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Graphene-Enhanced Plasmonic Interfaces: A General Strategy for Highly Sensitive Detection of Biomolecular
Ahmar Hasnain1, Heiko Heilmann1, Nghi Luong Phuong Le1
1Faculty of Computer Sciences and Microsystems Technology, Kaiserslautern University of Applied Sciences, Amerikastr. 1, 66482, Zweibrücken, Germany.
Advanced Healthcare Materials
|September 4, 2025
Summary
Graphene significantly boosts surface plasmon resonance (SPR) biosensors, enhancing detection sensitivity for viruses and cells by up to 600%. This breakthrough improves diagnostic capabilities and biomedical research applications.
Area of Science:
- Biomedical Engineering
- Materials Science
- Analytical Chemistry
Background:
- High-performance biosensors are crucial for research and clinical diagnostics.
- Surface Plasmon Resonance (SPR) offers label-free, real-time detection but faces limitations in complex biological samples.
- Two-dimensional (2D) materials like graphene are explored to enhance SPR sensor sensitivity.
Purpose of the Study:
- To investigate the impact of graphene integration on SPR biosensor performance.
- To evaluate graphene-enhanced SPR for detecting various biological interactions, including viruses and cells.
- To quantify the signal enhancement achieved by graphene in SPR systems.
Main Methods:
- Fabrication of SPR biosensors with and without graphene integration.
- Testing sensor performance using antibody-virus and peptide-cell interactions.
- Real-time, label-free detection and signal analysis.
Main Results:
- Graphene integration reproducibly enhanced SPR signals by up to 600% compared to gold sensors.
- Graphene-enhanced SPR demonstrated the ability to differentiate between various cell types, a feat not achievable with gold alone.
- Observed signal enhancement significantly exceeded theoretical predictions.
Conclusions:
- Graphene integration substantially improves SPR biosensor sensitivity and specificity.
- Graphene-enhanced SPR is a versatile platform applicable to diverse biological detection scenarios.
- This technology holds significant potential for advancing diagnostics, biomedical research, and gene therapy.

