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Peer-reviewedCC BYLight Science & Applications

High-speed and high-sensitivity multi-gas detection based on parallel heterodyne LITES sensor

  • Haiyue Sun1,2
  • Shunda Qiao1,2
  • Y Q He1,2
  • Yuanzhi Wang1,2
  • Jinfeng Hou1,2
  • Chu Zhang1,2
  • Yongkang Dong1,2
  • Yufei Ma3,4
4 affiliations
  1. 1National Key Laboratory of Laser Spatial Information, Harbin Institute of Technology, Harbin, 150000, China
  2. 2Zhengzhou Advanced Research Institute of Harbin Institute of Technology, Zhengzhou, 450000, China
  3. 3National Key Laboratory of Laser Spatial Information, Harbin Institute of Technology, Harbin, 150000, China. [email protected]
  4. 4Zhengzhou Advanced Research Institute of Harbin Institute of Technology, Zhengzhou, 450000, China. [email protected]
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Abstract

A parallel heterodyne light-induced thermoelastic spectroscopy (PH-LITES) sensor is proposed for high-speed and high-sensitivity multi-gas detection for the first time. Within the collaborative signal enhancement architecture (CSEA), high sensitivity and high-speed detection are achieved at the physical layer. A self-designed cylindrical multi-pass cell (MPC) with a recorded high optical path length to volume ratio (OPL/V = 37.4 cm –2 ) and a four‑tine quartz tuning fork (QTF) with a low resonant frequency ( f 0 = ~7.9 kHz) work synergistically to enhance detection responsivity, establishing a robust foundation for highly sensitive detection of low-concentration gas mixtures. High‑speed capability is enabled by parallel heterodyne modulation, where a single QTF is excited to generate a composite transient response signal, allowing for the rapid, simultaneous acquisition of spectral information from multiple gases. At the information layer, intelligent processing is implemented via a collaborative intelligent processing architecture (CIPA) integrating convolutional neural networks (CNN), a hybrid attention mechanism (HAM), and bidirectional long short-term memory (BiLSTM). The CNN-HAM-BiLSTM architecture performs feature extraction, attention-based enhancement, and temporal modeling to enable accurate concentration retrieval from the parallel spectra derived from a single QTF output. Experimental validation using methane (CH 4 ) and acetylene (C 2 H 2 ) achieved minimum detection limits (MDLs) of 378 ppb and 285 ppb, respectively, within a 4 s scanning time. The proposed system offers an efficient solution for applications requiring rapid and sensitive multi-gas detection.

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Cite

BibTeXRIS
BibTeX
@article{sun2026highspeed,
  title = {{High-speed and high-sensitivity multi-gas detection based on parallel heterodyne LITES sensor}},
  author = {Haiyue Sun and Shunda Qiao and Y Q He and Yuanzhi Wang and Jinfeng Hou and Chu Zhang and Yongkang Dong and Yufei Ma},
  journal = {Light Science \& Applications},
  year = {2026},
  month = jun,
  doi = {10.1038/s41377-026-02385-4},
  url = {https://doi.org/10.1038/s41377-026-02385-4},
  note = {CC BY},
}
RIS
TY  - JOUR
TI  - High-speed and high-sensitivity multi-gas detection based on parallel heterodyne LITES sensor
AU  - Haiyue Sun
AU  - Shunda Qiao
AU  - Y Q He
AU  - Yuanzhi Wang
AU  - Jinfeng Hou
AU  - Chu Zhang
AU  - Yongkang Dong
AU  - Yufei Ma
PY  - 2026
DA  - 2026/06/29
JO  - Light Science & Applications
DO  - 10.1038/s41377-026-02385-4
UR  - https://doi.org/10.1038/s41377-026-02385-4
AB  - A parallel heterodyne light-induced thermoelastic spectroscopy (PH-LITES) sensor is proposed for high-speed and high-sensitivity multi-gas detection for the first time. Within the collaborative signal enhancement architecture (CSEA), high sensitivity and high-speed detection are achieved at the physical layer. A self-designed cylindrical multi-pass cell (MPC) with a recorded high optical path length to volume ratio (OPL/V = 37.4 cm –2 ) and a four‑tine quartz tuning fork (QTF) with a low resonant frequency ( f 0 = ~7.9 kHz) work synergistically to enhance detection responsivity, establishing a robust foundation for highly sensitive detection of low-concentration gas mixtures. High‑speed capability is enabled by parallel heterodyne modulation, where a single QTF is excited to generate a composite transient response signal, allowing for the rapid, simultaneous acquisition of spectral information from multiple gases. At the information layer, intelligent processing is implemented via a collaborative intelligent processing architecture (CIPA) integrating convolutional neural networks (CNN), a hybrid attention mechanism (HAM), and bidirectional long short-term memory (BiLSTM). The CNN-HAM-BiLSTM architecture performs feature extraction, attention-based enhancement, and temporal modeling to enable accurate concentration retrieval from the parallel spectra derived from a single QTF output. Experimental validation using methane (CH 4 ) and acetylene (C 2 H 2 ) achieved minimum detection limits (MDLs) of 378 ppb and 285 ppb, respectively, within a 4 s scanning time. The proposed system offers an efficient solution for applications requiring rapid and sensitive multi-gas detection.
SN  - 2047-7538
SN  - 2095-5545
ER  -