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Published on: January 22, 2020
Classification of Volatile Organic Compounds Using a Novel High-Frequency Quartz Crystal Microbalance Sensor Array
Ian Chuey-Mendoza1, Severino Muñoz-Aguirre1, Isis I Ramírez-Valdés1
1Facultad de Ciencias Físico-Matemáticas, Benemérita Universidad Autónoma de Puebla, Avenida San Claudio y 18 Sur, Colonia San Manuel, Edificio FM1-101B, Ciudad Universitaria, Puebla C.P. 72570, Mexico.
Abstract:
Detecting volatile organic compounds (VOCs) is essential because they affect air quality and can serve as biomarkers for non-invasive early disease detection. VOCs can be identified using electronic noses combining cross-reactive sensors, pattern recognition, and classification algorithms. Here, a single-polymer 12-sensor array based on 30 MHz quartz crystal microbalances was developed using three ethyl cellulose (EC) microstructures: casting films (CFs), anti-solvent microparticles (ASMs), and electrospray microparticles (ESMs). The array detected ethanol, ethyl acetate, and heptane at ppm concentrations under controlled conditions of 20 °C and 20% relative humidity. Scanning electron micrographs exhibited average mesh-hole diameters of 1.13 ± 0.44 μm for CFs, and average particle diameters of 60 ± 15 nm and 1.1 ± 0.3 μm for ASMs and ESMs, respectively. FTIR spectra indicated O-H and H-O-H bending bands for ASMs and EC, whereas these bands were notably attenuated for ESMs, suggesting their affinities for polar and non-polar compounds, respectively. Mahalanobis distance and a support vector machine classifier accurately discriminated VOCs in principal component analysis space. Principal component regression and partial least squares regression predicted VOC concentrations with R2 > 0.99, achieving estimated limits of detection of 143.6, 57, and 42.1 ppm by PCR and 70.5, 32.8, and 26.5 ppm by PLSR for ethanol, ethyl acetate, and heptane, respectively.

