期刊
OPTICS EXPRESS
卷 29, 期 25, 页码 40734-40747出版社
OPTICAL SOC AMER
DOI: 10.1364/OE.444323
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资金
- Scientific Research Fund of Sichuan Province Science and Technology Department [2020YJ0137]
- City University of Hong Kong Strategic Research Grant (SRG) [7005505]
- Local Universities Reformation and Development Personnel Training Supporting Project from Central Authorities [140119001]
- Postdoctoral Scientific Research Development Fund of Heilongjiang Province [LBH-Q20081]
The surface plasmon resonance (SPR) chemical sensor using microstructured optical fiber (MOF) is designed for refractive index sensing and detection of gas-liquid pollutants, with high sensitivity and resolution. It has vast potential applications in the chemical industry, environmental monitoring, and safety control sectors.
A surface plasmon resonance (SPR) chemical sensor comprising microstructured optical fiber (MOF) is designed for refractive index (RI) sensing in the visible to near-infrared (0.42-1.60 mu m) region (NIR) as well as detection of gas-liquid pollutants. To realize mode coupling and facilitate manufacturing, gold with inert and plasmonic properties and an analyte sensing layer are introduced to the external surface of the MOF. The sensor is analyzed by the full-vector finite element method (FEM) and the wavelength and amplitude interrogation methods are adopted to evaluate the sensing characteristics. Our analysis reveals a maximum wavelength sensitivity (WS) of 15,000 nm/RIU, amplitude sensitivity (AS) of 1,603.37 RIU-1, and resolution (R) of 6.67x10(-6) RIU in the determination of analyte RIs spanning an ultra-wide range between 1.00 and 1.45. Furthermore, the figure of merit (FOM) and signal-to-noise ratio (SNR) of the sensor are 295.01 RIU-1 and 2.95, respectively. On account of its simple structure, low cost, and industrial compatibility, this multi-functional sensor has tremendous potential in the chemical industry, environmental monitoring, and safety control such as harmful gas monitoring, industrial wastewater and domestic sewage detection. (C) 2021 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
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