Mixed-mode electrokinetic chromatography of aromatic bases with two pseudo-stationary phases and pH control
Zakaria, P and Macka, M and Haddad, PR (2003) Mixed-mode electrokinetic chromatography of aromatic bases with two pseudo-stationary phases and pH control. Journal of Chromatography A, 997 (1-2). pp. 207-218. ISSN 0021-9673 ![[img]](http://eprints.utas.edu.au/style/images/fileicons/application_pdf.png) | PDF - Full text restricted - Requires a PDF viewer 262Kb | |
Official URL: http://dx.doi.org/10.1016/S0021-9673(03)00064-5 AbstractThe electrokinetic chromatographic (EKC) separation of a series of aromatic bases was achieved utilising an electrolyte system comprising an anionic soluble polymer (polyvinylsulfonic acid, PVS) and a neutral β-cyclodextrin (β-CD) as pseudo-stationary phases. The separation mechanism was based on a combination of electrophoresis, ion-exchange interactions with PVS, and hydrophobic interactions with β-CD. The extent of each chromatographic interaction was independently variable, allowing for control of the separation selectivity of the system. The ion-exchange and the hydrophobic interactions could be varied by changing the PVS and the β-CD concentrations, respectively. Additionally, mobilities of the bases could be controlled by varying pH, due to their large range of pKa values. The separation system was very robust with reproducibility of migration times being <2% RSD. The two-dimensional parameter space defined by the two variables, [β-CD] and %PVS, was modelled using a physical model derived from first principles. This model gave very good correlation between predicted and observed mobilities (r2=0.999) for the 13 aromatic bases and parameters derived from the model agreed with the expected ion-exchange and hydrophobic character of each analyte. The complexity of the mathematical model was increased to include pH and this three-dimensional system was modelled successfully using an artificial neural network (ANN). Optimisation of both the two-dimensional and three-dimensional systems was achieved using the normalised resolution product and minimum resolution criteria. An example of using the ANN to predict conditions needed to obtain a separation with a desired migration order between two of the analytes is also shown. | Item Type: | Article |
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| Additional Information: | The definitive version is available at http://www.sciencedirect.com |
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| Keywords: | Pyridines; Anilines; Amines; Picoline; Quinoline; Mixed-mode separations; Electrokinetic chromatography; Neural networks, artificial; Pseudo-stationary phases
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| ID Code: | 7770 |
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| Deposited By: | Mr Marcus Guijt |
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| Deposited On: | 13 Oct 2008 12:41 |
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| Last Modified: | 13 Oct 2008 12:41 |
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