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A laser-based sensor for selective detection of benzene, acetylene, and carbon dioxide in the fingerprint region

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Abstract

The long-wavelength infrared region provides opportunities for selective and sensitive measurements in various gas-sensing applications. In this work, a mid-infrared laser-based sensor is designed and demonstrated for trace detection of benzene, acetylene, and carbon dioxide at ambient conditions. The sensor is based on a distributed-feedback quantum cascade laser emitting near 14.84 μm. Scanned-wavelength absorption spectroscopy and a multidimensional linear regression algorithm were employed to enable selective measurements of the target species. The laser wavelength was scanned over 673.8–675.1 cm−1 by a sine-wave injection current at 1 kHz repetition rate. Noise-limited absorbance measurement was used to calculate minimum detection limits of 0.22, 5.92, and 8.32 ppm for benzene, acetylene, and carbon dioxide, respectively, at a laser path length of 26 cm. The current measurements are limited to mixtures prepared in the lab to demonstrate the superiority of this long wavelength region for high sensitivity and interference-free multi-species measurements. Future work will apply this sensor in field measurements.

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Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

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Acknowledgements

This work was funded by King Abdullah University of Science and Technology (KAUST), BAS/1/1300-01-01.

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MM wrote the manuscript, developed the codes, prepared the experimental setup, ran experiments, and processed the data. MS helped in running the experiments. AE helped in running the experiments and writing the manuscript. AF supervised the project. All authors reviewed the manuscript.

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Correspondence to Aamir Farooq.

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Mhanna, M., Sy, M., Elkhazraji, A. et al. A laser-based sensor for selective detection of benzene, acetylene, and carbon dioxide in the fingerprint region. Appl. Phys. B 129, 139 (2023). https://doi.org/10.1007/s00340-023-08083-y

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