Search

In this article, the ability of a new and efficient hard-soft method, previously proposed by our research group, is reported for modeling of the complex formation equilibria in the presence of interferences. This method is based on the net analyte signal (NAS) concept, which is a part of total signal that is directly related to the concentration of the component of interest. It monitors the concentration changes of any chemical species involved in the evolutionary process without requiring any pure spectra or having previous knowledge about the presence of the interferences. The proposed hard-soft method based on net analyte signal (HS-NAS) only needs a chemical model for one of the species involved in the reaction under study. The reliability of the method was examined by applying it to the measured data and spectrum of the known real systems of Fe(2+)-azithromycin and Ca(2+)-tetracycline., (Copyright © 2010 Elsevier B.V. All rights reserved.)

In this paper, partitioning behaviors of typical neutral (Alanine), acidic (Glutamic acid) and basic (Lysine) amino acids into imidazolium-based ionic liquids [C(4)mim][PF(6)], [C(6)mim][PF(6)], [C(8)mim][PF(6)], [C(6)mim][BF(4)] and [C(8)mim][BF(4)] as extracting solvents were examined. [C(6)mim][BF(4)] showed the best efficiency for partitioning of amino acids. The partition coefficients of amino acids in ionic liquids were found to depend strongly on pH of the aqueous solution, amino acid and ionic liquid chemical structures. Different chemical forms of amino acids in aqueous solutions were pH dependent, so the pH value of the aqueous phase was a determining factor for extraction of amino acids into ionic liquid phase. Both water content of ionic liquids and charge densities of their anionic and cationic parts were important factors for partitioning of cationic and anionic forms of amino acids into ionic liquid phase. Extracted amino acids were back extracted into phosphate buffer solutions adjusted on appropriate pH values. The results showed that ionic liquids could be used as suitable modifiers on the stationary phase of an HPLC column for efficient separation of acidic, basic, and neutral amino acids.

In this paper, imidazolium-based ionic liquids [C(4)mim][PF(6)], [C(6)mim][PF(6)], [C(8)mim][PF(6)], [C(6)mim][BF(4)] and [C(8)mim][BF(4)] were tested as extracting solvents for removal of 3-indole butyric acid (IBA) from aqueous media with subsequent determination using HPLC. Percent extraction of IBA was strongly affected by pH of aqueous phases and the chemical structures of ionic liquids (ILs). Extraction of IBA was quantitative in the pH values lower than pK(a) of IBA. Considering both extraction and stripping efficiencies of IBA, [C(4)mim][PF(6)] was found to act more efficient than other studied ILs. Capacity of [C(4)mim][PF(6)] was 17.6x10(-4)mmol IBA per 1.0 mL of IL. Ionic strength of aqueous phase and temperature had shown no serious effects on extraction efficiency of IBA. A preconcentration factor of 100 and a relative standard deviation of 1.16% were obtained. It was found that ionic liquid phase was reusable almost five times for extraction/stripping purposes. 3-Indole acetic acid showed interferential effect in the extraction step. In order to assess the applicability of the method, extraction and stripping of IBA from pea plants and some other samples were studied.

A new ammonia optical sensor was designed using bis(acetylacetoneethylendiamine)tributylphosphin cobalt(III) tetraphenylborate complex, coated on transparent triacetylcellulose film as membrane. The change in the absorbance of the optode at the maximum wavelength of 408 nm was related to ammonia concentration in aqueous samples. A buffer solution with a pH of 9 (sodium borate-HCl) was used. The optode was fully regenerated in pH 2. The linear dynamic range for determination of ammonia was 3.3 x 10(-4) to 6.9 x 10(-3) mol l(-1) with a detection limit of 5.0 x 10(-5) mol l(-1) and a response time range of 4 - 6 min. This membrane was successfully applied for determination of ammonia in drinking water.

A specterophotometric method for simultaneous determination of aniline and cyclohexylamine using principal component artificial neural networks is proposed. This method is based on the reactions involving aniline and/or cyclohexylamine, with bis(acetylacetoneethylendiamine)tributylphosphine cobalt(III) perchlorate as a complexing reagent. A nonionic surfactant, Triton X-100, was used for dissolving the complexes and intensifying the signals. The absorption data were based on the spectra registered in the range of 350 - 550 nm. An artificial neural network consisting of three layers of nodes was trained by applying a back-propagation learning rule. Sigmoid transfer functions were used in the hidden and output layers to facilitate nonlinear calibration. The predictive ability of artificial neural networks was examined for the determination of aniline and cyclohexylamine in synthetic mixtures.

Determination of V(IV) based on its catalytic effect on the reaction between Methyl Orange and bromate in thepresence of citric acid was studied. The calibration curve obtained by fixed-time method was linear in the range of 2.5-300 ng ml(-1). By use of slope method, a calibration curve containing two linear portions were obtained. Using fixed-time and slope methods, we obtained detection limits of 0.8 and 1.5 ng ml(-1), respectively. Fe2+, As(III), V(V) and Hg2+ interfered. The method was successful for analysis of water samples.