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Capillary electrophoresis determinations of trace concentrations of inorganic ions in large excess of chloride: Soft modelling using artificial neural networks for optimisation of electrolyte composition

Citation

Muzikar, M and Havel, J and Macka, M, Capillary electrophoresis determinations of trace concentrations of inorganic ions in large excess of chloride: Soft modelling using artificial neural networks for optimisation of electrolyte composition, Electrophoresis, 24, (12-13) pp. 2252-2258. ISSN 0173-0835 (2003) [Refereed Article]

DOI: doi:10.1002/elps.200305416

Abstract

In this work, using a combination of experimental design (ED) and artificial neural networks (ANN), the composition of a triethanolamine-buffered chromate electrolyte was optimised for determination of sulphate anions in the presence of high chloride excess. The optimal electrolyte, allowing a baseline-resolved separation of sulphate from chloride present in a 1500 multiple excess in less than 170 s, consists of 10 mmol/L CrO3, 2 mmol/L hexamethonium hydroxide, 10% methanol, and triethanolamine added to adjust the pH to 8.0. The method is suitable to a wide concentration range of chloride (4-1757 mg/L) and sulphate (4-590 mg/L) with linear calibration plots (R2 = 0.9937-0.9999). Relative standard deviations are less than 2.0% for both anions for migration times and peak areas. The detection limits (hydrodynamic injection of 1 s) were 0.6 mg/L for sulphate and 0.5 mg/L for chloride. The method was successfully applied to determination of sulphate in mineral waters containing a high chloride concentration and to determination of sulphate traces in an anticancer drug injection preparation containing a physiological level of chloride. It was shown that α-cyclodextrin as an electrolyte additive has a significant potential for further increasing the separation selectivity for inorganic anions.

Item Details

Item Type:Refereed Article
Research Division:Chemical Sciences
Research Group:Analytical Chemistry
Research Field:Separation Science
Objective Division:Expanding Knowledge
Objective Group:Expanding Knowledge
Objective Field:Expanding Knowledge in the Chemical Sciences
Author:Macka, M (Professor Mirek Macka)
ID Code:27359
Year Published:2003
Web of Science® Times Cited:8
Deposited By:Chemistry
Deposited On:2003-08-01
Last Modified:2011-10-03
Downloads:0

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