Polymer coated sensor array based on quartz crystal microbalance for chemical agent analysis
Introduction
Chemical agent defines as a chemical substance that has the potential to cause physical and/or physiological changes for human being, animal and their habitation. The intentional use of chemical agents for war and terrorism has created an imperative for the development of rapid detection and sensitive analytical method and apparatus. The horrific terrorism attack of 9-11-2001 in USA as well as in several other countries in recent years have greatly spurred that urgency [1], [2]. The current sensing systems can range from a sophisticated GC–MS to an array of simple chemical sensors. Among all kinds of sensors, quartz crystal microbalances (QCMs) sensor has attracted great attention for its low cost, compact volume, easy portability and high sensitivity [3], [4], [5].
As well known, the relation between mass changes Δm (g) due to absorbed/desorbed gas molecules and frequency shifts Δf (Hz) follows Sauerbrey equation [5], [6], [7]where F (Hz) is fundamental resonance frequency, and A (cm2) is sensing surface area. Selectivity, as well as the response time, stability and reproducibility of chemical sensors, has been a drawback to overcome. To compensate for the deficiency of selectivity, pattern recognition approaches have been applied using an array of various sensors [6], [7], [8], [9], [10], [11], [12]. Also, many researches carried out an array of QCMs for those advantages [9], [10].
In this study, by applying the principal component analysis (PCA) and hierarchical cluster analysis to a data set containing frequency shifts measured in response to analytes adsorbing on specific candidate coating materials, a reduced set of coatings for obtaining the maximum discriminating information of all analytes were attempted. And the sensing properties of the chemical agents were investigated using four simulant gases of dimethyl methyl phosphonate (DMMP), N,N-dimethyl acetamide (DMA), 1,5-dichloropentane (DCP) and 1,2-dichloroethane (DCE).
Section snippets
Reagents and materials
The vapors used listed in Table 1. The volatile organic solvents were all analytical reagent grade reagents: DMMP (97%, Aldrich); DCP 98%, 2,2′-thiodiethanol 99% (Alfa Aesar); DCE, DMA, cyclohexanone, hexane, ethanol, acetone; isopropanol, isooctane, ethyl acetate and acetic acid (all from Kelong, China). All solvents were used as received without further purification. Ultrapure water (18 MΩ cm) was used throughout all processes.
The coating materials were as follows: poly(isobutylene) (PIB),
Results and discussion
Theoretically, using more sensors to obtain as many as parameters provides more information to verify the analysis for unknown chemical vapors. In practical application, it is more cost-effective and convenient if fewer sensors can be applied to represent a maximal variance of unknown chemicals. To select a minimum number of sensors that adequately describe different chemicals in the samples, we applied for PCA and hierarchical cluster analysis methods.
Conclusion
Pattern recognition techniques were applied to frequency shift data obtained from 15 QCM sensors, formed by coating with 15 different materials, and tested using 12 analytes. The objective to use a subset of coatings without a significant loss of analytes identification information was achieved. The first four principal components described almost 92.1% of the variance in original data set of 15 coatings. And the hierarchical cluster analysis verified the results of PCA, which proved that PCA
Acknowledgement
This work was partially supported by National Science Foundation of China via Grant Nos. 60425101, 60736005 and Program for New Century Excellent Talents in University via Grant No. NCET-06-0812.
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