Strasters J K, Breyer E D, Rodgers A H, Khaledi M G
North Carolina State University, Department of Chemistry, Raleigh 27695.
J Chromatogr. 1990 Jul 6;511:17-33. doi: 10.1016/s0021-9673(01)93267-4.
Previously, the simultaneous enhancement of separation selectivity with elution strength was reported in micellar liquid chromatography (MLC) using the hybrid eluents of water-organic solvent-micelles. The practical implication of this phenomenon is that better separations can be achieved in shorter analysis times by using the hybrid eluents. Since both micelle concentration and volume fraction of organic modifier influence selectivity and solvent strength, only an investigation of the effects of a simultaneous variation of these parameters will disclose the full separation capability of the method, i.e. the commonly used sequential solvent optimization approach of adjusting the solvent strength first and then improving selectivity in reversed-phase liquid chromatography is inefficient for the case of MLC with the hybrid eluents. This is illustrated in this paper with two examples: the optimization of the selectivity in the separation of a mixture of phenols and the optimization of a resolution-based criterion determined for the separation of a number of amino acids and small peptides. The large number of variables involved in the separation process in MLC necessitates a structured approach in the development of practical applications of this technique. A regular change in retention behavior is observed with the variation of the surfactant concentration and the concentration of organic modifier, which enables a successful prediction of retention times. Consequently interpretive optimization strategies such as the interative regression method are applicable.
此前，在胶束液相色谱（MLC）中使用水-有机溶剂-胶束的混合洗脱剂时，有报道称分离选择性与洗脱强度可同时提高。这一现象的实际意义在于，使用混合洗脱剂能够在更短的分析时间内实现更好的分离。由于胶束浓度和有机改性剂的体积分数都会影响选择性和溶剂强度，因此只有同时研究这些参数变化的影响，才能揭示该方法的全部分离能力，即反相液相色谱中常用的先调节溶剂强度、再提高选择性的顺序溶剂优化方法，对于使用混合洗脱剂的MLC情况是低效的。本文通过两个例子对此进行说明：酚类混合物分离中选择性的优化，以及针对多种氨基酸和小肽分离确定的基于分辨率标准的优化。MLC分离过程中涉及大量变量，这就需要一种结构化方法来开发该技术的实际应用。随着表面活性剂浓度和有机改性剂浓度的变化，保留行为会有规律地改变，这使得能够成功预测保留时间。因此，诸如迭代回归法等解释性优化策略是适用的。
