Using computer modeling to predict and optimize separations for comprehensive two-dimensional gas chromatography.

In order to fully realize the separation power of comprehensive two-dimensional gas chromatography (GC x GC), a means of predicting and optimizing separations based on operating variables was developed. This approach initially calculates the enthalpy (DeltaH) and entropy (DeltaS) for the target compounds from experimental input data, and then uses this information to simultaneously optimize all column and runtime variables, including stationary phase composition, by comparing the performance of large numbers of simulated separations. This use of computer simulation has been shown to be a useful aid in conventional separations. It becomes almost essential for GC x GC optimization because of the large number of variables involved and their very complex interaction. Agreement between experimental and predicted values of standard test samples (Grob mix) using GC x GC separation shows that this approach is accurate. We believe that this success can be extended to more challenging mixtures resulting in optimizations that are simpler and transferable between GC x GC instruments.

Predicting gas chromatographic separation and stationary-phase selectivity using computer modeling.

A computer modeling technique has been developed which allows for the prediction of chromatographic separation and stationary-phase selectivity. This technique enables development of application-specific gas chromatographic columns by allowing for the simultaneous optimization of physical dimensions, flow and temperature programs, and stationary-phase composition. Stationary-phase selectivity is the most powerful tool available to achieve a separation; however most commercially available columns were not designed to have a selectivity specific to the separations for which they are used. The techniques described in this paper were developed to address this need.