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Quartz crystal nanobalance in conjunction with principal component analysis for identification and determination of Telone, Methyl Iodide, Endosulfan, and Methyl Bromide



This study reports the capability of a system based on single silicon OV-25 (a methylphenylsilicon (∼75% phenyl)) modified quartz crystal nanobalance (QCN) sensor with the application of principal component analysis (PCA) as a pattern recognition technique for the detection and determination of some organo-halide pesticides (Telone, Methyl Iodide, Endosulfan, and Methyl Bromide) in aqueous solutions. It was found that the sensor response is linear against the organo-halide pesticides in the concentration ranged between of 5–30 mg L−1 for Endosulfan and 5–60 mg L−1 for three other studied pesticides. The correlation coefficients (0.992, 0.989, 0.994, and 0.993), the sensitivity factors (2.27, 2.41, 3.61, and 1.44 Hz/mg L−1), and the lower limit of detections (1.4, 4.6, 2, and 4.6 mg L−1) were obtained for Telone, Methyl Iodide, Endosulfan, and Methyl Bromide, respectively. PCA has been performed based on the silicon OV-25-modified QCN sensor measurement results, and the signals were transformed into feature space. It was found that the transformed values of Telone, Methyl Iodide, Endosulfan, and Methyl Bromide were well separated. Thus, the developed QCN sensor has very good applicability to successfully determine organo-halide pesticides. Also, it was found that over 93.5% of the data variance could still be explained by using two principal components (PC1 and PC2). © 2013 American Institute of Chemical Engineers Environ Prog, 33: 267–274, 2014

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