Simulating Capillary Gas Chromatographic Separations including Thermal Gradient Conditions

Relation between characteristic temperature and elution temperature in temperature programmed gas chromatography - part I: Influence of initial temperature and heating rate

The development of new analytical methods can save resources, time and costs if there are prediction tools like computer simulation which support the optimization process. In GC the distribution-centric 3-parameter model (K-centric model) is well established for prediction of retention factors k and retention times but laborious isothermal measurements for determination of the characteristic parameters are needed. For the most important parameter, the characteristic temperature Tchar, the search for simpler determination methods or even estimates is an interesting research topic. In this work the elution temperatures for 37 fatty acid methyl esters, 6 BTEXs and 40 other volatile substances are determined by measurements under variable heating rates, initial temperatures, constant pressure mode and constant flow mode. The relationship between the measured elution temperature and the characteristic temperature was investigated. The novel multivariate curve fit model presented in this study describes accurately the relation between the characteristic temperature Tchar and elution temperatures Telu under variable heating rates RT, respectively, and initial temperature Tinit conditions. The novel model shows good accordance to earlier estimation models and expands the prediction range, especially for high volatile compounds. The model is suitable for determination of Tchar by estimated Telu and vice versa. Predictions of retention times of simple temperature programs were also possible by using the model with relative deviations < 5% compared to measurements.

Comparison of the Dynamic Thermal Gradient to Temperature-Programmed Conditions in Gas Chromatography Using a Stochastic Transport Model

This paper compares dynamic (i.e., temporally changing) thermal gradient gas chromatography (GC) to temperature-programmed GC using a previously published stochastic transport model to simulate peak characteristics for the separation of C12-C40 hydrocarbons. All comparisons are made using chromatographic conditions that give approximately equal analyte retention times (t_R). As shown previously, a static thermal gradient does not improve resolution (R_s) equally for all analytes, which highlights the need for a dynamic thermal gradient. An optimal dynamic thermal gradient should result in constant analyte velocities at any instant in time for those analytes that are actively being separated (i.e., analytes that have low retention factors). The average separation temperature for each analyte is used to determine the thermal gradient profile at different times in the temperature ramp. Because many of the analytes require a similar thermal gradient profile when actively being separated, the thermal gradient profile in this study was held fixed; however, the temperature of the entire thermal gradient was raised over time. From the simulations performed in this study, optimized dynamic thermal gradient conditions are shown to improve R_s by up to 13% over comparative temperature-programmed conditions, even with a perfect injection (i.e., zero injection bandwidth). In the dynamic thermal gradient simulations, all analytes showed improvements in R_s along with slightly shorter t_R values compared to simulations for traditional temperature-programmed conditions.

Modeling approaches for temperature-programmed gas chromatographic retention times under vacuum outlet conditions

This contribution evaluates the performance of two predictive approaches in calculating temperature-programmed gas chromatographic retention times under vacuum outlet conditions. In the first approach, the predictions are performed according to a thermodynamic-based model, while in the second approach the predictions are conducted by using the temperature-programmed retention time equation. These modeling approaches were evaluated on 47 test compounds belonging to different chemical classes, under different experimental conditions, namely, two modes of gas flow regulation (i.e., constant inlet pressure and constant flow rate), and different temperature programs (i.e., 7 °C/min, 5 °C/min, and 3 °C/min). Both modeling approaches gave satisfactory results and were able to accurately predict the elution profiles of the studied test compounds. The thermodynamic-based model provided more satisfying results under constant flow rate mode, with average modeling errors of 0.43%, 0.33%, and 0.15% across all the studied temperature programs. Nevertheless, under constant inlet pressure mode, lower modeling errors were achieved when using the temperature-programmed retention time equation, with average modeling errors of 0.18%, 0.18%, and 0.31% across the used temperature programs.

Comparison of Static Thermal Gradient to Isothermal Conditions in Gas Chromatography Using a Stochastic Transport Model

This paper compares static (i.e., temporally unchanging) thermal gradient gas chromatography (GC) to isothermal GC using a stochastic transport model to simulate peak characteristics for the separation of C12-C14 hydrocarbons resulting from variations in injection bandwidth. All comparisons are made using chromatographic conditions that give approximately equal analyte retention times so that the resolution and number of theoretical plates can be clearly compared between simulations. Simulations show that resolution can be significantly improved using a linear thermal gradient along the entire column length. This is mainly achieved by partially compensating for loss in resolution from the increase in mobile phase velocity, which approximates an ideal, basic separation. The slope of the linear thermal gradient required to maximize resolution is a function of the retention parameters, which are specific to each analyte pair; a single static, thermal gradient will not affect all analytes equally. A static, non-linear thermal gradient that creates constant analyte velocities at all column locations provides the largest observed gains in resolution. From the simulations performed in this study, optimized linear thermal gradient conditions are shown to improve the resolution by as much as 8.8% over comparative isothermal conditions, even with a perfect injection (i.e., zero initial bandwidth).