Abstract
Gas mixture quantification is essential for the recording and reproducing odors, because an odor consists of multiple chemical compounds. Gas mixture quantification using field asymmetric ion mobility spectrometry (FAIMS) was studied. Acetone, ethanol, and diethyl ether were selected as components of a ternary gas mixture sample as representatives of the ketone, alcohol, and ether chemical classes, respectively. One hundred and twenty-five points with different concentrations were measured. The results were evaluated by error hypersurface, variance, and the coefficient of variation. The error hypersurface showed that it is possible to reach the target composition by following the error-hypersurface gradient. Successful convergence was achieved with the gradient descent method in a simulation based on the measurement data. This result verified the feasibility of the quantification of a gas mixture using FAIMS.
Highlights
Gas mixture quantification is an essential technology for odor recording [1], since an odor consists of multiple chemical compounds
The learning rate was adaptively adjusted to reduce the number of iterations, and it was found that the number of iterations could be drastically decreased
This result suggests the feasibility of odor quantification in real time
Summary
Gas mixture quantification is an essential technology for odor recording [1], since an odor consists of multiple chemical compounds. Odor recorders and reproducers could be applied to various technical fields [2], if such devices were realized. They could be employed in teleolfaction [3], odors for virtual reality [4], etc. Gas chromatography–mass spectrometry (GC–MS) is generally used for gas quantification, since it can separate gases and detect low concentrations of gas. It is expensive and does not work in real time. It becomes difficult to determine the concentration of each gas because the QCM sensor array has a collinearity problem when the number of components in a gas mixture increases
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