity and performance of surface plasmon resonance biosensors by incorporating graphene and barium titanate layers in the sensor structure.
研究成果
The proposed SPR biosensor with optimized layers of Ag (45 nm), BaTiO3 (10 nm), and monolayer graphene achieves a high sensitivity of 257°/RIU, low FWHM of 5.705°, and a quality factor two times better than existing biosensors. This design shows promise for enhanced biomolecule detection applications due to improved performance metrics.
研究不足
The study is theoretical and computational, lacking experimental validation. It assumes ideal material properties and does not account for practical fabrication challenges or environmental factors that could affect sensor performance.
1：Experimental Design and Method Selection:
The study uses a theoretical approach based on the Kretschmann configuration for SPR excitation. The transfer matrix method is applied to solve Fresnel's equations for a multilayer model consisting of BK7 prism, Ag, BaTiO3, graphene, and sensing medium layers. Angular interrogation is employed to analyze reflectivity and resonance shifts.
2：Sample Selection and Data Sources:
No physical samples are used; the analysis is computational. Data for material properties (e.g., refractive indices of BK7, Ag, BaTiO3, graphene) are sourced from literature and theoretical models (e.g., Drude-Lorentz model for Ag, experimental data for BaTiO3).
3：3).
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: The materials include BK7 prism, silver (Ag) thin film, barium titanate (BaTiO3) layer, graphene layers, and a sensing medium. No specific equipment brands or models are mentioned as the study is theoretical.
4：Experimental Procedures and Operational Workflow:
The procedure involves calculating the minimum reflectivity and resonance angle shifts for various thicknesses of Ag (30-50 nm), BaTiO3 (0-10 nm), and number of graphene layers (0-10) at a fixed wavelength of 633 nm. Electric field distributions are analyzed to understand sensitivity enhancement.
5：Data Analysis Methods:
Data analysis includes determining sensitivity (S), full width at half maximum (FWHM), detection accuracy (DA), and quality factor (Q) using defined equations. Comparisons are made with existing biosensors from literature.
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