Acta Optica Sinica, Volume. 42, Issue 18, 1830004(2022)

Optimization Design of H-Type Differential Photoacoustic Cell and NO2 Detection

Zhengang Li1,2, Jiaxiang Liu1, Ganshang Si1,2, Zhiqiang Ning1,2, Yonghua Fang1,2、*, and Ying Pan1
Author Affiliations
  • 1Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui, China
  • 2University of Science and Technology of China, Hefei 230026, Anhui, China
  • show less

    Based on the photoacoustic spectroscopy technology, this paper constructed a simulation model of the H-type differential photoacoustic cell by finite element simulation, and the geometric parameters of the cell were optimized. In addition, the robustness to noise was guaranteed, and the sound pressure and quality factor were greatly increased. The paper chose NO2 as the target gas to verify the performance of the photoacoustic cell, and a low-cost 450 nm laser diode was used as the excitation light source to match the strong absorption line of NO2 and avoid photolysis. The experimental results show that the differential characteristic of the photoacoustic cell is consistent with the simulation results. Within the detection time of 5 s, the linearity between photoacoustic signals and different concentrations of samples reaches 0.999, and the minimum detection limit is 124×10-12, which meets the online detection requirements of NO2 in an atmospheric environment.

    Tools

    Get Citation

    Copy Citation Text

    Zhengang Li, Jiaxiang Liu, Ganshang Si, Zhiqiang Ning, Yonghua Fang, Ying Pan. Optimization Design of H-Type Differential Photoacoustic Cell and NO2 Detection[J]. Acta Optica Sinica, 2022, 42(18): 1830004

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Spectroscopy

    Received: Mar. 7, 2022

    Accepted: Apr. 5, 2022

    Published Online: Sep. 15, 2022

    The Author Email: Fang Yonghua (yhfang@aiofm.ac.cn)

    DOI:10.3788/AOS202242.1830004

    Topics