Electrical interaction between two cylinders with an ion-penetrable charged membrane in an oil/water interface

The electrical interaction between two long, parallel cylinders each is covered by an ion-penetrable charged membrane immersed in an oil/water interface is investigated. The effects of contact angle, radius of cylinder, and membrane thickness on the electrical interaction force are examined. The results of numerical simulation reveal that the following conditions lead to a greater electrical interaction force: (i) a larger contact angle, i.e. a larger fraction of a cylinder in the oil phase; (ii) a larger cylinder radius; and (iii) a thinner membrane. For a fixed ionic strength, the electrical interaction force is insensible to the type of electrolytes in the water phase, in general. However, if two cylinders are close enough, then the higher the valence of counterions the greater the electrical interaction force.     

Impact of micelles on the biocidal efficiency in a diesel–water interface

Biodegradation occurs in the diesel/water interface in petroleum product pipelines. The microbial contamination can result in inhibitor/fuel degradation, leading to unacceptable levels of turbidity, filter plugging, storage tank corrosion and stored product souring. Therefore, selection of the biocide/inhibitor plays an important role in the transportation of petroleum products through pipelines. Three biocides (cationic and nonionic) were employed to study the biodegradation in a diesel‐water interface. The biocidal efficiency against degradation of diesel was examined by employing Fourier‐transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR) spectroscopy and gas chromatography mass spectrometry (GC‐MS) techniques. Bronopol (2‐bromo‐2‐nitro‐propane‐1, 3‐diol) was found to have higher bactericidal efficiency than N‐cetyl‐N,N, N‐trimethyl ammonium bromide (CTAB) and cetyl pyridinum bromide (CPB). But the cationic biocides (CTAB and CPB) showed good biocidal efficiency at the interface. The data are explained in terms of a model that postulates the formation of a ‘micelle’ at the diesel‐water interface. Copyright © 2007 John Wiley & Sons, Ltd.     

Modeling of the relationship between electroosmotic flow and separation parameters in capillary zone electrophoresis using artificial neural networks and experimental design

The prediction of migration time of electroosmotic flow (EOF) marker was achieved by applying artificial neural networks (ANN) model based on principal component analysis (PCA) and standard normal distribution simulation to the input variables. The voltage of performance, the temperature in the capillary, the pH and the ionic strength of background electrolytes (BGE) were applied as the input variables to ANN. The range of the performance voltage studied was from 15 to 27 kV, and that of the temperature in the capillary was from 20 to 30 °C. For the pH values studied, the range was from 5.15 to 8.04. The range of the ionic strength investigated in this paper was from 0.040 to 0.097. The prediction abilities of ANN with different pre-processing procedure to the input variables were compared. Under the same performance conditions, the average prediction error of the migration time of the EOF marker was 5.46% with RSD = 1.76% according to 10 parallel runs of the optimized ANN structure by the proposed approach, and that of the 10 parallel predictions of the optimal ANN structure for the different performance conditions was 12.95% with RSD = 2.29% according to the proposed approach. The study showed that the proposed method could give better predicted results than other approaches discussed.     

All-glass open-split interface for capillary GC/MS

This paper describes a design for an all-glass GC/MS interface. The design has advantages due to low dead volume, lack of column effluent adsorption and degradation, simple interface production and installation, and ease of column mounting/dismounting.     

The Electrochemistry of Tetraphenyl Porphyrin Iron(III) Within Immobilized Droplets Supported on Platinum Electrodes

For the first time, the voltammetry of an ensemble of immobilized benzonitrile microdroplets containing 5,10,15,20‐tetraphenyl‐21H,23H‐porphine iron (III) chloride, TPPFeCl immobilized at platinum electrodes immersed in various aqueous electrolytes has been explored. The reduction of TPPFeCl was observed with the voltammetric response seen to be highly dependent on the nature of ions in the surrounding aqueous phase. Unlike voltammetry in purely homogeneous solution the nature of the aqueous electrolyte can influence the voltammetry in the droplet phase. The electrochemical reduction of TPPFeCl contained within tetrabutylammonium chloride (TBACl) supported benzonitrile (PhCN) microdroplets immersed into an aqueous solution of TBACl was first studied. During TPPFeCl reduction the resulting [TPPFeCl]^? species is stabilized due to the excess of chloride anions inside the oil droplet. Voltammograms of homogeneous solutions of PhCN supported with TBACl show similar chemically reversible process which is also attributed to the stable [TPPFeCl]^? species. This anion stabilization was not observed when the oil droplets were supported with tetrabutylammonium perchlorate (TBAP) or when the PhCN solution bathing the microdroplet ensemble was supported with TBAP resulting in a chemically irreversible process. The voltammetry of unsupported droplets immobilized on a platinum electrode immersed in different aqueous electrolytes was also explored and the fate of the [TPPFeCl]^? species formed considered during the reduction sweep. Similarities and difference to voltammetry in purely homogeneous media are noted and the use of droplet voltammetry provides complimentary information.     

Optimization of the Microwave-Assisted Saponification and Extraction of Organic Pollutants from Marine Biota Using Experimental Design and Artificial Neural Networks

Several improvements in sample pretreatment for the determination of organic pollutants (i.e. n-alkanes, polycyclic aromatic hydrocarbons, PAHs) in marine biota (mussels) are presented. The use of liquid nitrogen and homogenization of the samples are shown to be an alternative to the time consuming liophilization step required for the analysis of biota samples. Microwave-assisted hydrolysis and extraction are combined to isolate organic pollutants (19 n-alkanes and 27 PAHs) from biota matrices. Experimental design (ED) and artificial neural networks (ANNs) were used to optimize the experimental conditions. NIST-CRM 2978 was used to test the validity of the developed method which shows a good agreement with certified values.     

Application of an artificial neural network (ANN) and piezoelectric chemical sensor array for identification of volatile organic compounds

A piezoelectric chemical sensor array was developed using four quartz crystals. Gas chromatographic stationary phases were used as sensing materials and the array was connected to an artificial neural network (ANN). The application of the ANN method proved to be particularly advantageous if the measured property (mass, concentration, etc.) should not be connected exactly to the signal of the transducers of the piezoelectric sensor. The optimum structure of neural network was determined by a trial and error method. Different structures were tried with several neurons in the hidden layer and the total error was calculated. The optimum values of primary weight factors, learning rate (η=0.15), momentum term (μ=0.9), and the sigmoid parameter (β=1) were determined. Finally, three hidden neurons and 900 training cycles were applied. After the teaching process the network was used for identification of taught analytes (acetone, benzene, chloroform, pentane). Mixtures of organic compounds were also analysed and the ANN method proved to be a reliable way of differentiating the sensing materials and identifying the volatile compounds.     

Effects of amino acids on crystal growth of CaC2O4 in reverse microemulsion

Crystal growth of calcium oxalate (CaC2O4) in bulk aqueous solution, reverse microemulsion of p-octyl polyethylene glycol phenylether (OP)/iso-octyl alcohol (IOA)/cydohexane/water and above microemulsions containing different kinds of amino acids, such as aspartic acid (Asp), tyrosine (Tyr) and tryptophan (Trp) were studied. The results indicated that different crystallization types of the crystals, which were calcium oxalate monohydrate (COM), calcium oxalate dihydrate (COD) and calcium oxalate trihydrate (COT), existed in bulk aqueous solution. But CaC2O4 growth mainly paralleled with (1 01) plane of COM in reverse microemulsion because of the induction of surfactant at water/oil interface. After adding amino acids into microemulsions, the growth of CaC2O4 crystals mainly influenced by the varieties of amino acids and the pH values of the amino acid aqueous solution. When pH values of the solutions was higher than isoelectric points of amino acids, CaC2O4 crystal paralleled with (1 01) plane of COM more easily with the addition of Trp, Tyr, Asp in turn; however, when pH of the solutions was lower than isoelectric points of Trp, CaC2O4 crystal growth paralleled with (020) face of COM. It is obviously that amino acids, pH values of the solutions and surfactant played important roles in the process of crystal growth of CaC2O4 in the microemulsions. The formation mechanism of CaC2O4 was also discussed in different microemulsions at last.     

Sequential injection system with higher dimensional electrochemical sensor signals Part 1. Voltammetric e-tongue for the determination of oxidizable compounds

A sequential injection analysis (SIA) system was developed with the aim of obtaining an automatic and versatile way to prepare standards needed in the study of systems with higher dimensional sensor signals. To illustrate this, different analytical techniques were used in determinations of several analytes. Automated potentiometric calibrations of different potentiometric sensors, with and without interference, were carried out. Useful determinations of selectivity coefficients with two degrees of freedom were obtained. Simultaneous voltammetric determinations have also been done. Firstly, simultaneous determinations of lead and cadmium, using epoxy-graphite composite as the working electrode, have enabled a separate calibration for each metal to be obtained. Next, a voltammetric electronic tongue was designed and applied to the determination of oxidizable species. The use of artificial neural networks has solved the overlapped signal of ascorbic acid, 4-aminophenol and 4-acetamidophenol (paracetamol). A set of 63 data points was prepared automatically and has facilitated the training of an electronic tongue for these three analytes. Accurate predictions of test solutions, in the range of 12–410 μM for ascorbic acid, 17–530 μM for 4-aminophenol and 10–420 μM for paracetamol, have been achieved with RMSEs lower than 0.10 μM.     

Fluorescence optosensor using an artificial neural network for screening of polycyclic aromatic hydrocarbons

This paper presents an optosensor for screening of four polycyclic aromatic hydrocarbons: anthracene (ANT), benzo[a]pyrene (BaP), fluoranthene (FLT), and benzo[b]fluoranthene (Bbf) using a photomultiplier device with an artificial neural network as transducer. The optosensor is based on the on-line immobilization on a non-ionic resin (Amberlite XAD-4) solid support in a continuous flow. The determination was performed in 15 mM H₂PO₄⁻/HPO₄²⁻ buffer solution at pH 7 and 25% of 1,4-dioxane. Feed forward neural networks (multiplayer perceptron) have been trained to quantify the considered Polycyclic aromatic hydrocarbons (PAHs) in mixtures under optimal conditions. The optosensor proposed was also applied satisfactorily to the determination of the considered PAHs in water samples in presence of the other 12 EPA–PAHs.