Distribution coefficient prediction

Figure 4. Distribution coefficients predicted from the two-phase sorption model.

The ternary diagrams shown in Figure 22 and the selectivi-ties and distribution coefficients shown in Figure 23 indicate very good correlation of the ternary data with the UNIQUAC equation. More important, however, Table 5 shows calculated and experimental quarternary tie-line compositions for five of Henty s twenty measurements. The root-mean-squared deviations for all twenty measurements show excellent agreement between calculated and predicted quarternary equilibria. 

In practice, it is more convenient to predict the behavior of an ion, for any chosen set of conditions, by employing a much simpler distribution coefficient, which is defined as the concentration of a solute in the resin phase divided by its concentration in the liquid phase, or ... 

These variations permit the separation of other components, if desired. Additional data on uranium, plutonium, and nitric acid distribution coefficients as a function of TBP concentration, solvent saturation, and salting strength are available (24,25). Algorithms have also been developed for the prediction of fission product distributions in the PUREX process (23). 

Whenever data are available for a given system under similar conditions of temperature, pressure, and composition, equilibrium distribution coefficients (iC = y/x) provide a much more rehable tool for predicting vapor-liquid distributions. A detailed discussion of equilibrium iC vahies is presented in Sec. 13. 

Co is the solution concentration of the initial charge, and X is the fraction frozen. Figure 22-4 illustrates the solute redistribution predicted by Eq. (22-2) r various values of the distribution coefficient. 

Strkcttire inflkence. The specificity of interphase transfer in the micellar-extraction systems is the independent and cooperative influence of the substrate molecular structure - the first-order molecular connectivity indexes) and hydrophobicity (log P - the distribution coefficient value in the water-octanole system) on its distribution between the water and the surfactant-rich phases. The possibility of substrates distribution and their D-values prediction in the cloud point extraction systems using regressions, which consider the log P and values was shown. Here the specificity of the micellar extraction is determined by the appearance of the host-guest phenomenon at molecular level and the high level of stmctural organization of the micellar phase itself. 

On the basis of data obtained the possibility of substrates distribution and their D-values prediction using the regressions which consider the hydrophobicity and stmcture of amines was investigated. The hydrophobicity of amines was estimated by the distribution coefficient value in the water-octanole system (Ig P). The molecular structure of aromatic amines was characterized by the first-order molecular connectivity indexes ( x)- H was shown the independent and cooperative influence of the Ig P and parameters of amines on their distribution. Evidently, this fact demonstrates the host-guest phenomenon which is inherent to the organized media. The obtained in the research data were used for optimization of the conditions of micellar-extraction preconcentrating of metal ions with amines into the NS-rich phase with the following determination by atomic-absorption method. 

It is seen that, as predicted, the function for the retention volume is indeed simple and depends solely on the distribution coefficient and the volumes of the two phases that are present in the column. 

When the relationship between the distribution coefficient of a solute and solvent composition, or the corrected retention volume and solvent composition, was evaluated for aqueous solvent mixtures, it was found that the simple relationship identified by Purnell and Laub and Katz et al. no longer applied. The suspected cause for the failure was the strong association between the solvent and water. As a consequence, the mixture was not binary in nature but, in fact, a ternary system. An aqueous solution of methanol, for example, contained methanol, water and methanol associated with water. It follows that the prediction of the net distribution coefficient or net retention volume for a ternary system would require the use of three distribution coefficients one representing the distribution of the solute between the stationary phase and water, one representing that between the stationary phase and methanol and one between the stationary phase and the methanol/water associate. Unfortunately, as the relative amount of association varies with the initial... 

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. 

MD simulations in expHcit solvents are stiU beyond the scope of the current computational power for screening of a large number of molecules. However, mining powerful quantum chemical parameters to predict log P via this approach remains a challenging task. QikProp [42] is based on a study [3] which used Monte Carlo simulations to calculate 11 parameters, including solute-solvent energies, solute dipole moment, number of solute-solvent interactions at different cutoff values, number of H-bond donors and acceptors (HBDN and HBAQ and some of their variations. These parameters made it possible to estimate a number of free energies of solvation of chemicals in hexadecane, octanol, water as well as octanol-water distribution coefficients. The equation calculated for the octanol-water coefficient is ... 

Tetko, I. V., Bruneau, P. Application of ALOGPS to predict 1-octanol/water distribution coefficients, log P, and log D, of AstraZeneca in-house database. 

While there are plenty of methods to predict 1-octanol-water partition coefficients, logP (see Chapters 14 and 15), the number of approaches to predict 1-octanol-water distribution coefficients is rather limited. This is due to a lower availability of log D data and, in general, higher computational complexity of this property compared to that of log P. The approaches to predict log D can be roughly classified into two major categories (i) calculation of log D at an arbitrary pH and (ii) calculation of log D at a fixed pH. 

Tetko, I. V., Poda, G. I. Application of ALOGPS 2.1 to predict logD distribution coefficient for Pfizer proprietary compounds. J. Med. Chem. 2004, 47, 5601-5604. 

Manners, C. N. Payling, D. W. Smith, D. A., Distribution coefficient, a convenient term for the relation of predictable physico-chemical properties to metabolic processes, Xenobiotica 18, 331-350 (1988). 

Barton, P. Davis, A. M. McCarthy, D. J. Webbom, P. J. H., Drug-phospholipid interactions. 2. Predicting the sites of drug distribution using n-octanol/water and membrane/water distribution coefficients. J. Pharm. Set 86, 1034—1039 (1997). 

The un-ionized form is assumed to be sufficiently lipophilic to traverse membranes in the pH-partition hypothesis. If it were not, no transfer could be predicted, irrespective of pH. The lipophilicity of compounds is experimentally determined as the partition coefficient (log P) or distribution coefficient (log D) [16]. The partition coefficient is the ratio of concentrations of the neutral species between aqueous and nonpolar phases, while the distribution coefficient is the ratio of all species between aqueous and nonpolar phases [17,18],... 

The distribution coefficient approach - commonly referred to as the K approach - is the most widely applied method in environmental geochemistry for predicting the sorption of contaminant species onto sediments. The distribution coefficient Kd itself is simply the ratio under specific conditions of the sorbed to the dissolved mass of a contaminant. Sorbed and dissolved mass are expressed in units such as... 

Potentially more significant is the fact that a single ion is used to represent the dissolved form of the contaminant in question, an assumption that can lead to serious error. Cadmium in a model calculated at pH 12, for example, is present primarily as the species Cd(OH)2 almost no free ion Cd++ occurs. Employing the reaction Kd model in terms of Cd++ in this case would predict a contaminant distribution unlike that suggested by the distribution coefficient, applied in the traditional sense. We see the importance of applying a Kd model to systems similar to that for which it was originally determined. 

These results differ sharply from the behavior predicted by the distribution coefficient (K( ) approach. This approach, despite being broadly acknowledged as too simplistic to describe the behavior of heavy metals, is nonetheless the sorption model most commonly applied in studying aquifer remediation. 

Model Studies. In model studies of adsorption, one deals with simple, well-defined systems, where usually a single well-characterized solid phase is used and the composition of the ionic medium is known, so that reactions competing with the adsorption may be predicted. It is not a trivial problem to compare the results from such model studies with those from field studies, or to use model results for the interpretation of field data. In field studies, a complex mixture of solid phases and dissolved components, whose composition is only poorly known, has to be considered competitive reactions of major ions and trace metal ions for adsorption may take place, and the speciation of the trace metal ions is often poorly understood. In order to relate field studies to model studies, distribution coefficients of elements between the dissolved and solid phases are useful. These distribution coefficients are of the following form ... 

The distribution coefficients are independent of the concentration of suspended solids in water, which can vary over a wide range they thus give a better picture than the fraction of metal ions in solution. Such distribution coefficients can be predicted on the basis of the equilibrium constants defining the complexation of metals by surfaces and their complexation by solutes (Table 11.1). 

Campbell, J.R., Luthy, R.G., and Carrondo, M.J.T. Measurement and prediction of distribution coefficients for wastewater aromatic solutes, Environ. Sci. Technol., 17(10) 582-590, 1983. 

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