Stationary-Phase Optimized Selectivity Liquid Chromatography: Development of a Linear Gradient Prediction Algorithm

被引：50

作者：

De Beer, Maarten ^{[1
]}

Lynen, Frederic ^{[1
]}

Chen, Kai ^{[1
]}

Ferguson, Paul ^{[2
]}

Hanna-Brown, Melissa ^{[3
]}

Sandra, Pat ^{[1
]}

机构：

[1] Univ Ghent, Pfizer Analyt Res Ctr, B-9000 Ghent, Belgium

[2] Pfizer Global R & D, Res Analyt, Sandwich CT13 9NJ, Kent, England

[3] Pfizer Global R & D, Analyt R&D, Sandwich CT13 9NJ, Kent, England

来源：

ANALYTICAL CHEMISTRY | 2010年 / 82卷 / 05期

关键词：

PREOPT-W; RETENTION MODELS; MULTIVARIATE-OPTIMIZATION; SOLID CHROMATOGRAPHY; SIMULATION PROGRAM; SOLVENT MODULATION; HPLC; ELUTION; SEPARATIONS; COLUMNS;

D O I：

10.1021/ac902287v

中图分类号：

O65 [分析化学];

学科分类号：

070302 ; 081704 ;

摘要：

Stationary-phase optimized selectivity liquid chromatography (SOS-LC) is a tool in reversed-phase LC (RP-LC) to optimize the selectivity for a given separation by combining stationary phases in a multisegment column. The presently (commercially) available SOS-LC optimization procedure and algorithm are only applicable to isocratic analyses. Step gradient SOS-LC has been developed, but this is still not very elegant for the analysis of complex mixtures composed of components coveting a broad hydrophobicity range. A linear gradient prediction algorithm has been developed allowing one to apply SOS-LC as a generic RP-LC optimization method. The algorithm allows operation in isocratic, stepwise, and linear gradient run modes. The features of SOS-LC in the linear gradient mode are demonstrated by means of a mixture of 13 steroids, whereby baseline separation is predicted and experimentally demonstrated.

引用

页码：1733 / 1743

页数：11

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