Tools and Methodologies for The Rapid Determination and Transfer of Thermodynamic Parameters used in the Prediction of Gas Chromatographic and Two Dimensional Comprehensive Gas Chromatographic Retention Times

Abstract

Three parameter thermodynamic predictive models have been shown previously to provide superior accuracy in the prediction of gas chromatographic retention times in comparison to other forms of modelling such as retention indices. However, these models suffer from the need for extensive experimentation to generate the data required to make their predictions. This then limits the applicability of the method to real world situations. This thesis sets out to explore new methods and techniques that reduce the required experimentation necessary to make thermodynamic based retention time predictions in gas chromatography. Three main ideas are explored in the process of reducing experimentation: the automation of thermodynamic data collection, the adaptation of thermodynamic collection models from isothermal to temperature programmed based experimentation and a method to rapidly transfer thermodynamic data from one chromatographic system to the next. Along with the above stated goals, this research sets out to develop models for the prediction of retention times in two dimensional gas chromatography using three parameter thermodynamic data. Two dimensional separations are also used to validate the methods and concepts mentioned previously.