A D-type fiber based symmetrical long-range surface plasmon resonance sensor with high quality factor. (July 2019)

• Record Type: Journal Article
• Authors: Jing, Jian-Ying; Li, Si-Yuan; Wang, Xue-Zhou; Zhu, Qi; Meng, Fan-Li; Wang, Qi
• Is Part Of: Measurement. Volume 140(2019)
• Page Start: 395
• Page End: 406
• Publication Date: 2019-07
• Subjects: Long-range surface plasmon resonance -- D-type fiber -- Transfer matrix method -- High quality factor; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2019.03.078
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: A symmetrical LRSPR sensor based on D-type fiber was proposed and demonstrated. Transfer matrix method was mainly adopted to optimize the sensor parameters. The sensing performance of the cSPR, cLRSPR, and sLRSPR sensor was compared. The Q-F of the proposed symmetrical LRSPR sensor was as high as 107.52 RIU −1 . This work provided a novel method to improve the performance of fiber SPR sensor. Abstract: A D-type fiber based symmetrical long-range surface plasmon resonance (sLRSPR) sensor with high quality factor (Q-F) as high as 107.52 RIU −1 was proposed and experimentally demonstrated. The sensing structure of the proposed sensor consisted of fiber/dielectric buffer layer (DBL)/Au film/DBL/analyte, and the DBLs on both sides of the Au film in the sLRSPR sensor were identical, which greatly increased the permittivity matching degree between the analyte and the DBL near the D-type fiber, and reduced the loss of long-range surface plasmon polaritons. For LRSPR sensor, the closer the permittivities of DBL and analyte on both sides of metal film are, the easier the LRSPR is to stimulate, and thus the proposed sensor possessed higher sensitivity and higher detection accuracy. The transfer matrix method supported by the finite-difference beam propagation method and the finite element analysis was employed to optimize the sensor parameters for the first time. The refractive index sensing performance of the conventional SPR (cSPR) sensor, the conventional LRSPR (cLRSPR) sensor, and the sLRSPR sensor with optimal parameters were systematically researched by simulation and in-depth experiment. The results suggested that the sensing performance of the sLRSPR sensor was better than that of the other two sensors. This paper provided a meaningful advancement for designing an optical fiber SPR sensor with remarkable performance to measure biomass.