Solubility characteristics parameters

A second physicochemical parameter influencing chemical penetration through membranes is the relative lipid solubility of the potential toxicant that can be ascertained from its known partition coefficient. The partition coefficient is a measure of the ability of a chemical to separate between two immiscible phases. The phases consist of an organic phase (e.g., octanol or heptane) and an aqueous phase (e.g., water). The lipid solvent used for measurement is usually octanol because it best mimics the carbon chain of phospholipids, but many other systems have been reported (chloroform/water, ether/water, olive oil/water). The lipid solubility and the water solubility characteristics of the chemical will allow it to proportionately partition between the organic and water phase. The partition coefficients can be calculated using the following equation ... 

The characteristic parameters of the lamellar structure are the total thickness d of a sheet, the thickness dA of the layer containing the most soluble blocks, the thickness dB of the layer containing the less soluble blocks, and the average surface 2 available for a molecule at the interface. 

The solubility parameter model has difficulty with temperature effects and also fails to predict solubilities in several instances, such as with silicones. However it is a good starting point for estimating the solubility characteristics of a SCF as a function of temperature and pressure. The most likely temperatures and pressures under which a material is soluble in a supercritical fluid are where the solubility parameters are within a value of unity of each other. See Fig. 1, taken from Fig. 2 of Ref 5 by Allada, for a graph of 6 versus T and P for CO2. This effect allows one to selectively remove a particular component from a material by tuning the 5 of the SCF using T and P. 

A thermodynamic method, more fitting to this chapter, has been proposed by Nauman et al. They claim a process for the separation of a physically mixed solid polymers by selective dissolution. They rely on the different polymer solubility characteristics. Tables of this property have been reported and are based on regular solution theory and Hildebrand solubility parameters. The core of the Nauman invention is to find suitable solvents to dissolve particular polymers under defined temperature and pressure conditions. A mixture of polymers is first added to one solvent, at a given temperature, in order to dissolve a particular polymer. The remaining polymer mixture is then treated at a higher temperature with the same solvent or with a different solvent. For clarity, two examples are taken from the patent."... 

The standard molecular structural parameters that one would like to control in block copolymer structures, especially in the context of polymeric nanostructures, are the relative size and nature of the blocks. The relative size implies the length of the block (or degree of polymerization, i.e., the number of monomer units contained within the block), while the nature of the block requires a slightly more elaborate description that includes its solubility characteristics, glass transition temperature (Tg), relative chain stiffness, etc. Using standard living polymerization methods, the size of the blocks is readily controlled by the ratio of the monomer concentration to that of the initiator. The relative sizes of the blocks can thus be easily fine-tuned very precisely to date the best control of these parameters in block copolymers is achieved using anionic polymerization. The nature of each block, on the other hand, is controlled by the selection of the monomer for instance, styrene would provide a relatively stiff (hard) block while isoprene would provide a soft one. This is a consequence of the very low Tg of polyisoprene compared to that of polystyrene, which in simplistic terms reflects the relative conformational stiffness of the polymer chain. 

Mixing anionic and cationic surfactants results in the formation of an equimolar catanionic species, which is likely to precipitate even at very low concentration, because it is more hydrophobic (two tails) and less ionic (the charges cancel out at least partially). It was shown, however, that this equimolar catanionic surfactant tends to behave as a hydrophobic amphoteric, i.e. ionic surfactant, which is able to exhibit a linear mixing rule with either of the ionic species provided its proportion remains small, say, less than 20% [57]. For instance, if 5 wt.% of a cationic surfactant is added to 95 wt.% of anionic surfactant, the actual mixture behaves as if it were a mixture of 90 wt.% anionic and 10 wt.% catanionic surfactant. In practice, the pure catanionic species precipitates and hence does not exist as a soluble substance in the microemulsion. Hence, its characteristic parameter has to be estimated by extrapolating the linear trends of the 1 1 mixture, as seen in Fig. 3.10(c). 

Table 20.1. The characteristics parameters for the bulk-surface proton transfer in the absence of soluble buffers.

Soybean oil is miscible with many non-polar organic solvents. The solubility characteristics of vegetable oils in various solvents can be estimated from their dielectric constants or solubility parameters (Sipos and Szuhaj 1996a). Anhydrous or aqueous ethanol is not a good solvent for soybean oil at ambient temperature. Solubility increases with temperature until the critical solution temperature is reached, at which point the oil and ethanol become miscible. The solubility of oxygen in soybean oil contributes to the oxidative stability of the oil. It varies from 1.3 to 3.2ml/100ml in refined and crude oils. The solubility of water in soybean oil is about 0.071% at —1°C and 0.141% at 32°C (Perkins 1995b). 

There have been several efforts to provide means for computation of the interfacial tension coefficient from characteristic parameters of the two fluids [Luciani et al., 1996a]. The most interesting relation was that found between the interfacial tension coefficient and the solubility parameter contributions, that are calculable from the group contributions. The relation makes it possible to estimate the interfacial tension coefficient from the unit structure of macromolecules at any temperature. The correlation between the experimental and calculated data for 46 polymer blends was found to be good — the correlation coefficient R = 0.815 — especially when the computational and experimental errors are taken into account. 

Figure 2.1 Solubility coefficient of CO2 in PC at infinite dilution reported as a function of inverse temperature. The SAFT and NE-SAFT calculations are also reported. The characteristic parameters used for the regression are listed in Table 2.1...

Figure 2.2 Solubility isotherm of C Hg in PDMS at 35° C (>5g). The equilibrium models SAFT-PC (x symbols) and PHSC-SW (dashed line) provide good predictions of the solubility in a pure predictive way (k j = 0). A slight adjustment of the binary parameter (k j = I — i ) j = 0.032) is needed by the LF EoS (solid line). The characteristic parameters used for the calculations are listed in Table 2.2...

In Figure 2.7, we report the case of two glassy polymer blends the solubility of CH4 in PS-TMPC (tetramethyl polycarbonate) blends of different compositions (0-20-40-60-100% of PS) is shown in Figure 2.7a at 35° while the solubility isotherms of COj in five different blends of (bisphenol-chloral) polycarbonate (BCPC) and PMMA (0-25-50-75% of PMMA)[" 1 at 35° C are shown in Figure 2.7b. The NELF estimation of the solubility is also reported, based only on the pure component characteristic parameters... 

Because of the solubility characteristics of polystyrene, which has a solubility parameter value of 9.2 (cal/cm ) or 18.5 (J/M ) x 10 polystyrene-based polymer reagents or catalysts are especially suitable for organic reactions because they are readily soluble or swollen in common organic solvents such as benzene, chloroform, and methylene chloride for organic reactions. Some of the reactions run on polystyrene include epoxidations, peptide syntheses, separations of chiral molecules, and acid catalysis. 

More recently a number of systems using three solubility parameters has therefore been suggested in order to predict the solubility characteristics of polymers more precisely. Hildebrand s original theory was intended only for application to mixtures of non-polar liquids and for such liquids the intermolecular forces are only one type, namely dispersion forces. For other liquids, as discussed, also polar and hydrogen bonding forces play a role, and it has been argued by several workers that a solvent should be described by a parameter representing each of these three types of intermolecular forces [10]. 

Such migration requires only partial miscibility in the polymer matrix, silicone in the particular case studied by Stein et al. Owen and co-workers [9] have suggested that solubility parameter calculations can be useful in designing suitable compositions with partial miscibility. These ideas appear superficially to be at odds with compatibility/penetration and interpenetrating network concepts. However, these contrary solubility requirements are a consequence of the initial placement of the adhesion promoter. When used as a primer, it is already placed at the interface so needs no partial solubility characteristic to drive it there, as is needed when it is initially dispersed throughout the polymer matrix. In both cases it is the development of a strengthening interfacial phase that accounts for the enhancement in adhesion that is sought by the user. 

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