Our site saves small pieces of text information (cookies) on your device in order to deliver better content and for statistical purposes. You can disable the usage of cookies by changing the settings of your browser. By browsing our site without changing the browser settings you grant us permission to store that information on your device.
XIANGDONG YI1,* , TIANGUI HUANG1, RENLONG ZHOU1, JUNMING LAO1
This study presents the design and analysis of a highly sensitive surface plasmon resonance (SPR) biosensor based on a graphene-SiO2 hybrid structure. Utilizing a prism-coupled configuration, the sensor incorporates a SiO2 dielectric layer and a few-layer graphene film deposited on a gold film to substantially enhance the localized electromagnetic field and biomolecule capture efficiency at the sensing interface. The effects of key structural parameters—including the number of graphene layers, SiO2 thickness, and gold film thickness—on sensor performance were systematically investigated. An optimized sensitivity of 220°/RIU was achieved with a five-layer graphene configuration at an analyte refractive index of 1.39, representing a 175% improvement over conventional SPR sensors. Electromagnetic field analysis revealed that localized field enhancement near the graphene edges is the primary mechanism driving this sensitivity improvement. The proposed sensor exhibits excellent responsiveness and stability across a broad refractive index range of 1.33–1.39, providing a high-performance platform for precise biochemical detection.
Surface Plasmon Resonance (SPR), Biosensor, Graphene, SiO₂, Sensitivity.
XIANGDONG YI, TIANGUI HUANG, RENLONG ZHOU, JUNMING LAO, High-sensitivity plasmonic biosensor based on a graphene-SiO₂ hybrid structure, Optoelectronics and Advanced Materials - Rapid Communications, 20, 7-8, July-August 2026, pp.371-377 (2026).
Submitted at: April 19, 2026
Accepted at: Aug. 3, 2026
Optoelectronics and Advanced Materials - Rapid Communications
(2025): Impact Factor = 0.5 - Journal Citation Reports (Clarivate Analytics, 2026)
Active accounts were imported to the new platform and assigned a random password by default. In order to access your account you need to access the login page and go through the Lost Password dialog (involves the system sending you an email with instructions) in order to reset your password. This step is necessary as passwords are kept in hashed form and the new platform uses modern hashing algorithms incompatible with the previous ones.