New Approaches to Thermodynamics-based Predictive Modelling of Gas Chromatography and Comprehensive Two-dimensional Gas Chromatography

• Author / Creator

  Stevenson, Keisean AJM

• Thermodynamics-based predictive models of retention in gas chromatography and comprehensive two-dimensional gas chromatography have been demonstrated to provide high prediction accuracy across a wide range of separation conditions. They generally predict better than retention index-based models and can be more readily applied to comprehensive two-dimensional gas chromatography. However, no large or readily accessible databases of these parameters exist yet. The parameters generated from thermodynamic models are also suitable for use in creating Quantitative Structure-Retention Relationship models. Despite these benefits, thermodynamic parameters obtained using a column of a particular geometry and housed in a given instrument often lead to poor predictions of separation on another column of the same phase chemistry but differing in geometry and the system in which it is installed. As a result of this, the act of creating a database of thermodynamic parameters that can be used by experimenters to reliably model retention on their specific systems has been hindered. This thesis is aimed at investigating new and innovative approaches to improve the predictive capabilities (speed, accuracy and reliability) of thermodynamic models for predicting retention in gas chromatography and comprehensive two-dimensional gas chromatography (particularly across systems and column geometries). This is carried out by the design of a novel Quasi-Newton based optimization algorithm for the estimation of thermodynamic and geometric parameters that allow accurate cross-column and cross-system retention time prediction and transfer. A less time-consuming experimental approach for acquiring and using these parameters accompanies the computational design. The initial stages of the creation of a database of parameters are also presented. Then, parameters obtained using the new algorithm are applied to an innovative method for accurately and quickly predicting peak widths across geometries and systems without the need for additional experimentation. A new approach to estimating additional contributions to band broadening is also explored. Lastly, these thermodynamic parameters are used to calculate characteristic parameters by way of a distribution-centric approach to thermodynamic modelling. The mapping and predictive capabilities of the calculated characteristic parameters are then investigated through a series of thermally modulated comprehensive two-dimensional gas chromatography experiments on different combinations of stationary phase chemistries and geometries.

• Subjects / Keywords

  • Gas chromatography
  • Thermodynamics
  • Prediction
  • Comprehensive two-dimensional gas chromatography

• Graduation date

  Spring 2019

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/r3-73rc-vc11

• License

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