Prediction of mutual diffusion

Since the prediction of mutual diffusion coefficients from self-diffusion coefficients is not accurate enough to be used for modeling of chemical processes, complete data sets of mutual and self-diffusion coefficients are necessary and valuable. 

In addition to temperature and concentration, diffusion in polymers can be influenced by the penetrant size, polymer molecular weight, and polymer morphology factors such as crystallinity and cross-linking density. These factors render the prediction of the penetrant diffusion coefficient a rather complex task. However, in simpler systems such as non-cross-linked amorphous polymers, theories have been developed to predict the mutual diffusion coefficient with various degrees of success [12-19], Among these, the most notable are the free volume theories [12,17], In the following subsection, these free volume based theories are introduced to illustrate the principles involved. 

Fig. 8.8 Free volume theory prediction of mutual binary diffusion coefficient for the toluene-PS system based on parameters (19). [Reproduced by permission from J. L. Duda, J. S. Vrentas, S. T. Ju and H. T. Liu, Prediction of Diffusion Coefficients, A.I.Ch.E J., 28, 279 (1982).]...

Dullien, F. A. L. and Asfour, A-F. A., Concentration Dependence of Mutual Diffusion Coefficients in Regular Binary Solutions A New Predictive Equation, Ind. Eng. Chem. Fundam., 24, 1-7 (1985). 

Rathbun, R. E. and Babb, A. L., Empirical Method for Prediction of The Concentration Dependence of Mutual Diffusivities in Binary Mixtures of Associated and Nonpolar Liquids, Ind. Eng. Chem. Proc. Des. Dev., 5, 273-275 (1966). 

Vrentas and Duda s theory formulates a method of predicting the mutual diffusion coefficient D of a penetrant/polymer system. The revised version ( 8) of this theory describes the temperature and concentration dependence of D but requires values for a number of parameters for a binary system. The data needed for evaluation of these parameters include the Tg of both the polymer and the penetrant, the density and viscosity as a function of temperature for the pure polymer and penetrant, at least three values of the diffusivity for the penetrant/polymer system at two or more temperatures, and the solubility of the penetrant in the polymer or other thermodynamic data from which the Flory interaction parameter % (assumed to be independent of concentration and temperature) can be determined. An extension of this model has been made to describe the effect of the glass transition on the free volume and on the diffusion process (23.) ... 

Whatever the specific system or situation, the key issue in diffusion interphase adhesion is physical compatibility. This is once again, a thermodynamic issue and may be quantified in terms of mutual solubility. Most of the strategies for predicting diffusion interphase adhesion are based on thermodynamic compatibility criteria. Thus it is appropriate to review briefly the relevant issues of solution thermodynamics and to seek quantitative measures of compatibility between the phases to be bonded. 

The need to predict mutual diffusion coefficients from self-diffusion coefficients often arises, and many efforts have been made to understand and predict mutual diffusion data, through approaches such as, for example, the following extension of the Darken equation [5j ... 

In accordance with theoretical predictions of the dynamic properties of networks, the critical concentration of dextran appears to be independent of the molecular weight of the flexible polymeric diffusant although some differences are noted when the behaviour of the flexible polymers used is compared e.g. the critical dextran concentrations are lower for PEG than for PVP and PVA. For ternary polymer systems, as studied here, the requirement of a critical concentration that corresponds to the molecular dimensions of the dextran matrix is an experimental feature which appears to be critical for the onset of rapid polymer transport. It is noteworthy that an unambiguous experimental identification of a critical concentration associated with the transport of these types of polymers in solution in relation to the onset of polymer network formation has not been reported so far. Indeed, our studies on the diffusion of dextran in binary (polymer/solvent) systems demonstrated that both its mutual and intradiffusion coefficients vary continuously with increasing concentration 2. ... 

In nonideal mixtures, the thermodynamic nonideality of the mixture has to be considered. We still need to predict the concentration dependence of the mutual diffusion coefficient Dt] of a binary pair of nonelectrolytes. The concentration dependency of l)u in liquid mixtures may be calculated by using the Vignes equation or the Leffler and Cullinan equation. Besides these, we may also use a correlation suggested by Dullien and Asfour (1985), given by... 

The extension of ideal phase analysis of the Maxwell-Stefan equations to nonideal liquid mixtures requires the sufficiently accurate estimation of composition-dependent mutual diffusion coefficients and the matrix of thermodynamic factors. However, experimental data on mutual diffusion coefficients are rare, and prediction methods are satisfactory only for certain types of liquid mixtures. The thermodynamic factor may be calculated from activity coefficient models such as NRTL or UNIQUAC, which have adjustable parameters estimated from experimental phase equilibrium data. The group contribution method of UNIFAC may also be helpful, as it has a readily available parameter table consisting of mam7 species. If, however, reliable data are not available, then the averaged values of the generalized Maxwell-Stefan diffusion coefficients and the matrix of thermodynamic factors are calculated at some mean composition between x0i and xzi. Hence, the matrix of zero flux mass transfer coefficients [k ] is estimated by... 

Graf D. L., Anderson D. E., and Woodhouse J. E. (1983) Ionic diffusion in naturally-occurring aqueous solutions transition-state models that use either empirical expressions or statistically-derived relationships to predict mutual diffusion coefficients in the concentrated-solution regions of 8 binary systems. Geochim. Cosmochim. Acta 47, 1985—1998. 

Rg is the polymer radius of gyration, Xs is the value of the x parameter (see Section 2.3.1) at the spinodal point, and D is the mutual diffusion coefficient of the two polymer components. Bates and Wiltzius (1989) have confirmed the predictions of Eqs. (9-4) and (9-5) for early-time SD of binary blends of perdeuterated and protonated 1,4-polybutadiene. Neutron-scattering studies of SD on a similar system by Jiimai et al. (1993a, 1993b) also confirm the Cahn theory at early times, but the spinodal growth rates deviate somewhat from Eq. (9-5). 

Fig. 14 Separation of C2H6/CH4 mixtures by permeation through a silicalite membrane, a Flux b selectivity. Continuous lines show the predictions of the Maxwell-Stefan model (Eq. 44) based on single-component diffusivities (Dqa> F>ob) with Dab from the Vignes correlation (Eq. 46). Dotted lines show predictions from the simplified Habgood model in which mutual diffusion effects are ignored (Eq. 45). From van de Graaf et al. [53] with permission...

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