Estimation of significant solvent concentration ranges and its application to the enhancement of the accuracy of gradient predictions

The solvent concentration range actually useful for gradient predictions is significantly narrower than the total range scanned in a gradient run. This range, called “solvent informative range” (SIR), if known with the highest accuracy, allows to predict gradient retention times (tg) with minimal error. The small size of the SIR supports the application of the linear solvent strength theory (LSST). Furthermore, LSST allows a closed-form solution to the integral required to predict gradient retention times, which eliminates numerical integration, needed with other retention models. A methodology that calculates the SIR by applying error analysis, and uses it to improve the accuracy in the prediction of tg from isocratic experiments, is proposed. The importance of those mobile-phase compositions that do not contribute significantly to the prediction of tg is selectively attenuated within the prediction algorithm, relying the predictions more heavily on the SIR. As a result, tg was found to be predicted with similar accuracy using isocratic training data with regard to predictions based on gradient training data. The approach is useful for all situations where the chromatographer is able to provide predictions of retention at constant solvent concentration, and wish to predict the retention in gradient mode.