Photonic Crystal Fiber SPR Liquid Sensor Based on Elliptical Detective Channel.

finite element method linearity liquid sensor photonic crystal fiber refractive index sensitivity surface plasmon resonance effect

Journal

Micromachines
ISSN: 2072-666X
Titre abrégé: Micromachines (Basel)
Pays: Switzerland
ID NLM: 101640903

Informations de publication

Date de publication:
07 Apr 2021
Historique:
received: 24 02 2021
revised: 28 03 2021
accepted: 06 04 2021
entrez: 30 4 2021
pubmed: 1 5 2021
medline: 1 5 2021
Statut: epublish

Résumé

This paper proposes a Photonic Crystal Fiber (PCF) refractive index sensor model based on the surface plasmon resonance effect. The proposed PCF model also uses the full vector finite element method to transfer the structure under the anisotropic Perfect Matching Layer (PML) boundary condition. Numerical calculations were carried out on the sensor characteristics. The calculation results show that the elliptical air hole on the left side of the PCF core is coated with a gold-nano film which serves as a Surface Plasmon Resonance (SPR) sensing channel to detect the refractive index of liquid materials. Compared with other structures, the resonant peak generated by the excited SPR effect from the elliptical sensing channel has a high sensitivity to the change of the refractive index of the liquid to be measured. With the help of this attribute, it is relatively easy to adjust the sensitivity. The refractive index range of this structure is within 1.43-1.49 and the sensitivity is up to 12,719.97 nm·RIU

Identifiants

pubmed: 33917055
pii: mi12040408
doi: 10.3390/mi12040408
pmc: PMC8067755
pii:
doi:

Types de publication

Journal Article

Langues

eng

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Auteurs

Xin Yan (X)

State Key Laboratory of Synthetical Automation for Process Industries, College of Information Science and Engineering, Northeastern University, Shenyang 110819, China.

Yao Wang (Y)

State Key Laboratory of Synthetical Automation for Process Industries, College of Information Science and Engineering, Northeastern University, Shenyang 110819, China.

Tonglei Cheng (T)

State Key Laboratory of Synthetical Automation for Process Industries, College of Information Science and Engineering, Northeastern University, Shenyang 110819, China.

Shuguang Li (S)

State Key Laboratory of Synthetical Automation for Process Industries, College of Information Science and Engineering, Northeastern University, Shenyang 110819, China.

Classifications MeSH