Chromatographic models to predict the elution of ionizable analytes by organic modifier gradient in reversed phase liquid chromatography
| Autor: | Axel Andrés, Elisabeth Bosch, Adolfo Téllez, Martí Rosés |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Ions
Chromatography Reverse-Phase Work (thermodynamics) Analyte Acetonitriles Chromatography Elution Chemistry Organic Chemistry Analytical chemistry General Medicine Reversed-phase chromatography Buffers Hydrogen-Ion Concentration Biochemistry Analytical Chemistry Ion chemistry.chemical_compound Models Chemical Ionization Phase (matter) Calibration Linear Models Organic Chemicals Acetonitrile |
| Zdroj: | Journal of Chromatography A. 1247:71-80 |
| ISSN: | 0021-9673 |
| Popis: | The retention of an ionizable analyte under RP-HPLC organic modifier gradient elution is strongly affected by its ionization degree which, in turn, depends on its pK(a) and on the pH of the mobile phase. The values of both parameters change depending on the mobile phase composition and thus retention becomes a parameter quite difficult to predict, particularly when working in gradient mode. In this work, an equation describing the retention of ionizable analytes has been combined with three different models of different complexity, developed for gradient elution of neutral compounds (1, 2, or 3 fitting parameters), in order to predict retention of compounds with acid-base properties with particular buffers. All models have been tested under 16 different gradient patterns (4 linear gradients, 4 concave gradients, 4 convex gradients and 4 combinations between them) for the prediction of the retention time of 12 acid-base compounds (pK(a) values from 4 to 9) in 3 different buffered mobile phases (pH 5, pH 7 and pH 9) with acetonitrile as organic modifier. The agreement between the experimental and calculated retention times is good for all models. The best results are obtained through the model that depends on three parameters and the accuracy of the two-parameter model is slightly lower but very acceptable too. On the other hand, the predictions performed with the one-parameter model are the less accurate, but good enough to become a valid model taking into account that it requires very little experimental work. |
| Databáze: | OpenAIRE |
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