The focus of this study is the modeling and separation optimization of solutes on two types of chromatographic columns: reversed phase (conventional particle packed and monolithic) as well as hydrophilic interaction (HILIC) columns. Different retention models are proposed for solute retention prediction under organic modifier-, pH- and/or flow rate – gradient conditions. These models are used in adequate optimization algorithms in order to find out the optimal gradient profiles, which lead to

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... e optimal separation of a sample in the minimum total elution time. Mixtures of nucleosides and nucleobases are used as model compounds. In more details four different studies are conducted in this Thesis. The first study deals with the computer-aided separation optimization under multi-linear organic modifier gradient conditions on a conventional particle packed reversed-phase column. For this purpose the analytical solutions of the fundamental equation of the gradient elution were derived, when the retention model is expressed by . These theoretical expressions were embodied to algorithms for fitting gradient data and especially for resolution optimization and were successfully applied to separation optimization of a mixture of 16 model compounds. The second study deals with the computer-aided separation optimization under dual multi-linear flow rate/organic modifier gradients on a reversed phase monolithic column. For this purpose the numerical solution of a system of two integral equations expressed the solute elution under combined multi-linear flow rate/organic modifier gradients was embodied to prediction and optimization algorithms, which were successfully applied to separation optimization of a mixture of 14 analytes on a reversed phase monolithic column. The third study deals with the solute retention description under combined multi-linear pH/organic modifier gradients conditions on a reversed-phase column. For this purpose the analytical solutions of the fundamental equation of the gradient elution for a weak m [...]