Novel molecular materials and computational strategies with gas chromatography

The ability to detect, identify and quantify many types of compounds in complex matrices is paramount for many disciplines and application areas such as proteomics, environmental, pharmaceutical, medical, petrochemical, food and beverages. Existing detection technologies, such as high resolution mass spectroscopy, may fail to adequately analyse compounds of interest in multi‐component samples; isomers or compound identity may be incorrectly reported, e.g. false positive identification of illicit drugs, biomarkers or synthetic compounds due to the presence of interferences or by‐products. Chromatographic methods offer an effective solution where target analytes in complex matrices are separated from the non‐targets allowing improved identification of many compounds with minimised signal interference in a single analysis. Identification and quantification of well separated isomers can also be achieved. Among different separation techniques, comprehensive two dimensional gas chromatography (GC×GC) has been realised as a high resolution analysis technique allowing the separation of hundreds of analytes based on their differing boiling points and/or polarities. A simple concept may be that components in samples should be separated as much as possible, permitting unambiguous analysis of target analytes in GC×GC. Within this simple concept, a tremendous amount of time, consumables and energy needs to be spent on the optimisation process since the GC×GC method incorporates two dissimilar column geometries, and choice of stationary phases leading to many variables that must be considered when performing separation such as relative column dimensions, types of stationary phases, temperature programs and carrier gas flow. Thousands of experiments may need to be performed in order to obtain an effective chromatographic outcome for each sample. Understanding the impact of these variables on separation mechanisms is thus important to design an effective optimisation processes, and to reduce valuable resources. Recently, there has been an increasing interest in developing new methodologies for improved GC×GC analysis, utilising novel materials such as ionic liquids (IL) as stationary phases with high polarity and good thermal stability. Besides the polar/nonpolar interactions, additional hydrogen bond basicity is also obtained with these phases, due to the customisable functionalities of IL allowing introduction of acid moieties onto the IL stationary phase molecules which broadens selectivity in GC and finally offers improved overall separation quality (orthogonality) in GC×GC. In this thesis, new theoretical concepts and approaches to direct column selection and to aid optimisation of experimental conditions in GC×GC were established according to linear solvation energy relationship (LSER) and molecular modelling. Relevant computational software was developed according to the established approaches in order to simulate GC×GC results for individual experimental investigation covering a wide range of compounds such as fatty acid methyl esters, hydrocarbons in petroleum, alcohols, aldehydes, terpenes, polychlorinated naphthalenes and polychlorinated biphenyls. These simulated results were evaluated by comparison with experimental results. The theories, methods and results presented in this thesis will, in the future, allow further targeted developments of novel experimental design, effective stationary phase material selection, an understanding of separation mechanisms with IL stationary phases in GC×GC, and the possibility to design tuned stationary phases that further improve separation performance. These principles could also equally well apply to heart‐cut multidimensional GC operation.