Estimation of injection volume during a preparative chiral separation can be challenging. Commonly one attempts to maximize the injection volume to reduce total separation time. The factors that limit increasing injection volume are (a) purity constraint(e.g. enantiomeric excess) and (b) criterion of product recovery. Standard industrial practice is to successively inject increasing volume of sample mixture until two adjoining peaks (e.g. peaks of two enantiomers) touch respective baselines. Separation scientists may spend considerable time and material to detect this injection volume before starting the stack-injection run. This increased method-development time increases time spent on the instrument, resulting in decreased efficiency. In this report we demonstrate the utility of a mathematical model-based approach that can be employed for faster estimation of this optimum injection volume. Note that the model does not intend to detect the theoretical maximum injection volume, rather tries to mimic the experimental optimization approach through simulation. The method requires experimental data from one initial trial run as input to predict the final "optimum" injection volume, thus saving time and material compared to situations that require multiple trial runs. The proposed model is simple enough to be implemented in a Microsoft Excel spreadsheet, but offers reasonably accurate estimation. Although the example presented in this report is of preparative separation of a racemic mixture with supercritcal fluid chromatography (SFC), in general the model is applicable to any preparative separation under isocratic conditions where the chromatographic peak follows Langmuir adsorption isotherm behavior. A description of the fundamental basis of the model is presented here along with experimental results that demonstrate its utility.
Keywords: Chiral separation Enantiomers Injection volume Mathematical model Preparative SFC Supercritical Fluid Chromatography