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This study addresses the two major problems in the use of dyes as highly absorbing probes for indirect photometric detection in capillary electrophoresis (CE). First, effective electroosmotic flow (EOF) modification or suppression to allow separation and detection of a wide mobility range of analytes is not straightforward when electrolytes containing increased dye concentrations are used. The suppression of EOF to less than + 5x10(-9) m(2)V(-1)s(-1) was achieved with a combination of a poly(ethylenimine) (PEI)-coated capillary and the addition of the neutral polymer hydroxypropylmethylcellulose (HPMC) to the background electrolyte. Second, the deterioration of baselines due to adsorption of the dye probe to the capillary wall is generally a problem. In this work, baseline quality at higher probe concentrations was significantly improved by a rather unusual but highly effective combination of a simultaneous application of a slight overpressure (25 mbar) at the injection end during the separation, and the use of a relatively narrow capillary of 50 microm inner diameter. Both measures would appear to be counterproductive. Optimisation of the probe concentration with regard to signal-to-noise ratio resulted in an electrolyte of 4 mM Orange G, 0.05% HPMC buffered at pH 7.7 by the addition of 10.0 mM histidine isoelectric buffer. Very high separation efficiencies of 128 000-297 000 plates were made possible by the relatively high probe concentration. Combined with excellent detection sensitivity, even with the introduction of hydrodynamic flow and a reduced optical path length, these measures resulted in limits of detection ranging from 0.216 to 0.912 microM with a deuterium lamp light source (248 nm) and from 0.147 to 0.834 microM with a 476 nm blue light-emitting diode (LED) light source. Reproducibility over 30 consecutive runs without changing the electrolyte was excellent, with relative standard deviation (RSD) values of 0.14-0.80% for migration time, 1.27-3.36% for peak area and 0.88-5.12% for peak heights. The optimised electrolyte was used for the analysis of inorganic anions in air filter samples, providing good agreement with results obtained by ion chromatography.

A new software package, Virtual Column 2, is described for the simulation and optimization of the separation of inorganic anions by ion chromatography (IC). The software uses a limited amount of experimental retention data acquired according to a correct experimental design to predict retention times for analytes over a designated search area of eluent compositions. The experimental retention data are used to solve a new retention model, called the linear solvent strength model, empirical approach (LSSM-EA), which then enables prediction of retention times for all eluent compositions in the search area. The theoretical development of LSSM-EA and the processes used for solving the equations are discussed. Virtual Column 2 can be used for eluents containing one or two competing ions, and the software contains retention databases for up to 33 analytes on the Dionex AS9A-HC, AS4A-SC, and AS14A analytical columns with carbonatebicarbonate eluents and the Dionex AS10, AS15, and AS16 analytical columns with hydroxide eluents (results for the AS10 and AS15 columns are not discussed in the present study). Virtual Column 2 has been evaluated extensively and is shown to give predicted retention times that in most cases agree with experimentally determined data to within 5%. The software has uses in practical IC method development, education and training in IC, and refinement of existing IC methodology. A free version of this program is available by download at www.virtualcolumn.com.It is an important facet of any chromatographic technique to optimize the separation in order to achieve a high sample throughput with the desired degree of resolution between analytes. Such optimization is of particular interest for chromatographic techniques in which manual development of methods is a time-consuming process. One example is ion chromatography (IC), in which equilibration of the ion-exchange stationary phase with a new eluent composition normally requires considerable time. For this reason, the simulation of anion separations by IC has received significant interest in recent years. 1,2The conventional approach to optimization in IC is to apply a suitable mathematical model to the prediction of retention times of analytes under a range of eluent conditions. The model is used to simulate the separations that can be achieved over a desired search area of eluent compositions, and a suitable optimization algorithm is then used to locate the eluent composition leading to the best separation. Previous research by the authors has focused on the development and comparison of a series of retention models for use in computer-aided optimization of IC. [3][4][5] The emphasis of this work was on determining which of the models provided the most accurate predictive capability, taking into account the degree of experimentation and computing requirements necessary to apply each model. This work has shown that simple empirical models and artificial neural networks provided better accuracy than more complex theoretical retention models. [3][4][5][...

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