Optimization of chromatographic system

The elaboration of the most efficient chromatographic systems for the optimization of velocity and resolution of the chromatographic process is necessary for solving different analytical problems. The most important factor in the TLC optimization is the mobile phase composition. Taking into consideration the similarity in the retention mechanism between TLC and PLC, the optimized TLC mobile phase can be transferred to the preparative chromatographic system. There are different accepted models and theories for the separation and optimization of chromatographic systems [19,20,61]. 

G. Matysik, E. Soczewinski, M. Wojciak-Kosior and E. Wojtasik, Optimization of chromatographic systems for the high-performance thin-layer chromatography of flavonoids. Chromatographia 52 (2000) 357-362. 

Soczewinski, E. Simple device for continuous thin-layer chromatography. J. Chromatogr. 1977,138,443-445. Glowniak, K. Soczewinski, E. Wawrzynowicz, T. Optimization of chromatographic systems for the separations of components of the furocoumarin fraction of Archangelica fruits on a milligram scale. Chem. Anal. 1987,32,797-811. 

Matysik, G., and Soczewinski, E. (1996). Computer-aided optimization of stepwise gradient TLC of plant extracts. J. Planar Chromatogr.—Mod. TLC 9 404-412. Matyska, M., and Soczewinski, E. (1993). Optimization of chromatographic systems in TLC by graphical method and with a computer program. Chem. Anal. (Warsaw) 38 555-563. 

Procedures used vary from trial-and-error methods to more sophisticated approaches including the window diagram, the simplex method, the PRISMA method, chemometric method, or computer-assisted methods. Many of these procedures were originally developed for HPLC and were apphed to TLC with appropriate changes in methodology. In the majority of the procedures, a set of solvents is selected as components of the mobile phase and one of the mentioned procedures is then used to optimize their relative proportions. Chemometric methods make possible to choose the minimum number of chromatographic systems needed to perform the best separation. 

P.J. Schoenmakers, A. Peeters and R.J. Lynch, Optimization of chromatographic methods by a combination of optimization software and expert systems. J. Chromatogr., 506 (1990) 169-184. 

The different adsorption and desorption events are controlled via the flow rates adjusted by the means of 3 or 5 external pumps and the column switch times, Fig. 3. The key element for success is the proper selection of the respective flow rates, which must be chosen in such a way that the extract front between zones I and II and the raffinate front between zones III and IV are stabilized, while the separation between zones II and III is assured. A simple trial-and-error approach to such an optimization of the system parameters is unlikely to be successful. Instead, the chromatographic behavior of all compounds has to be modeled and simulated. 

Another factor that contributes to Rs is the plate count N. However, we have seen in section 1.5 that optimization through an increase in N is expensive, not only in terms of equipment and columns, but also in terms of analysis time. Therefore, as long as the shape of the peaks and the plate height (length of the column divided by N) are satisfactory, we should not rely on the number of plates for optimization, unless as a last resort. Methods which may be used to optimize the chromatographic system with respect to the required number of plates will be described in chapter 7. 

Eqn.(7.15) is the key equation for the optimization of chromatographic sensitivity. Naturally, the peak height is proportional to the concentration of the solute in the sample and to the volume of the injected sample. However, this proportionality holds over a limited range and we cannot increase these two quantities indefinitely without having to sacrifice another vital characteristic of the system, the linearity of detection. The proportionality between cmax and the product cgV-in ends when N may no longer be considered as a constant. Consequently, the aforementioned product may be increased until the plate count starts to be affected. 

Lor a particular analytical separation, each biosolute will have an optimal k] value for maximum resolution with a designated column, flow rate, and mobile phase composition. Similar criteria apply in preparative (overload) chromatography with multicomponent mixtures, where resolution is similarly enhanced following optimization of chromatographic selectivity and zone bandwidth. The conventional approach to process purification with low molecular weight solutes has frequently been based on linear scale-up of the performance of an analytical column system. In these cases, high-resolution separations can be achieved often without the burden of conformational or... 

Chapter 7, therefore, deals with model-based design and optimization of a chromatographic plant, where the already selected chromatographic system and concepts are applied. First, basic principles of the optimization of chromatographic processes will be explained. These include the introduction of the commonly used objective functions and the degrees of freedom. To reduce the complexity of the optimization and to ease the scale-up of a plant, this chapter will also emphasize the application of dimensionless parameters and degrees of freedom respectively. Examples for the... 

The choice of chromatographic system and the process concept are influenced by the classification of the separation problem into one of the three scenarios of Fig. 4.4. This chapter focuses on the influence of the chromatographic system, while the influence on the process concept is explained in Chapter 5.4. Here, it should be kept in mind that the elution order of the components is essential for the whole process and the elution order is determined by the chromatographic system. Especially if one component is in excess, as in scenarios (a) and (c) in Fig. 4.4, the use of thermodynamic effects like displacement or tag along are a special source for optimization as well as for severe errors and mistakes (Chapter 2.6). 

If the analytical task is the qualitative or quantitative determination of an analyte at low concentration it is first necessary to optimize the chromatographic system. Under isocratic conditions the concentration at the peak maximum Cn,ax is lower than in the injection solution c, ... 

The selection of chromatographic systems is the most critical for process productivity and thus process economy. On one hand, the selection of the chromatographic system offers the biggest potential for optimization but, on the other hand, it is a potential source of severe errors in developing separation processes. 

The selection of a chromatographic system can be based on a systematic optimization of the system through extensive studies of solubility, retention, and selectivity, but, sometimes, the use of generic gradient runs with standard systems is sufficient. 

As only milligrams or grams of product were to be purified in the above examples, relatively little effort was made to optimize the chromatographic system and... 

Once the volatile compounds were extracted, they should be analyzed by gas-chromatography (GC). Depending on the characteristics of the extracts (solvent, anal3 es of interest), the GC conditions must be select and optimized. The chromatographic system is composed by an injector, a column inside an oven and a detector. A carrier gas is needed to transport the volatile compounds through the column depending on the detector, other gases may be required. Finally, an acquisition system collects the information that arrives to the detector. 

A chemometric approach where the /ty-values of forty-seven flavonoids in seven TLC systems were studied using principal component and cluster analyses, has made it possible to choose the minimum number of chromatographic systems needed to perform the best separation (20). Another method (the PRISMA model) based on Snyder s solvent selectivity triangle has been described to aid mobile phase optimization (21). This model is reported to give good separation of flavonol glycosides from Betula spp. (1). When tested in our laboratory no improvements were obtained in comparison with established systems (22) such as the solvent ethyl acetate-formic acid-acetic acid-water (100 11 11 27) on silica support, which can be used for separation of a wide range of flavonoids. 

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