Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1200006 | Journal of Chromatography A | 2014 | 11 Pages |
•Implementation of organic solvent gradients in micellar liquid chromatography, MLC.•Screening of β-blockers in urine samples with direct injection in gradient MLC.•1-Propanol gradients allows the elution of β-blockers of diverse polarity.•Gradient elution starting with pure micellar solution benefits direct injection.•Optimisation of organic solvent gradients in MLC can be performed with DryLab®.
In micellar liquid chromatography (MLC), chromatographic peaks are more evenly distributed compared to conventional reversed-phase liquid chromatography (RPLC). This is the reason that most procedures are implemented using isocratic elution. However, gradient elution may be still useful in MLC to analyse mixtures of compounds within a wide range of polarities, decreasing the analysis time. Also, it benefits the determination of moderately to low polar compounds in physiological fluids performing direct injection: an initial micellar eluent with a low organic solvent content, or a pure micellar (without surfactant) solution, will provide better protection of the column against the proteins in the physiological fluid, and once the proteins are swept away, the elution strength can be increased using a positive linear gradient of organic solvent to reduce the analysis time. This work aims to encourage analysts to implement gradients of organic solvent in MLC, which is rather simple and allows rapid analytical procedures without pre-treatment or the need of re-equilibration. The implementation of gradient elution is illustrated through the separation of eight basic compounds (β-blockers) in urine samples directly injected into the chromatograph, the most hydrophobic showing large retention in both conventional RPLC and MLC. The use of the DryLab® software to optimise gradients of organic solvent with eluents containing a fixed amount of surfactant above the critical micellar concentration is shown to provide satisfactory predictions, and can facilitate greatly the implementation of gradient protocols.