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MATHEMATICAL MODEL FOR SIMULATION OF IC ANALYSIS RESPONSE

In accordance to common principles of economy, searching for financially more acceptable analytical methods becomes the important part of development policy of modern analytical laboratories ; ion chromatographic methods are not an exception. Although the best peak resolution can be obtained by using isocratic elution mode, the gradient elution mode may provide significant benefits. Due to its capability of reducing the analysis time significantly, gradient elution became inevitable chromatographic technique, despite of inherently more complex method development procedures. In development of new gradient eluted ion chromatographic methods, mathematical models commonly replace the traditional “trial and error” procedures, sometimes with remarkable success. By predicting the chromatographic system response, these models are able to provide an approximation for optimal separation conditions as well. The aim of this presentation is development of a gradient elution retention model based on isocratic experimental data (IG model). For the purpose of gradient modeling, the quadratic polynomial isocratic elution retention model was set up and tested. The entire experimental part was done on Dionex DX-600 ion chromatographic system. The behavior of a model solution, that contained fluoride (3 ppm), chlorite (10 ppm), chloride (6 ppm), chlorate (25 ppm), nitrate (25 ppm) and sulphate (25 ppm) ions, was tested by separating these anion constituents on AS19 ion chromatographic column. Three different chromatographic properties were predicted: retention time, resolution, and peak asymmetry, in relation to variable eluent ion concentration. The performed experiments proved that retention times under gradient elution mode could be satisfactorily predicted if quadratic polynomial retention model is used for isocratic prediction. The retention times were predicted directly, using experimental data. However, the properties of resolution and peak asymmetry were obtained indirectly, by calculations using predicted retention times of three characteristic points on the chromatographic peak (50% peak high at fronting side, peak maximum and 50% peak high at tailing side). The generalized logistic function was chosen for the peak shape prediction. This threeparameter distribution function was able to model all test chromatograms satisfactorily. By combining gradient elution model with the selected peak shape function, a number of real elution simulations was performed. The simulations were compared with experimental gradient chromatograms, and in most cases good fit was obtained. This approach offers, to every day chromatography users, a possibility for significant reducing of experimental efforts in optimization of ion chromatographic methods. In combination with one or more optimization criteria, the approach offers possibility to become an excellent basis for new ion chromatographic optimization software. This conjunction is already applied in optimization software OptIC, what is the distinct topic at one of 11th ISIC’s poster presentations.

retention modeling; ion chromatography

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