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SPR Sensor Based on a Concave Photonic Crystal Fiber Structure with MoS2/Au Layers
Xiaotong Guo1,2, Yueke Wang1,2, Tian Sang1,2
1Optica Information Science and Technology Department, Jiangnan University, Wuxi 214122, China.
Materials (Basel, Switzerland)
|August 26, 2023
Summary
We developed a novel surface plasmon resonance (SPR) sensor using concave photonic crystal fiber (PCF) coated with molybdenum disulfide (MoS2) and gold. This advanced SPR sensor demonstrates significantly enhanced wavelength sensitivity for refractive index (RI) detection.
Area of Science:
- Photonics
- Nanotechnology
- Sensing Technology
Background:
- Surface Plasmon Resonance (SPR) sensors are crucial for detecting changes in refractive index (RI).
- Photonic Crystal Fibers (PCFs) offer unique light-confining properties for enhanced sensing applications.
- Molybdenum disulfide (MoS2) and gold (Au) are advanced materials with significant optical and electronic properties.
Purpose of the Study:
- To propose and analyze a novel SPR sensor based on concave PCF.
- To investigate the potential of MoS2 and Au coatings for enhanced RI sensing.
- To optimize sensor design for improved sensitivity and resolution.
Main Methods:
- Utilizing a concave photonic crystal fiber (PCF) structure.
- Coating the PCF with molybdenum disulfide (MoS2) and gold (Au) layers.
- Employing the Finite Element Method (FEM) for optical loss spectra calculation and design verification.
Main Results:
- Achieved a maximum wavelength sensitivity of 5100 nm/RIU, a significant improvement over sensors with only Au layers.
- Demonstrated a wide RI detection range from 1.19 to 1.40 in the near-infrared band.
- Obtained a high resolution of 1.96 × 10^-5 RIU and a figure of merit (FOM) of 29.143.
Conclusions:
- The proposed MoS2-Au coated concave PCF SPR sensor offers superior performance for RI detection.
- The sensor design shows excellent potential for applications in medical testing, biological detection, environmental monitoring, and chemical analysis.
- Further investigation into geometrical parameters and material thicknesses can lead to further optimization.
