Doctor of Philosophy (PhD)
Multiple regression modeling techniques allow for rapid and accurate prediction of migration times and resolution values for micellar electrokinetic chromatography (MEKC) as well as the development of quick screening methods using steady-state fluorescence spectroscopy. All studies reported in this dissertation include optimization of calibration models and predictions of dependent variables by the use of validation samples. The root-mean-square percent relative error (RMS%RE) is used as a figure of merit for characterizing the performance of the calibration models. MEKC separations of achiral and chiral analytes were performed using an achiral molecular micelle, poly(sodium N-undecylenic sulfate), and chiral molecular micelles, poly(sodium N-undecanoyl-L-leucylvalinate) or poly(sodium N-undecanoyl-L-isoleucylvalinate), at various operating temperatures, applied voltages, pH, and molecular micelle concentrations in the background electrolyte. The RMS%RE values of predicted migration time, resolution, and resolution per unit time of the chiral as well as the achiral analytes ranged from 8.78 to 37.73% for all MEKC studies. Chiral analysis using steady-state fluorescence spectroscopy was employed to investigate the use of chiral molecular micelles as chiral selectors by multivariate regression modeling of spectral data. PLS-1 was used to correlate changes in the fluorescence emission intensity of several fluorescent analytes in the presence of non-fluorescent molecular micelles and fluorescent chiral molecular micelles (FCMMs) in the presence of non-fluorescent analytes. In terms of RMS%RE, the ability of the model to accurately predict the enantiomeric composition of future samples was dependent on the chiral analyte, molecular micelle, as well as the solvent medium, and ranged between 1.21 and 6.10%.
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Snearl, Alicia Williams, "Chiral analyses using molecualr micelles and multiple regression modeling in chromatographic and spectroscopic methods" (2007). LSU Doctoral Dissertations. 2601.
Isiah M Warner