Gas phase multicomponent detection and analysis combining broadband dual-frequency comb absorption spectroscopy and deep learning
Linbo Tian, Jinbao Xia, A.A. Kolomenskii, H. A. Schuessler, Feng Zhu, Yanfeng Li, Jingliang He, Qian Dong, Sasa Zhang
Abstract
Abstract In absorption spectroscopy, analysis of multicomponent gas mixtures becomes challenging when absorption features overlap (blended spectra). Here we propose a gas sensor which can accurately identify the species and retrieve the concentrations of components in a gaseous mixture in a broad spectrum. The sensor integrates a mid-infrared dual-frequency comb laser source for spectrum acquisition and a deep learning algorithm for spectral analysis. The sensor was tested on gas phase mixtures of methane, acetone and water vapor. A prototype sensor was assessed in realistic scenarios in real time. We also systematically analyzed and presented explicit visualizations to explain the underlying working mechanism of the algorithms.