Gradien elution methods for predicting isocratic conditions

Abstract

Gradient elution methods can elegantly be used for rapidly establishing the appropriate isocratic elution conditions for newly chromatographed samples. In comparison with the conventional approach of running a numbr of isocratic chromatograms on a trial-and-error basis, gradient elution methods can be much more efficient and yield more consistent results. Key factors are a description of the retention behaviour of the solutes under isocratic conditions as a function of the programmed parameters and an accurate knowledge of the actual gradient profile, i.e., the variation of the programmed parameters with time. Reasonably simple calculation procedures are facilitated by the use of simple ( e.g., linear) programmes and instrumentation that affects the actual profile as little as possible. For non-ionic solutes two different gradient scans suffice in principle. In certain cases a single gradient scan may be adequate. A combination of one gradient scan and once isocratic verification experiment can often be used for the accurate prediction of optimum isocratic conditions. For ionic solutes a larger number of scannning experiments are needed than for non-ionic solutes, but in comparison with the time needed for trial-and-error optimization the potential benefits of gradient scanning methods are much greater. For characterizing the ionic solutes in unknown samples two things are needed. First, the solutes need to be classified according to their type (weak or strong; acids or bases) and charge. Next, the optimum isocratic conditions should be established. The concentration of organic modifier, the pH and the type and concentration of ion-pair reagent are the most important parameters to be considered in the process. Using linear gradients at two different pH values in combination with “pulse injection” of ion-pairing reagents, four scanning experiments form the basis of an efficient classification procedure. Once the solutes have been classified, simple, stepwise procedures can be used to establish optimum isocratic conditions.