Correlation with solubility parameters

The isolation and/or identification of nonpolymerics has been described, including analyses for residual monomers (90,102,103) and additives (90,104—106). The deterrnination of localized concentrations of additives within the phases of ABS has been reported the partitioning of various additives between the elastomeric and thermoplastic phases of ABS has been shown to correlate with solubility parameter values (41). 

The purpose of this paper is to use data already aquired on critical surface tension for a correlation with solubility parameters and parachors of polymers. The theoretical background of these parameters is briefly mentioned. The evaluation of the calculated values is then discussed. Because of the complexity of the polymer conformation on the surface, we do not imply that a straight-forward relationship between the surface and the bulk properties is available, even in the case of a liquid-like amorphous polymer. Another purpose of this paper is, therefore, to point out the complicating factors and the difficulties in predicting the surface wettability on the basis of bulk properties. 

Antioxidants have been shown to improve oxidative stability substantially (36,37). The use of rubber-bound stabilizers to permit concentration of the additive in the rubber phase has been reported (38—40). The partitioning behavior of various conventional stabilizers between the rubber and thermoplastic phases in model ABS systems has been described and shown to correlate with solubility parameter values (41). Pigments can adversely affect oxidative stability (32). Test methods for assessing thermal oxidative stability include oxygen absorption (31,32,42), thermal analysis (43,44), oven aging (34,45,46), and chemiluminescence (47,48). 

Dilution ratio, DR, is used to express the tolerance of solvents to diluents, most frequently, toluene. DR is the volume of a solvent added to a given solution that causes precipitation of the dissolved resin. This ratio can characterize the compatibility of a diluent with a resin solution in primary solvent. When compatibility is high, more diluent can be added. Only a multi-parameter approach provides a satisfactory correlation with solubility parameters. DR depends on the polymer concentration. With polymer concentration increasing, DR increases as well. T emperature influences DR in a similar manner. Determination of DR must be performed at standard conditions. DR can be related to the solubility parameters but such correlation depends on concentration. 

Figure 10. Correlations of solubility parameter with (a) Sj/SaS, ratio and (b) fi-parameter for different polymeric membrane materials (56)...

Comparison of n values with solubility parameters for the various liquids and fluids, calculated as described by Giddings and coworkers (10), shows a general correlation for the less polar solvents. Ammonia and the polar liquid solvents diverge from this correlation, suggesting the operation of specific interactions which contribute to the greater magnitude of the shifts observed for ammoni a. 

At a given temperature, a solvent for the polymer should have a (5-value approximately between the limits, indicated by the two straight lines in the figure. An even better correlation of Flory-temperatures with solubility parameters can be given in a <5h-<5v-diagram. This is shown in Fig. 7.9 for polystyrene. The circle drawn in Fig. 7.9 corresponds again with Eq. (7.18). 

The value of kd was obtained from the determination of triplet lifetimes by measuring the decay of phosphorescence and found to be insensitive to changes in solvent polarity. The k2 values derived from Eqs. 10 and 11 were correlated with solvent parameters using the linear solvation energy relationship described by Abraham, Kamlet and Taft and co-workers [18] (Eq. 12), which relates rate constants (k) to four different solvation parameters (1) or the square of the Hildebrand solubility parameter (solvent cohesive energy density), (2) n or solvent dipolarity or polarizability, (3) a, or solvent hydrogen bond donor acidity (solvent electrophilic assistance), and (4) or solvent hydrogen bond acceptor basicity (solvent nucleophilic assistance). 

Compound solubility and permeability were identified as key factors in advancing these 2245 compounds into human trials. The authors compared the calculated properties of these compounds with the corresponding properties of the compounds of the entire database. Four parameters appeared to be correlated with solubility and permeability, namely molecular weight (MW), log P,... 

The relationship between chemical structure, lipophilicity and its disposition in vivo has been reviewed by a number of authors (e.g., Koehler et al. 1988). It has been shown that many biological phenomena can be correlated with this parameter, such that quantitative structure activity relationships (QSARs) maybe deduced. These include solubility, absorption potential, membrane permeability, plasma protein binding, volume of distribution and renal and hepatic clearance. 

Aqueous solubility data for the 12 aromatic hydrocarbons studied in this investigation are reported in this section. The solubilities determined spanned a range of 106. The solubilities measured at 25°C are compared with values reported by other investigators and are correlated with molecular parameters such as carbon number, molar volume, and molecular length. 

SOME CORRELATIONS OF RATES WITH SOLUBILITY PARAMETER... 

FIGURE 5.11 Correlation of rate constants for decarboxylation of 3,3-difluoro—4, 4-diethyloxetan—2-one at 168.1°C with solubility parameters of the solvents. (Rate constants from Ocampo, et al., 1997.)... 

Table 4.3 Examples of QSAR models for estimating water solubility log correlations with various parameters (S in mol/1).

Solubility parameters can be determined by direct measurement, correlations with other physical parameters, or indirect calculations. The solubility parameters of solvents usually can be determined directly. The following methods can be used to develop correlations between solubility parameters and other physical properties of solvents. 

Tfaeie have been a number of attempts to develop solvent parameter scales that could be used to correlate ttiermodynamic and kinetic results in terms of these patametois. Gutmann s Donor Numbers, discussed previously, are sometimes used as a solvent property scale. Kamlet and Taft and co-workers developed the solvatochromic parameters, Uj, B, and n that are related to the hydrogen bonding acidity, basicity and polarity, respectively, of the solvent. Correlations with these parameters also use the square of tte Hildebrand solubility parameter, (5, that gives the solvent cohesive energy density. Parameters for some common solvents are collected in Table 3.6. 

Suitable sensor array combinations can be easily predicted by computer simulation based on the Linear Energy Relationship (LSER) Models. This model correlates the solubility parameters with known physicochemical properties of the materials such as polarizability, polarity, acidity, basicity and geometrical factor, placed as sorption materials on the SAW s. Thus such a computer simulation leads to an optimization of the sensor array combination for a given task and replaces costly and time-consuming experimental work in the laboratory. 

Solubility parameters can be determined by direct measurements, indirect calculations, or correlations with other physical parameters. The solubility parameters of solvents usually can be determined directly by measuring the energy of vaporization. The solubility parameters of polymers can only be determined indirectly and may be affected by variations in their chemical constitutions, i.e., the number of crosslinks and the distribution of chain branches or substitutive groups along the polymer backbone. The methods presented in this section can be used to develop correlations of solubility parameters with other physical properties for specific commercial polymer products or to estimate the solubility parameters of new polymers. 

Numerous reports of comparable levels of success in correlating adhesion performance with the Scatchard-Hildebrand solubility parameters can be found in the literature [116,120-127], but failures of this approach have also been documented [128-132J. Particularly revealing are cases in which failure was attributed to the inability of the Scatchard-Hildebrand solubility parameter to adequately account for donor-acceptor (acid-base) interactions [130,132]. Useful reviews of the use of solubility parameters for choosing block copolymer compatibilizers have been prepared by Ohm [133] and by Gaylord [134]. General reviews of the use of solubility parameters in polymer science have been given by Barton [135], Van Krevelen [114], and Hansen [136]. 

Extensive use of the three-dimensional solubility parameters for predicting adhesion seems not to have been made, although its additional flexibility should make it successful over a wider range of conditions than the single-parameter approach. Some recent studies involving dental adhesion employed the method with success. Asmussen and Uno fl40 successfully correlated the shear bond strength of various dental adhesive resins, characterized in terms of their three-... 

Strictly speaking Eq. (8-51) should be applied only to reacting systems whose molecular properties are consistent with the assumptions of regular solution theory. This essentially restricts the approach to the reactions of nonpolar species in nonpolar solvents. Even in these systems, which we recall do not exhibit a marked solvent dependence, correlations with tend to be poor. - pp Nevertheless, the solubility parameter and its partitioning into dispersion, polar, and H-bonding components provide some insight into solvent behavior that is different from the information given by other properties such as those in Tables 8-2 and 8-3. 

In this approach, connectivity indices were used as the principle descriptor of the topology of the repeat unit of a polymer. The connectivity indices of various polymers were first correlated directly with the experimental data for six different physical properties. The six properties were Van der Waals volume (Vw), molar volume (V), heat capacity (Cp), solubility parameter (5), glass transition temperature Tfj, and cohesive energies ( coh) for the 45 different polymers. Available data were used to establish the dependence of these properties on the topological indices. All the experimental data for these properties were trained simultaneously in the proposed neural network model in order to develop an overall cause-effect relationship for all six properties. 

The use of direct electrochemical methods (cyclic voltammetry Pig. 17) has enabled us to measure the thermodynamic parameters of isolated water-soluble fragments of the Rieske proteins of various bci complexes (Table XII)). (55, 92). The values determined for the standard reaction entropy, AS°, for both the mitochondrial and the bacterial Rieske fragments are similar to values obtained for water-soluble cytochromes they are more negative than values measured for other electron transfer proteins (93). Large negative values of AS° have been correlated with a less exposed metal site (93). However, this is opposite to what is observed in Rieske proteins, since the cluster appears to be less exposed in Rieske-type ferredoxins that show less negative values of AS° (see Section V,B). 

---