Previous studies have shown that four experimental runs, where both temperature T and gradient time tG are varied, can be used for the reliable prediction of separation as a function of these two variables (two-dimensional optimization). Computer simulation (e.g., DryLab) can then be used to predict “optimized” conditions for maximum sample resolution using either isocratic or gradient elution. Samples that contain a large number of components (e.g., n>15–20) present a greater challenge. Resolution for these more complex samples is often quite sensitive to small changes in T or tG, in turn requiring greater accuracy in predictions that result from computer simulation. In the present study of several samples, we have examined computer simulation errors that can arise from inexact expressions for retention time as a function of T, tG or isocratic %B. Resulting conclusions are applicable to both complex and simpler samples, in either one- or two-dimensional optimization. Means to anticipate and minimize the impact of these predictive errors are examined.

Three ion chromatography (IC) retention models, namely the linear solvent strength model (LSSM), empirical end points model (EEPM) and three-point curve fitting using DryLab from LC Resources were evaluated in terms of their ability to predict retention factors for inorganic anions separated on a Dionex AS11 column using electrolytically generated hydroxide eluents. Extensive experimental retention data were gathered for 21 anions (fluoride, acetate, formate, bromate, chloride, nitrite, methanesulfonate, bromide, chlorate, nitrate, iodide, thiocyanate, succinate, sulfate, tartrate, oxalate, tungstate, phthalate, chromate, thiosulfate and phosphate) using hydroxide eluents of varying concentration. Although the purely theoretical LSSM was found to give adequate performance, the EEPM (in which a linear relationship is assumed between the logarithm of retention factor and the logarithm of eluent strength, but the slope is determined empirically) and DryLab performed better, with DryLab giving the best accuracy and precision of the three models. The EEPM and DryLab were also shown to have advantages in terms of their low knowledge requirements and ease of solution. Compared with IC using dual eluent species, the retention behaviour in IC using single eluent species was found to be easier to model by both theoretical and empirical approaches.

The optimized reversed-phase HPLC separation of 14 different samples is reported, based on simultaneous changes in temperature and gradient steepness. Four experimental runs are required for each sample, following which preferred conditions can be predicted using computer simulation software (DryLab). The overall accuracy and effectiveness of this method development approach is discussed, with particular attention to the use of resolution maps provided by the software. These maps are useful for maximizing resolution for the total sample, for optimizing the separation of a smaller number of selected sample compounds, and as an initial step in the separation of more demanding samples.