Gradient separations optimization programs

Of course, the simultaneous optimization of different (primary) program parameters (initial and final composition, slope and shape of the gradient) and secondary parameters (nature and relative concentration of modifiers) may involve too many parameters, so that an excessive number of experiments will be required to locate the optimum. This problem may be solved by a separate optimization of the program (primary parameters) and the selectivity (secondary parameters) based on the concept of iso-eluotropic mixtures (see section 3.2.2). This will be demonstrated below (section 6.3.2.2). However, the transfer of... 

The Snyder procedure would have led to a quick solution of the separation problem shown in figure 6.11. However, the answer would have been different from that obtained with the Simplex optimization program. If we assume an S value of about 7 for the solutes involved and estimate the hold-up volume of the column to be around 1.18 mL (60% of the volume of the empty column), then we can estimate the b value for the gradient used in figure 6.11... 

Use of 10 pm LiChrosorb RP18 column and binary eluent of methanol and aqueous 0.1 M phosphate buffer (pH 4.0) according to suitable gradient elution program in less than 20-min run time with satisfactory precision sensitivity of spectrophotometric detection optimized, achieving for all additives considered detection limits ranging from 0.1 to 3.0 mg/1, below maximum permitted levels Simultaneous separation (20 min) of 14 synthetic colors using uncoated fused silica capillary column operated at 25 kV and elution with 18% acetonitrile and 82% 0.05 M sodium deoxycholate in borate-phosphate buffer (pH 7.8), recovery of all colors better than 82%... 

Optimization of the primary parameters of the gradient program may only lead to sufficient separation if the selectivity is sufficiently large. If the a values between one or more pairs of solutes are low, resolution may be enhanced by a reduction of the programming rate and by increasing the number of plates. However, this will be at the expense of increased analysis times and the resolution will never be better than under constant elution conditions. 

Figures 6.16e and 6.16f show two chromatograms using gradients which were predicted to yield insufficient separation. Using the optimization procedure of Jandera et al., a number of gradient programs can be tested by calculating the resulting chromatograms, so that the number of experiments required can be greatly reduced.

A second reason not to become involved in extensive calculations for the complete mathematical optimization of the (primary) program parameters is that a more powerful way to optimize the separation of all sample components in the mixture may be to optimize the selectivity of the gradient by varying the nature of the mobile phase components (secondary parameters). 

With the program and derived mathematics, the scientist can calculate the retention times and peak widths for any set of solutes, run under any conditions ranging from Isocratlc to complex gradients with multiple columns. Given this mathematical tool, the problem of determining which chromatographic conditions will achieve the desired separation, within any constraints, becomes the next problem to be approached. The solution to such an "optimization" problem Is not easy, however, the necessary universal mathematical tools are now available for researchers In this area to develop approaches to optimization strategies. 

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