Estimation of peak capacity based on peak simulation

Abstract

Peak capacity (PC) is a key concept in chromatographic analysis, nowadays of great importance for characterising complex separations as a criterion to find the most promising conditions. A theoretical expression for PC estimation can be easily deduced in isocratic elution, provided that the column plate count is assumed constant for all analytes. In gradient elution, the complex dependence of peak width with the gradient program implies that an integral equation has to be solved, which is only possible in a limited number of situations. In 2005, Uwe Neue developed a comprehensive theory for the calculation of PC in gradient elution, which is only valid for certain situations: single linear gradients, absence of delays and extra-column effects, Gaussian peaks and constant plate count. Going beyond these limitations implies resolving algebraic expressions that unfortunately cannot be integrated. In this work, PC is predicted for multiple situations based on peak simulation. The approach is more general and can be applied for situations out of the scope of the Neue outline, such as complex multi-linear gradients, including asymmetrical peaks. The plots of PC versus retention time of the last eluted solute give rise to Pareto fronts, and can be useful for the probabilistic enhancement of peak resolution in situations where complex multi-analyte samples are processed.