A mid-infrared exhaled carbon dioxide isotope detection system based on 4.35 mu m quantum cascade laser
Author(s): Li, GL (Li, Guolin); Zhang, XN (Zhang, Xuena); Zhang, ZC (Zhang, Zecheng); Wu, YH (Wu, Yunhui); Ma, K (Ma, Kun); Jiao, Y (Jiao, Yue); Li, JR (Li, Jiarui); Liu, YJ (Liu, Yajing); Song, YM (Song, Yimeng); Zhao, H (Zhao, Hao); Zhai, SQ (Zhai, Shenqiang); Li, Q (Li, Qiang)
Source: OPTICS AND LASER TECHNOLOGY Volume: 152 Article Number: 108117 DOI: 10.1016/j.optlastec.2022.108117 Published: AUG 2022
Abstract: The carbon dioxide isotope in human exhaled gas can be used as an indicator to determine Helicobacter pylori (HP), the detection of carbon dioxide isotope in human exhaled gas is of great significance for the treatment of human diseases. Based on Tunable Diode Laser Absorption Spectroscopy (TDLAS), a carbon dioxide isotope detection system for exhaled gas was developed to detect the carbon dioxide isotope in human exhaled gas, a 4.35 mu m quantum cascade laser (QCL) and a 3 m optical path multi-pass gas cell (MPGC) were adopted in the detection system. The exhaled gas pretreatment system was designed to pass through human exhaled gas into the MPGC. The performance of the system was researched using a gas distribution station fitted with standard 12CO2 and 13CO2 concentrations. The results show that the limits of detection(LOD)of 12CO2 and 13CO2 reach up 0.0134 ppm and - 0.0149 ppm, respectively. The detection precision of the system is - 0.00214 parts per thousand with a 48 s averaging time. QCL-based mid-infrared detection system has higher sensitivity and lower detection limit compared with near-infrared detection system. The volume of MPGC is 250 ml, which is much less than the volume of normal human exhaled gas, therefore the majority of human exhaled gas can be filled with MPGC. Two-stage proportional-integral-derivative (PID) temperature control is adopted to eliminate the effect of drift of the spectrum due to the change of temperature, so that the stability of the system is improved. A high precision and high-speed Genetic Algorithm Extreme Learning Machine (GA-ELM) algorithm is applied for improving the concentration inversion precision of the system. Finally, the performance of detection system was validated at Sichuan Cancer Hospital for detecting carbon dioxide isotope in exhaled gas, and the verification results illustrate that the detection system has a very important application prospect in the field of exhaled gas detection.
Accession Number: WOS:000806575800003
ISSN: 0030-3992
eISSN: 1879-2545
Full Text: https://www.sciencedirect.com/science/article/pii/S0030399222002742?via%3Dihub