Binary systems diffusion

Multicomponent Diffusion. In multicomponent systems, the binary diffusion coefficient has to be replaced by an effective or mean diffusivity Although its rigorous computation from the binary coefficients is difficult, it may be estimated by one of several methods (27—29). Any degree of counterdiffusion, including the two special cases "equimolar counterdiffusion" and "no counterdiffusion" treated above, may arise in multicomponent gas absorption. The influence of bulk flow of material through the films is corrected for by the film factor concept (28). It is based on a slightly different form of equation 13 ... 

The solute 1 is dissolved in a solvent pair of 2 and 3. D are infinite dilution binary diffusivities estimated by the proper method discussed previously. The mixture viscosity can be predic ted by methods of the previous section. The average absolute error when tested on 40 systems is 25 percent. The method gives higher errors if the solute is gaseous. 

If a liquid system containing at least two components is not in thermodynamic equilibrium due to concentration inhomogenities, transport of matter occurs. This process is called mutual diffusion. Other synonyms are chemical diffusion, interdiffusion, transport diffusion, and, in the case of systems with two components, binary diffusion. 

According to Maxwell s law, the partial pressure gradient in a gas which is diffusing in a two-component mixture is proportional to the product of the molar concentrations of the two components multiplied by its mass transfer velocity relative to that of the second component. Show how this relationship can be adapted to apply to the absorption of a soluble gas from a multicomponent mixture in which the other gases are insoluble and obtain an effective diffusivity for the multicomponent system in terms of the binary diffusion coefficients. 

A schematic illustration of the method, and of the correlation between binary phase diagram and the one-phase layers formed in a diffusion couple, is shown in Fig. 2.42 adapted from Rhines (1956). The one-phase layers are separated by parallel straight interfaces, with fixed composition gaps, in a sequence dictated by the phase diagram. The absence, in a binary diffusion couple, of two-phase layers follows directly from the phase rule. In a ternary system, on the other hand (preparing for instance a diffusion couple between a block of a binary alloy and a piece of a third... 

Other general cases in binary systems are referred to as interdiffusion or binary diffusion. For example, Fe-Mg diffusion between two olivine crystals of different Xpo (mole fraction of forsterite Mg2Si04) is called Fe-Mg interdiffusion. Inter-diffusivity often varies across the profile because there are major concentration changes, and diffusivity usually depends on composition. 

Uphill diffusion in a binary system is rare and occurs only when the phase undergoes spinodal decomposition. In multicomponent systems, uphill diffusion occurs often, even when the phase is stable. The cause for uphill diffusion in multicomponent systems is different from that in binary systems and will be discussed later. 

Despite the various drawbacks, the effective binary approach is still widely used and will be widely applied to natural systems in the near future because of the difficulties of better approaches. For major components in a silicate melt, it is possible that multicomponent diffusivity matrices will be obtained as a function of temperature and melt composition in the not too distant future. For trace components, the effective binary approach (or the modified effective binary approach in the next section) will likely continue for a long time. The effective binary diffusion approach may be used under the following conditions (but is not limited to these conditions) with consistent and reliable results (Cooper, 1968) ... 

As long as care is taken so that effective binary diffusivity obtained from experiments under the same set of conditions is applied to a given problem, the approach works well. Although the limitations mean additional work, because of its simplicity and because of the unavailability of the diffusion matrices, the effective binary diffusion approach is the most often used in geological systems. Nonetheless, it is hoped that effort will be made in the future so that multi-component diffusion can be handled more accurately. 

Therefore, in the transformed components, the diffusion is decoupled, meaning that the diffusion of one component is independent of the diffusion of other components. The equation for each w, can be obtained given initial and boundary conditions using the solutions for binary diffusion. The final solution for C is C = Tw. When the diffusivity matrix is not constant, the diffusion equation for a multicomponent system can only be solved numerically. 

Similar to binary diffusivities, each element in the diffusivity matrix is expected to depend on composition, sometimes strongly, especially for highly nonideal systems. If the nonideality is strong enough to cause a miscibility gap, the eigenvalues would vary from positive to zero and to negative. If there is no miscibility gap, the eigenvalues are positive but can still vary with composition. 

If the difference in concentration is in one component only, e.g., one side contains a dry rhyolite, and the other side is prepared by adding H2O to the rhyolite, then the main concentration gradient is in H2O, and all other components have smaller concentration gradients. The diffusion of H2O may be treated fairly accurately by effective binary diffusion. In other words, the diffusion of the component with the largest concentration gradient may be treated as effective binary, especially if the component also has high diffusivity. The diffusion of other components in the system may or may not be treated as effective binary diffusion. 

If the difference in concentration is in only two exchangeable components, such as FeO and MgO, the interdiffusion in a multicomponent system may be treated as effective binary. The diffusion of other components in the system may or may not be treated as effective binary diffusion. 

In irreversible thermod3mamics, the second law of thermodynamics dictates that entropy of an isolated system can only increase. From the second law of thermodynamics, entropy production in a system must be positive. When this is applied to diffusion, it means that binary diffusivities as well as eigenvalues of diffusion matrix are real and positive if the phase is stable. This section shows the derivation (De Groot and Mazur, 1962). 

Cooper A.R. and Varshneya A.K. (1968) Diffusion in the system K20-Sr0-Si02,1 effective binary diffusion coefficients. /. Am. Ceram. Soc. 51, 103-106. 

The rapid transport of the linear, flexible polymer was found to be markedly dependent on the concentration of the second polymer. While no systematic studies were performed on these ternary systems, it was argued that the rapid rates of transport could be understood in terms of the dominance of strong thermodynamic interactions between polymer components overcoming the effect of frictional interactions this would give rise to increasing apparent diffusion coefficients with concentration 28-45i. This is analogous to the resulting interplay of these parameters associated with binary diffusion of polymers. 

For a two-component mixture the multicomponent diffusion coefficients D, become the ordinary binary diffusion coefficients Sh,. For these quantities 2D,-, = 2D,- and 2D = 0. For a three-component system the multicomponent diffusion coefficients are not equal to the ordinary binary diffusion coefficients. For example, it has been shown by Curtiss and Hirschfelder (C12) in their development of the kinetic theory of multicomponent gas mixtures that... 

Note that in Eq. (60) it is the multicomponent Dtj which appear, whereas in Eq. (61) the binary diffusion coefficients Sh, appear.13 For a system at constant temperature and pressure Eq. (61) may also be written... 

To expedite the evaluation of transport properties, one could fit the temperature dependent parts of the pure species viscosities, thermal conductivities, and pairs of binary diffusion coefficients. Then, rather than using the complex expressions for the properties, only comparatively simpler polynomials would be evaluated. The fitting procedure must be carried out for the particular system of gases that is present in a given problem. Therefore the fitting cannot be done once and for all but must be done once at the beginning of each new problem. 

Such fits may also be done for each pair of binary diffusion coefficients in the system,... 

Four different types of diffusivities are summarized in Table 3.1. These include the self-diffusivity in a pure material, D the self-diffusivity of solute i in a binary system, Df, the intrinsic diffusivity of component i in a chemically inhomogeneous system, Dand the interdiffusivity, D, in a chemically inhomogeneous system. These diffusivities are applicable only in certain reference frames which are also listed in Table 3.1. In the remainder of this book, the type of diffusivity under discussion will be identified by these symbols when this information is relevant. When a diffusivity is identified in this manner, it may be assumed that the diffusion under consideration is being described in the proper corresponding frame. 

These equations contain a number of assumptions. First of all, they are a result of a dilute gas approximation in which binary diffusion coefficients, which may be assumed independent of composition, are used. Secondly, thermal diffusion has been neglected although this assumption should be verified for the system under investigation. It appears that the flux due to thermal diffusion could be a substantial fraction of the ordinary diffusion flux for some systems (F6). 

Note that the above study is performed for a simple system. There exists a large body of literature on the study of diffusion in complex quasi-two-dimensional systems—for example, a collodial suspension. In these systems the diffusion can have a finite value even at long time. Schofield, Marcus, and Rice [17] have recently carried out a mode coupling theory analysis of a quasi-two-dimensional colloids. In this work, equations for the dynamics of the memory functions were derived and solved self-consistently. An important aspect of this work is a detailed calculation of wavenumber- and frequency-dependent viscosity. It was found that the functional form of the dynamics of the suspension is determined principally by the binary collisions, although the mode coupling part has significant effect on the longtime diffusion. 

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).]...

The dec8y rate of the order-parameter fluctuations is proportional to the thermal diffusivity in case of pure gases near the vapor-liquid critical point and is proportional to the binary diffusion coefficient in case of liquid mixtures near the critical mixing point (6). Recently, we reported (7) single-exponential decay rate of the order-parameter fluctuations in dilute sugercritical solutions of liquid hydrocarbons in CO for T - T 10 C. This implied that the time scales associated with thermal diffusion and mass diffusion are similar in these systems. 

In this study, we employed PCS to measure the decay rate of the order-parameter fluctuations in dilute supercritical solutions of heptane, benzene, and decane in CC - The refractive index increment with concentration is much larger than the refractive index increment with temperature in these systems. Therefore the order-parameter fluctuations detected by light scattering are mainly concentration fluctuations and their decay rate T is proportional to the binary diffusion coefficient, D = V/q. The... 

CO -benzene, and CO -n-decane. The critical densities and the corresponding compositions are plotted in Figure 1. The three hydrocarbons in order of higher to lower solubility in C0 were heptane, benzene, and decane. The measured binary diffusion coefficients or the decay rates of the order-parameter fluctuations at various temperatures and pressures are listed in Tables I, II, and III for CO -heptane, CO -benzene, and CO -decane systems respectively. In Figure 2, the critical lines of the three binary systems in the dilute hydrocarbon range are shown in the pressure-temperature space. dP/dT along the critical lines of CO.-heptane and CO -benzene systems are similar and lower than dP/dT along the critical line of CO -decane system, which indicates that C02 and decane form more asymmetric mixtures relative to CO with heptane or benzene. 

For diffusion coefficients in systems under high pressure, the method of Dawson-Khoury-Kobayashi (see Ref. [52]) suggests a relevant pressure correction factor. To estimate the molar volumes, some reliable equations of state should be applied, whereas the necessary binary diffusivities at 1 atm can be determined with one of the methods described above. 

The Characteristic Time Model was always found to give the worst fit and the Single Sphere Model II (which is not shown and which allows for film resistance) was not found to be appreciably better than the computationally simpler Model I for these systems. The values of De obtained were about two orders of magnitude lower than the estimated binary diffusivities. 

In general, diffusivity depends on pressure, temperature, and composition. With respect to the mobility of molecules, the diffusion coefficients are generally higher for gases and lower for solids. The diffusivities of gases at low densities are almost independent of concentration, increase with temperature, and vary inversely with pressure. Liquid and solid diffusivities are strongly concentration dependent and generally increase with temperature. Tables 2.7 and 2.8 show some of the experimental binary diffusivities for gas and liquid systems. 

Equation (2.71) can be compared with Eq. (2.46) for the thermal conductivity of gases, and with Eq. (2.19) for the viscosity. For binary gas mixtures at low pressure, is inversely proportional to the pressure, increases with increasing temperature, and is almost independent of the composition for a given gas pair. For an ideal gas law P = cRT, and the Chapman-Enskog kinetic theory yields the binary diffusivity for systems at low density... 

We may describe multicomponent diffusion by (1) the Maxwell-Stefan equation where flows and forces are mixed, (2) the Chapman-Cowling and Hirschfelder-Curtiss-Bird approaches where the diffusion of all the components are treated in a similar way, and (3) a reference to a particular component, for example, the solvent or mass average (baiycentric) definition. Frames of reference in multicomponent system must be clearly defined. Binary diffusion coefficients are often composition dependent in liquids, while they are assumed independent of composition for gases. 

Thus, the Maxwell-Stefan diffusion coefficients satisfy simple symmetry relations. Onsager s reciprocal relations reduce the number of coefficients to be determined in a phenomenological approach. Satisfying all the inequalities in Eq. (6.12) leads to the dissipation function to be positive definite. For binary mixtures, the Maxwell-Stefan dififusivity has to be positive, but for multicomponent system, negative diffusivities are possible (for example, in electrolyte solutions). From Eq. (6.12), the Maxwell-Stefan diffusivities in an -component system satisfy the following inequality... 

The behavior of the Fick diffusion coefficient in nonideal systems may be complicated, while the Maxwell-Stefan diffusion coefficients behave quite well, and are always positive for binary systems. In nonideal binary systems, the Fick diffusivity varies with concentration. As seen in Figure 6.1, water-acetone and water-ethanol systems exhibit a minimum diffusivity at intermediate concentrations. Table 6.1 displays the dependency of binary diffusivity coefficients on concentration for selected alkenes in chloroform at 30°C and 1 atm. As the nonideality increases, mixture may split into two liquid phases at certain composition and temperature. 

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