Abstract
Rapid optimization of gradient liquid chromatographic (LC) separations often utilizes analyte retention modelling to predict retention times as function of eluent composition. However, due to the dwell volume and technical imperfections, the actual gradient may deviate from the set gradient in a fashion unique to the employed instrument. This makes accurate retention modelling for gradient LC challenging, in particular when very fast separations are pursued. Although gradient deformation has been addressed in method-transfer situations, it is rarely taken into account when reporting analyte retention parameters obtained from gradient LC data, hampering the comparison of data from various sources. In this study, a response-function-based algorithm was developed to determine analyte retention parameters corrected for geometry-induced deformations by specific LC instruments. Out of a number of mathematical distributions investigated as response-functions, the so-called “stable function” was found to describe the formed gradient most accurately. The four parameters describing the model resemble the statistical moments of the distribution and are related to chromatographic parameters, such as dwell volume and flow rate. The instrument-specific response function can then be used to predict the actual shape of any other gradient programmed on that instrument. To incorporate the predicted gradient in the retention modelling of the analytes, the model was extended to facilitate an unlimited number of linear gradient steps to solve the equations numerically. The significance and impact of distinct gradient deformation for fast gradients was demonstrated using three different LC instruments. As a proof of principle, the algorithm and retention parameters obtained on a specific instrument were used to predict the retention times on different instruments. The relative error in the predicted retention times went down from an average of 9.8% and 12.2% on the two other instruments when using only a dwell-volume correction to 2.1% and 6.5%, respectively, when using the proposed algorithm. The corrected retention parameters are less dependent on geometry-induced instrument effects.
Highlights
IntroductionThe majority of methods in liquid chromatography (LC) utilize gradient elution, where the fraction of strong solvent (e.g. the organic modifier in reversed-phase LC) φ is gradually increased
The majority of methods in liquid chromatography (LC) utilize gradient elution, where the fraction of strong solvent φ is gradually increased
We have developed an algorithm to correct retention modelling for gradient deformation induced by instrument geometry
Summary
The majority of methods in liquid chromatography (LC) utilize gradient elution, where the fraction of strong solvent (e.g. the organic modifier in reversed-phase LC) φ is gradually increased. Gritti et al have extensively investigated gradient deformation in reversed-phase LC and the effects thereof on the separation [11,12,13]. They were able to improve retention prediction for fast gradients on a single instrument by taking the adsorption isotherms of individual analytes into account [11]. In the same study it was shown that for less-retained compounds the resolution would collapse when fast gradients are applied and the authors proposed to modify the gradient to prevent this behaviour
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