We report on the detection of acetone at low concentrations using a W18O49-based gas sensor operating at room temperature (RT). W18O49 was synthesized using the solvothermal method, yielding nanoparticles along with sparsely separated nanorods. The intrinsic properties (i.e., crystal structure, morphology, and defect states) of the W18O49 were examined. While operating at RT, the W18O49-based gas sensor demonstrated superior behavior to acetone among eight (8) other tested gases (ethanol, methanol, m-xylene, p-xylene, o-xylene, benzene, CO, and NO2). The sensor was exposed to a minimal concentration of 0.08 ppm acetone, resulting in a response (Ra/Rg) of 1.04. At 1.8 ppm, the response was 1.49, respectively. The repeatability measurements at 1.8 ppm revealed that the sensor could output a constant response over multiple cycles, with a standard deviation in the spread of the data of 0.1 ppm. Relative humidity (RH) measurements indicated that the sensor performed optimally in humid conditions, suggesting that humidity acted as a catalyzing agent. The sensor displayed the best responses to acetone at lower concentrations than the other gases. The underlying data was then used for Principal Component Analysis (PCA) analysis and the k-Nearest Neighbor (kNN) algorithm. The PCA plot of the sensor responses clearly showed well-separated clusters for the tested gases, indicating that the W18O49-based sensor produced distinct response patterns suitable for data-driven classification. Then, the PCA-kNN classification algorithm achieved a recognition accuracy of 93%, confirming the sensor system's excellent ability to differentiate acetone from other VOCs, even at trace levels. This highlights the benefit of combining nanostructured W18O49 sensing materials with Machine-Learning tools for reliable VOC detection in complex environments. Density Functional Theory analysis was then performed to understand the affinity of the sensor towards acetone compared to the other gases tested. Finally, a proposed sensing mechanism was discussed in detail.
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