High-precision quasi-static sensing method based on WGM resonator self-modulation

Whispering gallery mode (WGM) resonators have been widely researched for their high-sensitivity sensing capability, but there is currently a lack of high-sensitivity real-time sensing methods for quasi-static measurement. In this paper, within the framework of dissipative coupling sensing, a new method for quasi-static sensing based on the self-modulation of lithium niobate (LiNbO 3 ) resonators is proposed. The LiNbO 3 resonator actively modulates the signal to be measured, solving the challenge of real-time demodulation of quasi-static signals. The noise background is upconverted to a high frequency region with lower noise, further enhancing the detection limit. In the demonstration of quasi-static displacement sensing, a customized LiNbO 3 resonator with a Q -factor of 2.09×10 7 serves as the high frequency modulation and sensing element, while the movable resonator acts as the displacement loading unit. Experimental and theoretical results show that the sensing response can be improved to 0.0416 V/nm by dissipation engineering to enhance the resonator evanescent field decay rate and orthogonal polarization optimization. The Allan deviation σ demonstrates a bias instability of 0.205 nm, which represents the best result known to date for microresonator displacement sensing in the quasi-static range. Our proposed scheme demonstrates competitiveness in high-precision quasi-static sensing and provides solutions for the high-precision real-time detection of low frequency or very low frequency acceleration, pressure, nanoparticles, or viruses.

Authors

Institutions

Publication Details

Journal
Photonics Research
Published
2025-04-02
DOI
https://doi.org/10.1364/prj.549972
Citations
1
Primary Topic
Geophysics and Sensor Technology
Type
article
Field-Weighted Citation Impact
1.15
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

High-precision quasi-static sensing method based on WGM resonator self-modulation

Tao Jia, Tong Xing, Yanru Zhou, Guohui Xing et al.
1 citations
Photonics Research
Geophysics and Sensor Technology
1.15
article

High-precision quasi-static sensing method based on WGM resonator self-modulation

Tao Jia, Tong Xing, Yanru Zhou, Guohui Xing, Jun Liu, Yujie Zhang, Jun Tang, Wenyao Liu, Jianglong Li, Jiamin Rong, Hongbo Yue
article en
1 citations

Abstract

Whispering gallery mode (WGM) resonators have been widely researched for their high-sensitivity sensing capability, but there is currently a lack of high-sensitivity real-time sensing methods for quasi-static measurement. In this paper, within the framework of dissipative coupling sensing, a new method for quasi-static sensing based on the self-modulation of lithium niobate (LiNbO 3 ) resonators is proposed. The LiNbO 3 resonator actively modulates the signal to be measured, solving the challenge of real-time demodulation of quasi-static signals. The noise background is upconverted to a high frequency region with lower noise, further enhancing the detection limit. In the demonstration of quasi-static displacement sensing, a customized LiNbO 3 resonator with a Q -factor of 2.09×10 7 serves as the high frequency modulation and sensing element, while the movable resonator acts as the displacement loading unit. Experimental and theoretical results show that the sensing response can be improved to 0.0416 V/nm by dissipation engineering to enhance the resonator evanescent field decay rate and orthogonal polarization optimization. The Allan deviation σ demonstrates a bias instability of 0.205 nm, which represents the best result known to date for microresonator displacement sensing in the quasi-static range. Our proposed scheme demonstrates competitiveness in high-precision quasi-static sensing and provides solutions for the high-precision real-time detection of low frequency or very low frequency acceleration, pressure, nanoparticles, or viruses.

Photonics ResearchVol. 13(5)
North University of China (CN)
Affordable and clean energy
Openalex Percentile: Top 25%
Geophysics and Sensor Technology
1.15
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.