Quartz crystal microbalance sensor array for the detection of volatile organic compounds

A sensor array system consisting of five quartz crystal microbalance (QCM) sensors (four for measuring and one for reference) and an artificial neural network (ANN) method is presented for on-line detection of volatile organic compounds. Three ionic liquids, 1-butyl-3-methylimidazolium chloride (C 4...

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Bibliographic Details
Published in:Talanta (Oxford) 2009-05, Vol.78 (3), p.711-716
Main Authors: Xu, Xiuming, Cang, Huaiwen, Li, Changzhi, Zhao, Zongbao K., Li, Haiyang
Format: Article
Language:English
Subjects:
Acetone - analysis
Analytical chemistry
Artificial neural network
Chemistry
Chromatographic methods and physical methods associated with chromatography
Ethanol - analysis
Exact sciences and technology
Gas chromatographic methods
General, instrumentation
Ionic Liquids
Methylene Chloride - analysis
Micro-Electrical-Mechanical Systems
Quartz crystal microbalance
Sensor array
Toluene - analysis
Volatile organic compounds
Volatile Organic Compounds - analysis
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Summary:A sensor array system consisting of five quartz crystal microbalance (QCM) sensors (four for measuring and one for reference) and an artificial neural network (ANN) method is presented for on-line detection of volatile organic compounds. Three ionic liquids, 1-butyl-3-methylimidazolium chloride (C 4mimCl), 1-butyl-3-methylimidazolium hexafluorophosphate (C 4mimPF 6), 1-dedocyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (C 4mimNTf 2), and silicone oil II, which is widely used as gas chromatographic stationary phase, have been selected as sensitive coatings on the quartz surface allowing the sensor array effective to identify chemical vapors, such as toluene, ethanol, acetone and dichloromethane. The success rate for the qualitative recognition reached 100%. Quantitative analysis has also been investigated, within the concentration range of 0.6–6.1 mg/L for toluene, 0.9–7.5 mg/L for ethanol, 2.8–117 mg/L for dichloromethane, and 0.7–38 mg/L for acetone, with a prediction error lower than 8%.
ISSN:0039-9140
1873-3573
DOI:10.1016/j.talanta.2008.12.031