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This digital document is a journal article from Analytica Chimica Acta, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
The feasibility of using sol-gel amorphous titania (TiO"2) as a solid-phase sorbent for the pre-concentration of domoic acid (DA), a potent amnesic shellfish poisoning (ASP) toxin, directly from seawater was explored. The sol-gel titania material is able to adsorb DA from seawater, via the formation of ester-linkage between the carboxylic moieties of DA and the Ti-OH groups on the sorbent surface, at low pH and desorb it at high pH. The chemisorption process is not significantly interfered by the seawater matrix. The optimum pH values for the adsorption and desorption of DA were found to be pH 4 and 11, respectively. The optimal sorbent loading for the batch-type solid-phase extraction of DA was 0.67mg-TiO"2ng-DA^-^1 and adsorption equilibrium was achieved in 2h at room temperature. The desorbed DA in 500@mL of 0.1M alkaline borate buffer can be directly derviatized by 4-fluoro-7-nitro-2,1,3-benzoxadiazole (NBD-F) in aqueous media for fluorimetric HPLC quantification. Analyte recovery, repeatability and detection limit of this titania SPE-fluorimetric HPLC determination are 89%, 6.2% and 120pg-DAmL^-^1 (n=7, P<0.05), respectively, for a sample volume of 30mL. This titania SPE technique should also be applicable to the pre-concentration of other polar carboxylate- and phosphonate-containing biomolecules and pharmaceuticals in complex and interfering environmental sample matrices. .
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This digital document is a journal article from Analytica Chimica Acta, published by Elsevier in . The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
In the analysis of an environmental disaster caused by spillage of crude oil, limitation of the possible sources to a few geographical origins can help in the identification of the polluting vessel from a group of potential candidates. In this paper we show that Kohonen self-organizing maps (or Kohonen neural networks) can classify samples of crude oils on the basis of gas chromatography-mass spectrometry (GC-MS) descriptors, in terms of geographical origin, with a high degree of accuracy. Two data sets were investigated - one from Instituto Hidrografico (Lisbon, Portugal) with 188 samples from 20 geographical origins, and another from EUROCRUDE^(R) with 374 samples. After training the Kohonen self-organizing maps with a training set, predictions were obtained for an independent test set. Correct predictions were obtained for 70% and 60% of the test sets for the two studies, respectively. Ensembles of networks were highly interesting for the calculation of a prediction score, which can be used as a measure of the reliability of the prediction. For the samples with high prediction scores, the percentage of correct predictions jumped to 94-96%. The ability of the maps to identify a given origin is very much dependent on the availability of samples from that class in the training set. Equally good predictions were obtained for a small test set of weathered samples. This investigation adds value to the GC-MS descriptors already in use for practical analytical work, suggesting new ways to ferret out useful knowledge from them. .
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This digital document is a journal article from Analytica Chimica Acta, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
In this work it has been shown that the routine ASTM methods (ASTM 4052, ASTM D 445, ASTM D 4737, ASTM D 93, and ASTM D 86) recommended by the ANP (the Brazilian National Agency for Petroleum, Natural Gas and Biofuels) to determine the quality of diesel/biodiesel blends are not suitable to prevent the adulteration of B2 or B5 blends with vegetable oils. Considering the previous and actual problems with fuel adulterations in Brazil, we have investigated the application of vibrational spectroscopy (Fourier transform (FT) near infrared spectrometry and FT-Raman) to identify adulterations of B2 and B5 blends with vegetable oils. Partial least square regression (PLS), principal component regression (PCR), and artificial neural network (ANN) calibration models were designed and their relative performances were evaluated by external validation using the F-test. The PCR, PLS, and ANN calibration models based on the Fourier transform (FT) near infrared spectrometry and FT-Raman spectroscopy were designed using 120 samples. Other 62 samples were used in the validation and external validation, for a total of 182 samples. The results have shown that among the designed calibration models, the ANN/FT-Raman presented the best accuracy (0.028%, w/w) for samples used in the external validation. .
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This digital document is a journal article from Analytica Chimica Acta, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
Methylene blue (MB) was strongly retained inside the cavity of host layered barium phosphate, without leaching, and the intercalated compound was characterized through X-ray power diffraction (XRD), IR spectra and electrochemical measurements. The intercalated dye compound was incorporated into a carbon paste electrode and, by means of cyclic voltammetry and amperometry, its electrochemical properties were investigated. In various electrolyte solutions, changing the pH between 3 and 9, the midpoint potential remained practically constant at -0.15V. This is not the usual behavior for MB, since it is known that in the solution phase the midpoint potential changes considerably with pH. These data suggest that methylene blue behaves as a guest molecule in the lamellar structure of the barium phosphate. The electrode formed by this host/guest composition was used to investigate NADH electrochemical oxidation. .
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This digital document is a journal article from Analytica Chimica Acta, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
A novel method for determination of mercury was developed using an intermittent flow electrochemical cold vapor generation coupled to atomic fluorescence spectrometry (IF-ECVG-AFS). The mercury vapor was generated on the surface of glassy carbon cathode in the flow cell. The operating conditions for the electrochemical generation of mercury vapor were investigated in detail, and the interferences from various ions were evaluated. Under the optimized conditions, no evident memory effects of mercury were observed. The calibration curve was linear up to 5@mgL^-^1Hg at 0.54Acm^-^2. A detection limit of 1.2ngL^-^1 Hg and a relative standard deviation of 1.8% for 1@mgL^-^1 Hg were obtained. The accuracy of method was verified by the determination of mercury in the certified reference human hair. The ECVG avoided the use of reductants, thereby greatly reducing the contamination sources. In addition, the manifold of IF-ECVG-AFS was simple and amenable to automation. .
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