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. 2021 Jul 30;9(8):201.
doi: 10.3390/chemosensors9080201.

Ionogels Based on a Single Ionic Liquid for Electronic Nose Application

Affiliations

Ionogels Based on a Single Ionic Liquid for Electronic Nose Application

Wellington B Gonçalves et al. Chemosensors (Basel). .

Abstract

Ionogel are versatile materials, as they present the electrical properties of ionic liquids and also dimensional stability, since they are trapped in a solid matrix, allowing application in electronic devices such as gas sensors and electronic noses. In this work, ionogels were designed to act as a sensitive layer for the detection of volatiles in a custom-made electronic nose. Ionogels composed of gelatin and a single imidazolium ionic liquid were doped with bare and functionalized iron oxide nanoparticles, producing ionogels with adjustable target selectivity. After exposing an array of four ionogels to 12 distinct volatile organic compounds, the collected signals were analyzed by principal component analysis (PCA) and by several supervised classification methods, in order to assess the ability of the electronic nose to distinguish different volatiles, which showed accuracy above 98%.

Keywords: composite; electronic nose; gas sensor; ionic liquid; ionogel; volatile organic compound.

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Conflict of interest statement

Conflicts of Interest: The authors declare no conflict of interest.

Figures

Figure 1
Figure 1. Interdigitated electrode used in the preparation of the gas sensors.
Figure 2
Figure 2. Schematic representation ol the electronic nose assembled.
Figure 3
Figure 3
Response of set A sensors to eight exposure (5 s)/recovery (100 s) cycles to ethanol vapors, doped with different concentrations of Fe3O4: (blue) pure ionogels, (orange) 25 mg/mL, (green) 50 mg/mL and (red) 75 mg/mL.
Figure 4
Figure 4
FTIR spectra of bare Fe3O4 particles (magenta) and of functionalized Fe3O4 particles with AA (blue), OA (red), and LA (black).
Figure 5
Figure 5. Relative responses of set A sensors upon 10 cycles of exposure to VOCs.
Figure 6
Figure 6. Responses of set B sensors upon 10 cycles of exposure to VOCs.
Figure 7
Figure 7
PCA scatter plots indicating the variance of each component (in brackets) for the VOCs tested (PC = principal component); (A) with set A sensors and (B) with set B sensors.
Figure 8
Figure 8
Loading plot showing the contribution of each sensor in the both sets for the principal components, (A) with set A and (B) with set B.
Figure 9
Figure 9. Comparison of the accuracies of the different classifiers used for set A and set B sensors.
Figure 10
Figure 10
Confusion matrices of the Random SubSpace classifier applied in the predictions of VOCs (A) in set A sensors and (B) in set B sensors.

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