Surface Plasmon Resonance and Photonic Fiber Sensors for Biosensing and Refractive Index Measurement
This community designs and models optical sensors that exploit surface plasmon resonance and photonic crystal fibers to detect changes in refractive index, primarily for biosensing applications like cancer biomarker identification and pathogen detection.
The work centers on the integration of plasmonic materials, such as gold and silver nanoparticles, with fiber optic structures to enhance sensitivity. Recurring methods include the use of photonic crystal fibers, graphene oxide coatings, and lossy mode resonance to improve detection limits. Applications are heavily skewed toward biomedical diagnostics, with specific focus on cancer detection, glucose quantification, and viral identification. The research frequently employs machine learning algorithms to optimize sensor design and signal processing, while also exploring the use of advanced materials like black phosphorus and MXenes to further refine the plasmonic response.
Gold research contains the largest share of this community's output, accounting for 0.6% of all gold research, and 1,148 papers here. The community publishes most frequently in Plasmonics, Optics & Laser Technology, and Optical and Quantum Electronics. Recent work continues to focus on high-sensitivity biosensors for cancer biomarkers and glucose detection, often incorporating machine learning for signal enhancement and utilizing nanostructured surfaces to improve plasmonic coupling.