Retention optimization

This relationship has been experimentally verified for numerous mobile phases (and different solvents) and a wide variety of solutes, with both alumina (IS) and silica (18) as adsorbents. Some examples of the applicability of Eq. (31a) in these LSC systems are given in Fig. 15a (alumina) and Fig. 15b (silica). The use of 3-solvent or 4-solvent mobile phases (18, 20) allows the continuous variation ofm while holding e° constant, which greatly facilitates retention optimization by maximizing a without changing c°. 

Fig. 22. Hypothetical example of retention optimization in liquid-solid chromatography. (a) Solvent strength k is optimized (b) selectivity a.

Fig. 23. The solvent selectivity triangle for separations on silica LD, localized dipole LB, localized base, (a) general form (b) seven compositions for retention optimization. Reprinted with permission from Glajch el a . (20),...

When this procedure is repeated for every possible pair of overlapping bands in the sample, and the/ s plots for each band pair are superimposed, the ORM plot of Fig. 25b results. Now it is seen that the white area for R > 1.0 is very much reduced. Also indicated (x) is the optimum composition for maximizing the resolution of the most poorly separated band pair. The actual separation based on this optimum mobile-phase composition is shown in Fig. 26 for several nominally similar 25-cm silica columns. The desired resolution (Rg > 1.0) is indeed observed for all three columns. This is an important point when retention optimization is applied to complex mixtures if column-to-column variability in retention is significant, an optimum separation on one column may not be transferable to... 

Once retention optimization has been achieved as in Fig. 26, further increase in / s can usually be achieved by increase in column length (see Ref. 44). This is shown for the separation of Fig. 26 in Fig. 27, where column length is doubled by connecting two 25-cm columns in series. The time required for separation is now doubled, but the separation of band pair 7-11 is improved, as is the resolution of an impurity on the side of band 9. 

In the past, several theoretical models were proposed for the description of the reversed-phase retention process. Some theories based on the detailed consideration of the analyte retention mechanism give a realistic physicochemical description of the chromatographic system, but are practically inapplicable for routine computer-assisted optimization or prediction due to then-complexity [9,10]. Others allow retention optimization and prediction within a narrow range of conditions and require extensive experimental data for the retention of model compounds at specified conditions [11]. 

In the optimization of an HPLC method different steps can usually be considered (Fig. 6.1). If only the solvent composition of the mobile phase (i.e. types and amounts of organic modifiers) are considered, one often first optimizes the retention of the substances by selecting a mobile phase with an acceptable solvent strength retention optimization). Retention has to be sufficiently high to achieve separation of the compounds of interest, but also sufficiently low to obtain an acceptable analysis time. Conditions leading to an acceptable retention do not necessarily lead to the separation of all peaks. In a next step the organic modifier composition is adapted (e.g. replacement of one organic modifier by another one) in order to achieve selectivity selectivity optimiza-... 

Sometimes other variables must be investigated such as the pH and/or the ionic strength of the buffer in the mobile phase or the concentration of additives in the mobile phase such as for instance tensio-active substances in micellar chromatography. In such a case the first step in an optimization is to screen these factors and to identify the most important ones for the subsequent optimization. The screening (Section 6.4.2) leads to a definition of the experimental domain in which the optimum is probably situated. This is somewhat similar to the retention optimization step. It is followed by an optimization step (Sections 6.4 and 6.7), in which the most important variables are changed, often according to an experimental design. Similar methods are used in capillary zone electrophoresis. 

The PRDDO (partial retention of diatomic differential overlap) method is an attempt to get the optimal ratio of accuracy to CPU time. It has been parameterized for the periodic elements through Br, including the 3rd row transition metals. It was parameterized to reproduce ah initio results. PRDDO has been used primarily for inorganic compounds, organometallics, solid-state calculations, and polymer modeling. This method has seen less use than other methods of similar accuracy mostly due to the fact that it has not been incorporated into the most widely used semiempirical software. 

Additional improvements have been incorporated since 1966 with the availabihty of thinner float glass. Glass thickness and interlayer thickness have been studied to optimize the product for occupant retention, occupant injury, and damage to the windshield from external sources (30,31). The thinner float glass windshields are more resistant to stone impacts than the early plate glass windshields. The majority of laminated windshields are made of two pieces of 2—2.5 mm aimealed glass and 0.76 mm of controlled adhesion interlayer. 

All filters require a filter medium to retain solids, whether the filter is for cake filtration or for filter-medium or depth filtration. Specification of a medium is based on retention of some minimum parficle size at good removal efficiency and on acceptable hfe of the medium in the environment of the filter. The selection of the type of filter medium is often the most important decision in success of the operation. For cake filtration, medium selection involves an optimization of the following factors ... 

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. 

Although it is often possible to predict the effect of the solvent on retention, due to the unique interactive character of both the solvents and the enantiomers, it is virtually impossible to predict the subtle differences that control the separation ratio from present knowledge. Nevertheless, some accurate retention data, taken at different solvent compositions, can allow the retention and separation ratios to be calculated over a wide range of concentrations using the procedure outlined above. From such data the phase system and the column can be optimized to provide the separation in the minimum time, a subject that will be discussed later in the treatment of chromatography theory. 

It is seen that the curves in Figure (24) become horizontal between 40°C and 45 °C as predicted by the theory. It is also clear that there is likely source of error when exploring the effect of solvent composition on retention and selectivity. It would be important when evaluating the effect of solvent composition on selectivity to do so over a range of temperatures. This would ensure that the true effect of solvent composition on selectivity was accurately disclosed. If the evaluation were carried out at or close to the temperature where the separation ratio remains constant and independent of solvent composition, the potential advantages that could be gained from an optimized solvent mixture would never be realized. 

In contrast molecular interaction kinetic studies can explain and predict changes that are brought about by modifying the composition of either or both phases and, thus, could be used to optimize separations from basic retention data. Interaction kinetics can also take into account molecular association, either between components or with themselves, and contained in one or both the phases. Nevertheless, to use volume fraction data to predict retention, values for the distribution coefficients of each solute between the pure phases themselves are required. At this time, the interaction kinetic theory is as useless as thermodynamics for predicting specific distribution coefficients and absolute values for retention. Nevertheless, it does provide a rational basis on which to explain the effect of mixed solvents on solute retention. 

It is seen that the separation ratio must be greater than about 1.055 for a low efficiency column (2500 theoretical plates) before accurate retention measurements can be made on the composite curve. On the high efficiency columns (10,000 theoretical plates), the separation ratio need only be in excess of about 1.035 before accurate retention measurements can be made on the composite curve. It will be seen later in this chapter that to optimize a column for a difficult separation, accurate retention data must be obtained over a range of temperatures and solvent compositions. It follows that ... 

The task of synthesizing an optimal RON can be stated as follows For a given feed flowrate, Qf. and a feed concentration, Cp. it is desired to synthesize a minimum cost system of reverse osmosis modules, booster pumps and energy-recovery turbines Chat can separate the feed into two streams an environmentally acceptable permeate and a retentate (reject) stream in which the undesired species is concentrated. The permeate stream must meet two requirements ... 

However, for very highly retained solutes direet measurement of the eapaeity faetor ks is not possible, and this parameter must be predieted on the basis of retention data determined with a stronger mobile phase. The determination of Vb is an essential step in the optimization of traee enriehment and elean-up proeedures. 

When analytes lack the selectivity in the new polar organic mode or reversed-phase mode, typical normal phase (hexane with ethanol or isopropanol) can also be tested. Normally, 20 % ethanol will give a reasonable retention time for most analytes on vancomycin and teicoplanin, while 40 % ethanol is more appropriate for ristocetin A CSP. The hexane/alcohol composition is favored on many occasions (preparative scale, for example) and offers better selectivity for some less polar compounds. Those compounds with a carbonyl group in the a or (3 position to the chiral center have an excellent chance to be resolved in this mode. The simplified method development protocols are illustrated in Fig. 2-6. The optimization will be discussed in detail later in this chapter. 

Typical normal-phase operations involved combinations of alcohols and hexane or heptane. In many cases, the addition of small amounts (< 0.1 %) of acid and/or base is necessary to improve peak efficiency and selectivity. Usually, the concentration of polar solvents such as alcohol determines the retention and selectivity (Fig. 2-18). Since flow rate has no impact on selectivity (see Fig. 2-11), the most productive flow rate was determined to be 2 mL miiT. Ethanol normally gives the best efficiency and resolution with reasonable back-pressures. It has been reported that halogenated solvents have also been used successfully on these stationary phases as well as acetonitrile, dioxane and methyl tert-butyl ether, or combinations of the these. The optimization parameters under three different mobile phase modes on glycopeptide CSPs are summarized in Table 2-7. 

Enantioresolution in capillary electrophoresis (CE) is typically achieved with the help of chiral additives dissolved in the background electrolyte. A number of low as well as high molecular weight compounds such as proteins, antibiotics, crown ethers, and cyclodextrins have already been tested and optimized. Since the mechanism of retention and resolution remains ambiguous, the selection of an additive best suited for the specific separation relies on the one-at-a-time testing of each individual compound, a tedious process at best. Obviously, the use of a mixed library of chiral additives combined with an efficient deconvolution strategy has the potential to accelerate this selection. 

Good rhodium retention results were obtained after several recycles. However, optimized ligand/metal ratios and leaching and decomposition rates, which can result in the formation of inactive catalyst, are not known for these ligands and require testing in continuous mode. As a reference, in the Ruhrchemie-Rhone-Poulenc process, the losses of rhodium are <10 g Rh per kg n-butyraldehyde. 

Reactor productivity was obtained by dividing final ethanol concentration with respect to sugar concentration at a fixed retention time. It was found that the rates of 1.3, 2.3 and 2.8 g 1 1 h 1 for 25, 35 and 50 g 1 1 glucose concentrations were optimal. Ethanol productivities with various substrate concentrations were linearly dependent on retention time (Figure 8.12). The proportionality factor may have increased while the substrate... 

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