The bachelor’s thesis is comprised of a literature review, which describes the modern trends in the prediction of retention in reverse-phase liquid chromatography. An introduction to Hansen solubility parameters, their derivation, applications and experimental determination is presented. It is followed by a theoretical model construction, based upon Hansen solubility parameters. The thermodynamic descriptor is introduced and defined formally.
UV-vis absorption spectra and solute cavitation volumes are calculated using density functional theory ab initio approaches. HPLC experiments are conducted in order to obtain a retention database of three homologous dialkyl phthalates, which are used in the construction of theoretical models. A smaller retention database of different analytes is also obtained to explore the models’ predictiveness.
Hansen solubility parameters can be used for retention prediction, but only for models built upon one analyte at a time. A group model, comprised of different analytes, which aims to generalize the predictivity of retention for different compounds, has no real predictive ability. During the experimental work, an anomaly was identified. At the molar fraction of 0,34 acetonitrile in the mobile phase, the sensitivity of retention in response to a change in temperature is suddenly lowered. Aside from that, a trend of inverse relationship in the sensitivity of retention as a function of temperature and mobile phase composition is identified, exclusively using experimental data. An increase in the amount of acetonitrile lowers the effect of temperature on the retention sensitivity.
A multiple linear regression model, using the thermodynamic descriptor, temperature and the total adsorption of acetonitrile onto the stationary phase as independent variables, is identified as the best model but fails to fully explain the identified anomaly.
The presented method for predicting retention based on Hansen solubility parameters is a novel approach, using established thermodynamic solubility parameters for modelling reverse-phase chromatographic separations. The theoretical construction, rigorous mathematical formulation and statistical evaluation of the model equation are therefore entirely original.
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