Novel approaches for selectivity enhancement in the chromatographic analysis of complex samples

Many products and materials that are used daily consist of different compounds or mixtures of ingredients each containing many different chemical species. As these products tend to become even more complex every day, the development of selective analytical methods is not only important for understanding how the properties of these products or materials are related to their components, but also for ensuring their quality and safety features. Selective analytical methods have the ability to determine specific analyte(s) or group(s) of analytes in a complex mixture without interferences from other components of the mixture. The desired selectivity can be achieved at different stages of the analytical method: during sample pretreatment, sample separation, compound detection or at the data interpretation stage. If these stages are correctly chosen and optimized, taking into account the performance of each of the steps and the way they influence each other, the selectivity of the overall analytical method can be tuned in order to facilitate the characterization of complex samples. In this thesis we studied the selectivity provided by the different stages of the analytical methods for the optimal analysis of complex samples. In terms of the applications, we focused on the selective analysis of two complex samples used for the elaboration of consumer products: mineral oils and lignin. We demonstrated that the use and combination of various selectivities is necessary to describe all the components of these complex samples in sufficient detail in order to assure the sample’s quality, correct properties and safety.