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Online coupling of in-tube solid phase micro-extraction (IT-SPME) with direct analysis in real time mass spectrometry (DART-MS) was realized for the first time and applied in the analysis of triazine herbicides in lake water and orange juice. We incorporated single-wall carbon nanotubes (SWNTs) into a polymer monolith containing methacrylic acid (MAA) and ethylene dimethacrylate (EDMA) to form a novel poly(mefhacrylic add-co-ethylene dimethacrylate-co-single wall carbon nanotubes) (poly(MAA-EDMA-SWNT)) monolith, which was then used in IT-SPME for enrichment of six triazine herbicides from water samples. With the online combination of IT-SPME with DART-MS, the analytes desorbed from the monolith were directly ionized by DART and transferred into MS for detection, thus rapid determination was achieved. Compared with regular DART-MS method, this online IT- SPME-DART-MS method was more sensitive and reproducible, because of the IT-SPME procedures and the isotope-labeled internal standard used in the experiment. Six triazine herbicides were determined simultaneously using this method with good linearity (R2 > 0.998). The limit of quantification (signal-to-noise ratio of S/N = 10) of the six herbicides were only 0.06-0.46 ng/mL. The proposed method has been applied to determine triazine herbicides in lake water and orange juice, showing satisfactory recovery (85%-106%) and reproducibility (relative standard deviation of RSD = 3.1%-10.9%). [ABSTRACT FROM AUTHOR]

A cross-reactive chemiluminescence (CL) sensor array based on catalytic nanomaterials was constructed for the discrimination and identification of flavors in cigarettes. A total of 21 nanomaterials, including metal oxides, metal oxides deposited on carbon nanotubes (CNTs), gold nanoparticles deposited on metal oxides, and carbonate, have been carefully selected as sensing elements of the array. Each flavor gives its unique CL pattern from the array, which is able to be employed for the discrimination and identification of flavors. Hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA) were used to analyze the patterns. The obtained CL patterns are temperature dependent, thus additional discrimination power could be provided by changing the working temperature of the array. Quantification of the flavors has been performed according to the emission intensity on the specific sensing element. The linear ranges of the sensor array for the flavors are in the range of 20-2000 ppmv with the limits of detection below 10 ppmv, which vary with the kinds of flavors. Six brands of cigarettes have been discriminated by their CL patterns obtained with the present sensor array. The robust and reversible response of this array, combined with its simple instrumentation, indicates the promise of this array for real world application. [ABSTRACT FROM AUTHOR]