Programmed-temperature elution optimization

According to eqn.(5.4), if the result of a programmed temperature scanning experiment in GC is a bunch of peaks eluted around a column temperature of 195 °C, then a chromatogram in which all the peaks appear with roughly optimal capacity factors may be expected to result from an isothermal experiment at 150 °C. 

If the program is optimized so that all sample components are eluted under optimal conditions, then other (secondary) parameters may be used for the optimization of the selectivity. However, changes in the secondary parameters may imply that the parameters of the program need to be re-optimized. For example, if the selectivity in a temperature programmed GC analysis is insufficient, then another stationary phase may be used to enhance the separation. However, the optimum program parameters obtained with one stationary phase cannot be transferred to another column that contains another stationary phase. The re-optimization of the temperature program for the other column will require at least one additional experiment to be performed. 

The overall density of the mobile phase is one of the most important parameters used to optimize separations in SFC with density programming as common in SFC as temperature programming in GC and eluent composition in HPLC [5]. Capacity ratios, k decrease roughly linearly at higher densities with different slopes for different classes of compounds, thereby affording changes in selectivity [5]. A similar effect is seen for the supercritical fluid elution of analytes from octadecylsilica sorbents, as seen in Fig. 2 [6]. 

The simplest and most common temperature program is the single linear ramp illustrated earher. More complex programs, with multiple ramps interrupted by isothermal intervals may be designed to optimize critical separations and minimize overall analysis time. Environmental and biological samples often contain very slowly eluting heavier background contaminants of no interest to the analysis, which must be cleared off the column before the next injection, lest they elute with and interfere with analyte peaks from... 

The range of separation effects that chromatographers can produce is greatly expanded when the column temperatnre comes into play. However, the relationship of retention time to column temperature is nonlinear, and individual peaks are not equally affected by temperature shifts. In fact, as we shall see, peaks often will merge or even reverse their elution order as isothermal temperatures or temperature programs are modified. These more complex thermal relationships combine with the infinences of the column physical dimensions and the carrier-gas flow to make a fnlly delineated model of a particular separation beyond the capability of many chromatographers to construct using tools such as a scientific calculator or a spreadsheet. Computerized models of separation behavior can provide the necessary functionality for fully enabled optimization. 

Here kf is the retention factor from eqnation 4.5 expressed as a function of the temperature program, and tu,t expresses the effect of changing temperature on the unretained peak time. This type of calculation is conveniently carried out on a personal computer using either a commercially available elution prediction program or a spreadsheet, and we will discuss it in more detail in the next section on computerized optimization. 

Figure 4.14 shows a screen dump of an isothermal gas chromatographic simulation from a commercial gas chromatographic optimization program. The Temperature, Pressure, and Column tabs in the display permit the user to set elution conditions, including multiramp temperature and pressure programming, which were not exercised for this example. The Auto-Optimize tab carries out a minimum-resolution-oriented optimization calculation, which determines a set of conditions that lie within specified limits and meet the minimum resolution criterion. 

These mathematical models enable prediction of isothermal or temperature-programmed retention times with very good accuracy, and so chromatographers can estimate the effects of changing conditions on peak elution sufficiently well to provide a good basis for optimization. These models do not take into account any of the band-broadening processes that determine peak shapes, and therefore alone they cannot predict peak resolution, Trennzahl or separation number, or any other measurement of chromatographic quality. 

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