Mobile-phase composition, optimal

Figure 4.26. Experimental design for mobile phase composition optimization using a grid search (A) and simplex search (B).

The development of micellar liquid chromatography and accumulation of numerous experimental data have given rise to the theory of chromatographic retention and optimization methods of mobile phase composition. This task has had some problems because the presence of micelles in mobile phase and its modification by organic solvent provides a great variety of solutes interactions. 

Usually goodness of fit is provided by adding new parameters in the model, but it decreases the prediction capability of the retention model and influences on the optimization results of mobile phase composition. 

For preparative separation, the mobile phase can be selected by performing preliminary analytieal TLC experiments. In PLC, the chromatographic chamber has to be saturated within 2 h beeause the development of preparative plates is much slower than the analytical development. In the analytical preassay during the selection of mobile phase composition, the chromatographic chamber must be hned with a sheet of filter paper to obtain a saturated atmosphere with mobile phase vapor. Then, the optimized analytical mobile phase can be transferred imchanged to preparative separations in the saturated developing chamber. 

The separation can be optimized by the alteration of the mobile phase composition. The more the polarity of solutes, the less the content of water of mobile phase must be. If water-alcohol mixmre is used as mobile phase, the resolution can be improved by using alcohol witli different chain lengths and different water proportions. 

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]. 

Morita et al. [69] optimized the mobile phase composition using the PRISMA model for rapid and economic determination of synthetic red pigments in cosmetics and medicines. The PRISMA model has been effective in combination with a super modihed simplex method for fadhtating optimization of the mobile phase in high performance thin layer chromatography (HPTLC). 

Cimpoiu et al. [72] made a comparative study of the use of the Simplex and PRISMA methods for optimization of the mobile phase used for the separation of a group of drugs (1,4-benzodiazepines). They showed that the optimum mobile phase compositions by using the two methods were very similar, and in the case of polar compounds the composition of the mobile phase could be modified more precisely with the Simplex method than with the PRISMA. 

Pelander et al. [81] developed a computer program for optimization of the mobile phase composition in TLC. They used the desirability function technique combined with the PRISMA model to enhance the quahty of TLC separation. They apphed the statistical models for prediction of retardation and band broadening at different mobile phase compositions they obtained using the PRISMA method the optimum mobile phase mixtures and a good separation for cyanobacterial hepatotoxins on a normal phase TLC plate and for phenolic compound on reversed-phase layers. 

The popularity of reversed-phase liquid chromatography (RPC) is easily explained by its unmatched simplicity, versatility and scope [15,22,50,52,71,149,288-290]. Neutral and ionic solutes can be separated simultaneously and the rapid equilibration of the stationary phase with changes in mobile phase composition allows gradient elution techniques to be used routinely. Secondary chemical equilibria, such as ion suppression, ion-pair formation, metal complexatlon, and micelle formation are easily exploited in RPC to optimize separation selectivity and to augment changes availaple from varying the mobile phase solvent composition. Retention in RPC, at least in the accepted ideal sense, occurs by non-specific hydrophobic interactions of the solute with the... 

Some kinds of chromatography require relatively little optimization. In gel permeation chromatography, for example, once the pore size of the support and number of columns is selected, it is only rarely necessary to examine in depth factors such as solvent composition, temperature, and flow rate. Optimization of affinity chromatography is similarly straightforward. In RPLC or IEC, however, retention is a complex and sensitive function of mobile phase composition column type, efficiency, and length flow rate gradient rate and temperature. 

A reversed phase method (Method 3) was used for the optimization of the LANA reaction scheme (scheme 5 Figure 13). With slight modification of the mobile phase composition, it was also used for steps 1 to 3 of the LANA route (Figure 12). 

Method 3 was modified to an internal standard method into Method 5 by changing the bonded phase and the mobile phase composition. Biphenyl was used as an internal standard added into the reaction. Aliquots were withdrawn, diluted with degassed acetonitrile, and analyzed according to Method 5. This internal standard method, Method 5, was helpful in the optimization of the desired ris-1,2/1,4 product of the key step of the LANA reaction (scheme 5). 

Adequate resolution of the components of a mixture in the shortest possible time is nearly always a principal goal. Establishing the optimum conditions by trial and error is inefficient and relies heavily on the expertise of the analyst. The development of computer-controlled HPLC systems has enabled systematic automated optimization techniques, based on statistical experimental design and mathematical resolution functions, to be exploited. The basic choices of column (stationary phase) and detector are made first followed by an investigation of the mobile phase composition and possibly other parameters. This can be done manually but computer-controlled optimization has the advantage of releasing the analyst for other... 

A new HP-TLC method has been applied for the quantitative analysis of flavonoids in Passiflora coerulea L. The objective of the experiments was the separation and identification of the compound(s) responsible for the anxiolytic effect of the plant. Samples were extracted with 60 per cent ethanol or refluxed three times with aqueous methanol, and the supernatants were employed for HPTLC analysis. Separation was performed on a silica layer prewashed with methanol and pretreated with 0.1 M K2HP04, the optimal mobile phase composition being ethyl acetate-formic acid-water (9 1 l,v/v). It was established that the best extraction efficacy can be achieved with 60 - 80 per cent aqueous methanol. The HPTLC technique separates 10 different flavonoids, which can be used for the authenticity test of this medicinal plant [121],... 

Fig. 2.48. Separation of an extract by HPLC under optimized conditions in a 250 mm X 2 mm i.d., 5 pm particle, C18 column. The mobile phase was a gradient prepared from 0.03 per cent TFA in water (a) and acetonitrile (b) mobile phase composition (%) was changed from 90a 10b to 64a 36b in 35 min. The flow rate was 0.2 ml/min, the temperature 25°C, and detection was performed at 210 and 330 nm. Peak assignments 1 = pseudochlorogenic acid 2 = neochlorogenic acid 3 = chlorogenic acid 4 = cryptochlorogenic acid 5 = cynarin 6 = cynaroside 7 = scolymoside 8 = 3,4-di-O-caffe- oylquinic acid 9 = 1,3-di-O-caffeoylquinic acid 10 = 4,5-di-O-caffeoylquinic acid 11 = cynaropikrin. Reprinted with permission from M. Hausler et al. [148].

Retention theory from the work of Lanin and Nikitin [55] (Equation 1.6) was adapted to describe the dependency of retention factors k) as a function of the mobile phase composition [53]. The concentration of the polar modifier is, besides the type, the primary variable for the optimization of the separation and can be described by competitive adsorption reactions of solute (i.e., sorbate) and polar modifier for which the following relationship can be applied (Equation 1.6)... 

In the development and optimization of a comprehensive LCxLC method, many parameters have to be taken in acconnt in order to accomplish snccessfnl separations. First of all, selectivity of the columns used in the two dimensions must be different to get maximum gain in peak capacity of the 2D system. For the experimental setup, column dimensions and stationary phases, particle sizes, mobile-phase compositions, flow rates, and second-dimension injection volumes should be carefully selected. The main challenges are related to the efficient coupling of columns and the preservation of mobile phase/column compatibility. 

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