Combined effect of solvent content, temperature and pH on the chromatographic behaviour of ionisable compounds

Optimization of resolution as a simultaneous function of solvent composition, pH and temperature in reversed-phase liquid chromatography

BACKGROUND

The latest chromatographic retention models are capable of accurately describe the dependencies of retention over a wide range of experimental conditions. By using a suitable conversion, these models can be transformed into equations expressing the optimization criteria as function of multiples variables. Even though that theoretical models significantly reduce the experimental requirements for optimizations, these models have been barely used. Instead, most optimizations rely on empirical exploration of the relationships between criterions and variables. There is a need for a strategy to reduce the required number of experiments in multivariated optimization of separations, and Fundamental Models offer a clear opportunity for addressing it.

RESULTS

A Fundamental Model is used to give the simultaneous dependence of chromatographic retention of seven ionizable pesticides on the three variables: solvent composition, temperature and pH (w, T, pH). Based on few experiments, the 10 parameters required to predict the chromatographic retention of those compounds, taken as model analytes, can be obtained. Two mathematical treatments to convert retentions into resolutions between pairs are used: one considering extracolumn dispersions and other neglecting these contributions. Using the Overlapped Resolutions Maps, extended to four dimensions, two optimal conditions can be found for the two different mathematical conversions. Chromatographic conditions were empirically evaluated obtaining the best results for the optimization considering extracolumn dispersions, proving that this condition is a true optimal. It was demonstrated that any small shift in any of the variables from this true optimal leads to a loss in resolution.

SIGNIFICANCE

Fundamental Models describing chromatographic retention as a simultaneous function of multiple variables are nowadays very accurate. In this work is demonstrated that these models are useful not only to predict retentions, but also to optimize separations, even in the more challenging mode: isocratic, isothermal and iso-pH. However, the success in the optimization procedure depends also on the proper definition of the mathematical conversion of the Fundamental Models into optimization criteria.

Using the column wall itself as resistive heater for fast temperature gradients in liquid chromatography

A new system is proposed for applying fast temperature gradients in liquid chromatography. It consists of a 0.7 mm × 150 mm fused-silica column coated with a 50 μm Nickel-layer, which is connecting with a power source and a temperature control system to perform fast and reproducible temperature gradients using the column wall itself as a resistive heater. Applying a current of 4A and passive cooling results in a maximal heating and cooling rate of, respectively, 71 and -21 °C/min. Multi-segment temperature gradients were superimposed on mobile phase gradients to enhance the selectivity for three sets of mixtures (pharmaceutical compounds, a highly complex mixture and an insecticide sample). This resulted in a higher peak count or better selectivities for the various mixtures.

Combined effect of solvent content, temperature and pH on the chromatographic behaviour of ionisable compounds. III: Considerations about robustness

We previously reported a model able to predict the retention time of ionisable compounds as a function of the solvent content, temperature and pH [J. Chromatogr. A 1163 (2007) 49]. The model was applied further, developing an optimisation of the resolution based on the peak purity concept [J. Chromatogr. A 1193 (2008) 117]. However, we left aside an important issue: we did not consider incidental overlaps caused by shifts in the predicted peak positions, owing either to uncertainties in the source data, modelling errors, or the practical implementation in the chromatograph of the optimal mobile phase (or any other). These shifts can ruin the predicted separation, since they can easily amount several peak-width units at pH values close to the logarithm of the solutes' acid-base constants. A probabilistic optimisation is proposed here, which is able to evaluate the uncertainties associated with the model and the consequences when the optimal mobile phase is implemented in the chromatograph. This approach assumes peak fluctuations in replicated assays obtained through Monte Carlo simulations, which gives rise to a distribution of elementary peak purities. The results yielded by the conventional (i.e. non-robust), derivative-penalised, and probabilistic optimisations were compared, checking the predicted and experimental chromatograms at several critical experimental conditions. Among the three approaches, only the probabilistic one was able to appraise properly the practical difficulties of the separation problem.

Retention mechanisms in micellar liquid chromatography

Micellar liquid chromatography (MLC) is a reversed-phase liquid chromatographic (RPLC) mode with mobile phases containing a surfactant (ionic or non-ionic) above its critical micellar concentration (CMC). In these conditions, the stationary phase is modified with an approximately constant amount of surfactant monomers, and the solubilising capability of the mobile phase is altered by the presence of micelles, giving rise to diverse interactions (hydrophobic, ionic and steric) with major implications in retention and selectivity. From its beginnings in 1980, the technique has evolved up to becoming a real alternative in some instances (and a complement in others) to classical RPLC with hydro-organic mixtures, owing to its peculiar features and unique advantages. This review is aimed to describe the retention mechanisms (i.e. solute interactions with both stationary and mobile phases) in an MLC system, revealed in diverse reports where the retention behaviour of solutes of different nature (ionic or neutral exhibiting a wide range of polarities) has been studied in a variety of conditions (with ionic and non-ionic surfactants, added salt and organic solvent, and varying pH). The theory is supported by several mechanistic models that describe satisfactorily the retention behaviour, and allow the measurement of the strength of solute-stationary phase and solute-micelle interactions. Suppression of silanol activity, steric effects in the packing pores, anti-binding behaviour, retention of ionisable compounds, compensating effect on polarity differences among solutes, and the contribution of the solvation parameter model to elucidate the interactions in MLC, are commented.