Gradient retention times are difficult to project from the underlying retention factor (k) vs. solvent composition (φ) relationships. A major reason for this difficulty is that gradients produced by HPLC pumps are imperfect – gradient delay, gradient dispersion, and solvent mis-proportioning are all difficult to account for in calculations. However, we recently showed that a gradient “back-calculation” methodology can measure these imperfections and take them into account. In RPLC, when the back-calculation methodology was used, error in projected gradient retention times is as low as could be expected based on repeatability in the k vs. φ relationships. HILIC, however, presents a new challenge: the selectivity of HILIC columns drift strongly over time. Retention is repeatable in short time, but selectivity frequently drifts over the course of weeks. In this study, we set out to understand if the issue of selectivity drift can be avoid by doing our experiments quickly, and if there any other factors that make it difficult to predict gradient retention times from isocratic k vs. φ relationships when gradient imperfections are taken into account with the back-calculation methodology. While in past reports, the accuracy of retention projections was >5%, the back-calculation methodology brought our error down to ∼1%. This result was 6–43 times more accurate than projections made using ideal gradients and 3–5 times more accurate than the same retention projections made using offset gradients (i.e., gradients that only took gradient delay into account). Still, the error remained higher in our HILIC projections than in RPLC. Based on the shape of the back-calculated gradients, we suspect the higher error is a result of prominent gradient distortion caused by strong, preferential water uptake from the mobile phase into the stationary phase during the gradient – a factor our model did not properly take into account. It appears that, at least with the stationary phase we used, column distortion is an important factor to take into account in retention projection in HILIC that is not usually important in RPLC.

梯度保留时间很难从基本保留因子（k）与溶剂组成（φ）的关系中推算出来。造成这一困难的主要原因是HPLC泵产生的梯度不完美–梯度延迟，梯度分散和溶剂配错都难以在计算中解决。但是，我们最近表明，梯度“反向计算”方法可以测量这些缺陷并将其考虑在内。在RPLC中，当使用反向计算方法时，根据k与φ的重复性，预计的梯度保留时间误差将尽可能低。关系。但是，HILIC提出了新的挑战：随着时间的流逝，HILIC色谱柱的选择性会发生很大的漂移。保留时间可在短时间内重复，但选择性通常会在数周内发生漂移。在这项研究中，我们着手了解是否可以通过快速进行实验来避免选择性漂移的问题，以及是否存在其他因素使得难以根据等度k对φ预测梯度保留时间。反向计算方法考虑梯度不完美时的关系。在过去的报告中，保留预测的准确性大于5％，而反向计算方法使我们的误差降低到了约1％。该结果比使用理想梯度进行的投影准确度高6–43倍，比使用偏移梯度（即仅考虑梯度延迟的梯度）所进行的相同保留投影准确度高3–5倍。但是，我们的HILIC预测中的误差仍然高于RPLC。根据反算梯度的形状，我们怀疑较高的误差是由于梯度过程中流动相向固定相强烈，优先吸水而引起的明显的梯度畸变所致，这是我们的模型未适当考虑的一个因素考虑在内。