Solute molar volume

Component 1 is the diffusing gas, while component 2 is the solvent. The solvent viscosity l2 in Pa sec, the solute molar volume at the normal boihng point Vi in mVkmole, and the solvent association parameter Xo multiplied by the solvent... 

The Stokes-Einstein equation predicts that DfxITa is independent of the solvent however, for real solutions, it has long been known that the product of limiting interdiffusion coefficient for solutes and the solvent viscosity decreases with increasing solute molar volume [401]. Based upon a large number of experimental results, Wilke and Chang [437] proposed a semiempirical equation,... 

In Table 3 are the values of surface tension for the aqueous LAS homolog solutions. Values of molar volume used are those for the pure LAS homolog independent of water. The justification for this comes from the Winsor R model (20, 21) and work by Scriven and Davis (30) who showed that accurate CED values can be obtained from a statistical mechanical treatment of an interface using only 2 or 3 atomic or molecular layers of that interface. For a surfactant solution, the surfactant will predominate in the interface, hence the choice of pure LAS for the solution molar volumes. 

Table 3.8 Solute molar volumes (Vb) at normal boiling point...

Solute mobility (k ) which is affected by temperature, solute molar volumes, and cuti-cular wax composition. 

Mog a = -1.93 + 3.06 WlOO + 0.56 n -3.20(3, where Vis a measure of solute molar volume and k and P are the solva-tochromic parameters that scale dipolarity/polarizabilities and hydrogen bond acceptor basicities of the adsorbates. 

From Eqs. 5.8a to 5.16, it is clear that the diffusion coefficient is a function of two parameters, the solvent viscosity and the solute molar volume, both of which depend on the pressiue. Thus, we can write... 

In this approach, the solute-solvent interactions are modeled using polarizability and the molar volume of the solute. Polarizability, O, is in turn modeled by Ketelaar s method (13). where an atomic contribution scheme is employed. Molar volume is in turn modeled by molecular connectivity indices, %, which are calculated using slightly modified algorithms (9), originally proposed by Kicr and Hall (14.15). These indices encode information on the molecular topology and its hctcroatom content. They have been shown to correlate well with the solutes molar volume, and... 

Electrotopological indices have been used to predict permeability, computationally (Table 16-3). The electrotopological descriptors are not always easily comprehended, even though they can be attributed to describe hydropho-bicity, hydrophilicity, and size. Other typical 2D generated descriptors are related to dispersion forces, polarizability, solute molar volume, and hydrogen bonding acidity and basicity [44-47]. Descriptors such as log Poct/log Doct,... 

The Perturiiatioii Treatment.—Based on a statistical solution theory of Longuet-Higgins, a first-order perturbation approach to the free energy of solution has been developed by Luckhurst and Martire and by Tewari et al. This theory appears useful for interpreting the interaction parameters within a series of structurally related solute molecules in the same solvent. It is thus ideally suited for testing data obtained from g.l.c. experiments. The theory involves a comparison of two solutes - a reference one and a perturbed one in a common solvent. The interaction parameter x is shown to be linearly related to Ty( V y where Tf and Ff are the solute critical temperature and the solute molar volume at temperature 0.675 respecively. The term 75/( Ff ) is a measure of the depth of the interaction potential well. ... 

For smaller solute molar volumes, Eq. (6.3-8) does not hold. Several other theoretical derivations have been attempted, but the equations do not predict diffusivities very accurately. Hence, a number of semitheoretical expressions have been developed (Rl). The Wilke-Chang (T3, W5) correlation can be used for most general purposes where the solute (A) is dilute in the solvent (B). 

Prediction of diffusivities for biological solutes. For predicting the diffusivity of small solutes alone in aqueous solution with molecular weights less than about 1000 or solute molar volumes less than about 0.500 m /kg mol, Eq. (6.3-9) should be used. For larger solutes the equations to be used are not as accurate. As an approximation the Stokes-Einstein equation (6.3-8) can be used. 

The experimental quantities reported in the study publication are indicated in the 10th column density (d) differential density (solution density minus water density) (dd) solution molar volume (V) solution specific volume (Vs) apparent molar volume (Vf) solute infinite dilution partial molar volume (Vo), excess volume (Ve), volume of mixing (Vm), compressibility factor (Z), virial coefficients (B, C, D, E), and soimd velocity (sv). 

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