Data for: "Vibrational Fingerprinting of Gas Mixtures Using COCO-QEPAS"

Here, we use coherent control in quartz-enhanced photoacoustic spectroscopy (COCO-QEPAS) with an in-situ learning method for rapid fingerprinting of trace gases to identify and monitor arbitrary gases at very low concentrations, without prior knowledge of gas composition. We validate this on various mixtures, including CH4/C2H2/C2H4/C2H6/NO/NH3.

To this end, we demonstrate real-time analysis of mixtures containing up to four trace gases at ppm-level, monitoring changes in seconds using linear regression. The scalability of simultaneously distinguishable gases is straightforward. Furthermore, we expand fingerprinting to 10 ppm with a detection limit of 180 ppb CH4, and apply empirical mode decomposition as an adaptive, data-driven filtering method to recover characteristic spectral features at the noise floor.