Laser-based selective BTEX sensing using deep neural networks

Mhanna Mhanna, Mohamed Sy, Ayman Arfaj, Jose Llamas, Aamir Farooq*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

A mid-infrared absorption-based laser sensor is developed for selective and simultaneous benzene, toluene, ethylbenzene, and xylenes (BTEX) measurements under ambient conditions. The sensor is based on a distributed feedback inter-band cascade laser emitting near 3.3 µm. Wavelength tuning and deep neural networks were employed to differentiate the broadband absorbance of BTEX species. The sensor was validated with gas mixtures and real-time measurements were demonstrated at a temporal resolution of 1 s. Minimum detection limits for BTEX in air are 8, 20, 5, and 46 ppm, respectively. This sensor can be utilized to monitor BTEX emissions in the petrochemical, rubber, and paint industries to avoid hazardous health effects.

Original languageEnglish (US)
Pages (from-to)3247-3250
Number of pages4
JournalOPTICS LETTERS
Volume47
Issue number13
DOIs
StatePublished - Jul 1 2022

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

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