Robust and Rapid Detection of Mixed Volatile Organic Compounds in Flow Through Air by a Low Cost Electronic Nose

Abstract

This work aims to detect volatile organic compounds (VOC), i.e., acetone, ethanol and isopropyl alcohol (IPA) and their binary and ternary mixtures in a simulated indoor ventilation system. Four metal-oxide-semiconductor (MOS) gas sensors were chosen to form an electronic nose and it was used in a flow-through system. To speed up the detection process, transient signals were used to extracted features, as opposed to commonly used steady-state signals, which would require long time stabilization of testing parameters. Five parameters were extracted including three in phase space and two in time space. Classifier and regression models based on backpropagation neural network (BPNN) were used for the qualitative and quantitative detection of VOC mixtures. The VOCs were mixed at different ratios; ethanol and isopropyl alcohol had similar physical and chemical properties, both being challenging in terms of obtaining quantitative results. To estimate the amounts of VOC in the mixtures, the Levenberg–Marquardt algorithm was chosen in network training. When compared with the multivariate linear regression method, the BPNN-based model offered better performance on differentiating ethanol and IPA. The test accuracy of the classification was 82.6%. The concept used in this work could be readily translated for detecting closely related chemicals.

Fast and noninvasive electronic nose for sniffing out COVID-19 based on exhaled breath-print recognition

“…Commonly, for metal oxide semiconductor gas sensors, their conductivity will change in the presence of target gases due to a redox reaction between the active material (e.g., n -type tin oxide (SnO 2 )) and gas molecules. The detailed sensing mechanism toward VOCs based on an equilibrium shift of the surface chemisorbed oxygen reaction has been described in other studies 41 , 67 – 69 . Here, the depletion regions at material surfaces were controlled by target VOCs, leading to a change in the movement of free charge carriers from the metal oxide semiconductor to the oxygens or vice versa (i.e., free electrons in the case of the n -type SnO 2 active layers).…”

Hybrid learning method based on feature clustering and scoring for enhanced COVID-19 breath analysis by an electronic nose

“…1 a. Several other studies have described the sensing principle of MOS gas sensors in detail, which is based on an equilibrium shift of the surface chemisorbed oxygen reaction [54] , [55] , [56] . The output signals then underwent preprocessing steps (i.e., labeling, normalization, and area under the curve (AUC) determination) prior to machine learning-based data assessment ( Fig.…”

Exhaled Breath and Oxygenator Sweep Gas Propionaldehyde in Acute Respiratory Distress Syndrome

“…In their study, the signal of acetone and isoprene detected in both measurement sites correlated well, whereas propionaldehyde was not identified as a significant signal. Ongoing research focuses on alternative detection methods for VOCs in patients’ breath that are more cost effective and portable than the IMR-MS technology [ 15 , 16 ].…”