Effective binary diffusion

Here L is the thickness of the porous septum and jS the length of each dead-end micropore, the effective binary bulk diffusion coefficient... 

Mass Transport. An expression for the diffusive transport of the light component of a binary gas mixture in the radial direction in the gas centrifuge can be obtained directly from the general diffusion equation and an expression for the radial pressure gradient in the centrifuge. For diffusion in a binary system in the absence of temperature gradients and external forces, the general diffusion equation retains only the pressure diffusion and ordinary diffusion effects and takes the form... 

Binary Electrolyte Mixtures When electrolytes are added to a solvent, they dissociate to a certain degree. It would appear that the solution contains at least three components solvent, anions, and cations, if the solution is to remain neutral in charge at each point (assuming the absence of any applied electric potential field), the anions and cations diffuse effectively as a single component, as for molecular diffusion. The diffusion or the anionic and cationic species in the solvent can thus be treated as a binary mixture. 

Chakraborty S. and Ganguly J. (1992). Cation diffusion in aluminosilicate garnets Experimental determination in spessartine-almandine diffusion couples, evaluation of effective binary diffusion coefficients, and applications. Contrib. Mineral Petrol, 111 74-86. 

Interdiffusion, effective binary diffusion, and multicomponent diffusion may be referred to as chemical diffusion, meaning there are major chemical concentration gradients. Chemical diffusion is defined relative to self diffusion and tracer diffusion, for which there are no major chemical concentration gradients. 

When one refers to the diffusion equation, it is usually the binary diffusion equation. Although theories for multicomponent diffusion have been extensively developed, experimental studies of multicomponent diffusion are limited because of instrumental analytical error and theoretical complexity, and there are yet no reliable diffusivity matrix data for practical applications in geology. Multicomponent diffusion is hence often treated as effective binary diffusion by treating the component under consideration as one component and combining all the other components as the second component. 

Uphill diffusion of some components is reported in silicate melts (e.g., Sato, 1975 Watson, 1982a Zhang et al., 1989 Lesher, 1994 Van Der Laan et al., 1994). Recall that uphill diffusion in binary systems is rare and occurs only when the two-component phase undergoes spinodal decomposition. In multicomponent systems, uphiU diffusion often occurs even when the phase is stable, and may be explained by cross-effects of diffusion by other components. 

With each level of increased sophistication, the complexity of treating a diffusion problem increases tremendously, especially for natural silicate melts that have a large number of components. The simplest method (effective binary approach) is the most often used, but it cannot treat the diffusion of many components (such as those that show uphill diffusion). All the other methods have not been applied much to natural silicate melts. 

Below, the effective binary approach and the concentration-based diffusivity matrix are introduced. The modified effective binary approach (Zhang, 1993) has not been followed up. The approach using the activity-based diffusivity matrix, similar to activity-based diffusivity T> (Equations 3-61 and 3-62), is probably the best approach, but such diffusivities require systematic effort to obtain. 

Pick s law is an empirical diffusion law for binary systems. For multicomponent systems. Pick s law must be generalized. There are several ways to generalize Pick s law to multicomponent systems. One simple treatment is called the effective binary treatment, in which Pick s law is generalized to a multicomponent system in the simplest way ... 

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) ... 

If the compositional difference along the diffusion direction is primarily in one component, and the difference in other components is due to the dilution effect, then diffusion of this component (not necessarily the other components) may be treated as effective binary, and the EBDC can be applied reliably to similar situations. Some examples are a diffusion couple made of dry rhyolite on one half and hydrous rhyolite on the other half, the hydration or dehydration of a silicate melt, and adsorption of a gas component by a glass. 

If initial concentration gradients are in two complementing components, such as FeO and MgO (with the sum of FeO and MgO molar concentrations being a constant), and all other components have uniform concentration, the diffusion between the two components may be treated as interdiffusion, or effective binary diffusion. 

In all of the three cases above, components other than the discussed major components often cannot be treated as effective binary diffusion, especially for a component whose concentration gradient is small or zero compared to other components. Such a component often shows uphill diffusion. 

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. 

Zhang (1993) proposed the modified effective binary approach (also called activity-based effective binary approach). In this approach, the diffusive flux of a component is related to its activity gradient and all other components are treated as one combined component. The diffusive flux for any component i is expressed as (by analogy with Equation 3-61)... 

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. 

The components whose concentration gradient is small compared to other components cannot be treated as effective binary. They often show uphill diffusion. 

For the dissolution of a crystal into a melt, if one wants to predict the interface melt composition (that is, the composition of the melt that is saturated with the crystal), the dissolution rate, and the diffusion profiles of all major components, thermodynamic understanding coupled with the diffusion matrix approach is necessary (Liang, 1999). If the effective binary approach is used, it would be necessary to determine which is the principal equilibrium-determining component (such as MgO during forsterite dissolution in basaltic melt), estimate the concentration of the component at the interface melt, and then calculate the dissolution rate and diffusion profile. To estimate the interface concentration of the principal component from thermod5mamic equilibrium, because the concentration depends somewhat on the concentrations of other components, only... 

In principle, the diffusion matrix approach can be extended to trace elements. My assessment, however, is that in the near future diffusion matrix involving 50 diffusing components will not be possible. Hence, simple treatment will still have to be used to roughly understand the diffusion behavior of trace elements the effective binary diffusion model to handle monotonic profiles, the modified effective binary diffusion model to handle uphill diffusion, or some combination of the diffusion matrix and effective binary diffusion model. 

Even in the absence of uphill diffusion, a trace element concentration profile often does not match that for a constant diffusivity by using the effective binary diffusion treatment. Hence, the effective binary diffusivity depends on the chemical composition, which is expected. 

If diffusivity is extracted from the profile of the isotopic fraction of an element, it may differ significantly from, and often greater than, the effective binary diffusivity obtained from the concentration profile of the trace or minor element. 

To quantify the diffusion profiles is a difficult multicomponent problem. The activity-based effective binary diffusion approach (i.e. modified effective binary approach) has been adopted to roughly treat the problem. In this approach. 

Figure 3-24 Calculated diffusion-couple profiles for trace element diffusion and isotopic diffusion in the presence of major element concentration gradients using the approximate approach of activity-based effective binary treatment. The vertical dot-dashed line indicates the interface. The solid curve is the Nd trace element diffusion profile (concentration indicated on the left-hand y-axis), which is nonmonotonic with a pair of maximum and minimum, indicating uphill diffusion. The dashed curve is the Nd isotopic fraction profile. Note that the midisotopic fraction is not at the interface.

Tracer diffusivities are often determined using the thin-source method. Self-diffusivities are often obtained from the diffusion couple and the sorption methods. Chemical diffusivities (including interdiffusivity, effective binary diffusivity, and multicomponent diffusivity matrix) may be obtained from the diffusion-couple, sorption, desorption, or crystal dissolution method. 

For inter diffusion between same-valence ions (ionic exchange) in an aqueous solution, or a melt, or a solid solution such as olivine (Fe +, Mg +)2Si04, an equation similar to Equation 3-135c has been derived from the Nemst-Planck equations first by Helfferich and Plesset (1958) and then with refinement by Barter et al. (1963) with the assumption that (i) the matrix (or solvent) concentration does not vary and (ii) cross-coefficient Lab (phenomenological coefficient in Equation 3-96a) is negligible, which is similar to the activity-based effective binary diffusion treatment. The equation takes the following form ... 

The diffusion behavior of components that are not the principal equilibriumdetermining component is difficult to model because of multicomponent effect. Many of them may show uphill diffusion (Zhang et al., 1989). To calculate the interface-melt composition using full thermod3mamic and kinetic treatment and to treat diffusion of all components, it is necessary to use a multicomponent diffusion matrix (Liang, 1999). The effective binary treatment is useful in the empirical estimation of the dissolution distance using interface-melt composition and melt diffusivity, but cannot deal with multicomponent effect and components that show uphill diffusion. 

Diffusive dissolution of MgO-rich olivine and diffusion profiles MgO is the principal equilibrium-determining component and its diffusion behavior is treated as effective binary. Consider the dissolution of an olivine crystal (Fo90, containing 49.5 wt% MgO) in an andesitic melt (containing 3.96 wt% MgO) at 1285°C and 550 MPa (exp 212 of Zhang et al. 1989). The density of olivine is 3198 kg/m, and that of the initial melt is 2632 kg/m. Hence, the density ratio is 1.215. To estimate the dissolution parameter a, it is necessary to know the interface melt... 

For the calculation of convective dissolution rate of a falling crystal in a silicate melt, the diffusion is multicomponent but is treated as effective binary diffusion of the major component. The diffusivity of the major component obtained from diffusive dissolution experiments of the same mineral in the same silicate melt is preferred. Diffusivities obtained from diffusion-couple experiments or other types of experiments may not be applicable because of both compositional effect... 

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