Ultrasensitive refractive index fiber sensor based on high-order harmonic Vernier effect and a cascaded FPI

被引:27
|
作者
Qiu, Haiming [1 ]
Tian, Jiajun [1 ]
Yao, Yong [1 ]
机构
[1] Harbin Inst Technol, Dept Elect & Informat Engn, Shenzhen 518055, Peoples R China
基金
中国国家自然科学基金;
关键词
MACH-ZEHNDER INTERFEROMETER; PHOTONIC CRYSTAL FIBER; FEMTOSECOND LASER; TEMPERATURE;
D O I
10.1364/OE.484430
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
This paper proposes and demonstrates an ultrasensitive refractive index (RI) sensor based on harmonic Vernier effect (HEV) and a cascaded Fabry-Perot interferometer (FPI). The sensor is fabricated by sandwiching a hollow-core fiber (HCF) segment between a lead-in single-mode fiber (SMF) pigtail and a reflection SMF segment with an offset of 37 mu m between two fiber centers to form a cascaded FPI structure, where the HCF is the sensing FPI, and the reflection SMF is the reference FPI. To excite the HEV, the optical path of the reference FPI must be multiple times (>1) that of the sensing FPI. Several sensors have been made to conduct RI measurements of gas and liquid. The sensor's ultrahigh RI sensitivity of up to similar to 378000 nm/RIU can be achieved by reducing the detuning ratio of the optical path and increasing the harmonic order. This paper also proved that the proposed sensor with a harmonic order of up to 12 can increase the fabricated tolerances while achieving high sensitivity. The large fabrication tolerances greatly increase the manufacturing repeatability, reduce production costs, and make it easier to achieve high sensitivity. In addition, the proposed RI sensor has advantages of ultrahigh sensitivity, compactness, low production cost (large fabrication tolerances), and capability to detect gas and liquid samples. This sensor has promising potentials for biochemical sensing, gas or liquid concentration sensing, and environmental monitoring. (c) 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
引用
收藏
页码:13053 / 13064
页数:12
相关论文
empty
未找到相关数据