Fiber optic DC electric field sensor based on electrically tunable liquid crystals
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Hongchao Lan
,
Xiaozhan Yang
,
Wenlin Feng
,
Zhixian Zhang
Abstract
Two fiber optic direct current (DC) electric field sensors are proposed based on electrically tunable liquid crystal (LC) is proposed. The two sensors have the transmissive and reflective structure, respectively. The multimode fiber is connected to the LC device, enabling the measurement of the transmittance and reflective interferometric spectra. The variation of the applied electric field can cause the change in the effective refractive index of the LC, and the intensity or wavelength of light passing through the LC device can be continuously tuned when the applied electric field exceeds a threshold value. In the electric field range of 280–520 V/mm, with the increase of the electric field intensity, the transmittance of the sensor decreases, the linear sensitivity is 0.40549 %/(V/mm) with the detection limit (LOD) of 0.20028 V/mm. For the sensor with the reflective structure, the blue shift occurs with the increase of electric field intensity, and the linear sensitivity of 0.0474 nm/(V/mm) with the LOD of 0.12152 V/mm. In addition, the sensors have the advantages of good repeatability, low cost, high sensitivity, etc., and have potential applications in the electric field sensing and photoelectric switches.
Funding source: Chongqing Municipal Education Commission and Municipal Science and Technology Bureau Joint Fund
Award Identifier / Grant number: CSTB2022NSCQ-LZX0032
Funding source: Chongqing Municipal Education Commission
Award Identifier / Grant number: KJZD-K202201107
Funding source: National Natural Science Foundation of China
Award Identifier / Grant number: 51574054
Acknowledgments
The authors acknowledge the support from the National Natural Science Foundation of China (51574054), Chongqing Municipal Education Commission (KJZD-K202201107), Chongqing Municipal Education Commission and Municipal Science and Technology Bureau Joint Fund (CSTB2022NSCQ-LZX0032), and Chongqing University of Technology Graduate Education Quality Development Project (gzlcx20233321).
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Research ethics: This research did not involve human participants, animals, or the use of sensitive data.
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Informed consent: Not applicable.
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Author contributions: Hongchao Lan: Conceptualization, Methodology, Writing – original draft, Writing – review & editing, Investigation, Data curation. Taiming Luo: Conceptualization and Methodology. Xiaozhan Yang: Supervision, Software, Resources. Wenlin Feng: Visualization, Software, Resources. Zhixian Zhang: Validation, Formal analysis. Sheng Tang: Materials and Formal analysis.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors declare that they have no competing interests.
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Research funding: None declared.
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Data availability: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
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