Concentration-Dependent Diffusivities

Philip, J.R. 1955. Numerical solution of equations of the diffusion type with diffusivity concentration-dependent. Trans. Faraday Soc. 51 885-892. 

As with the diffusion coefficient, sedimentation coefficients are frequently corrected for concentration dependence and reduced to standard conditions ... 

A rapid increase in diffusivity in the saturation region is therefore to be expected, as illustrated in Figure 7 (17). Although the corrected diffusivity (Dq) is, in principle, concentration dependent, the concentration dependence of this quantity is generally much weaker than that of the thermodynamic correction factor d ap d a q). The assumption of a constant corrected diffusivity is therefore an acceptable approximation for many systems. More detailed analysis shows that the corrected diffusivity is closely related to the self-diffusivity or tracer diffusivity, and at low sorbate concentrations these quantities become identical. 

The cost of enriched material from a gaseous diffusion plant depends both on the cost of separative work and of feed material. It can be seen from equation 15 that if the optimum tails concentration from a gaseous diffusion plant is 0.25%, the ratio of the cost of a kg of normal uranium to the cost of a kg of separative work equal to 0.80 is impfled. Because the cost of separative work in new gaseous diffusion plants is expected to be about 100/SWU, equation 16 gives the cost per kg of uranium containing 4% as about 1,240. 

Since the infinite dilution values D°g and Dba. re generally unequal, even a thermodynamically ideal solution hke Ya = Ys = 1 will exhibit concentration dependence of the diffusivity. In addition, nonideal solutions require a thermodynamic correction factor to retain the true driving force for molecular diffusion, or the gradient of the chemical potential rather than the composition gradient. That correction factor is ... 

For noncoustaut diffusivity, a numerical solution of the conseiwa-tion equations is generally required. In molecular sieve zeohtes, when equilibrium is described by the Langmuir isotherm, the concentration dependence of the intracrystalline diffusivity can often be approximated by Eq. (16-72). The relevant rate equation is ... 

This equation has the same form of that obtained for solid diffusion control with D,j replaced by the equivalent concentration-dependent diffusivity = pDpj/[ pn]Ki l - /i,//i)) ]. Numerical results for the case of adsorption on an initially clean particle are given in Fig. 16-18 for different values of A = = 1 - R. The upt e curves become... 

Because of the close similarity in shape of the profiles shown in Fig. 16-27 (as well as likely variations in parameters e.g., concentration-dependent surface diffusion coefficient), a contrdling mechanism cannot be rehably determined from transition shape. If rehable correlations are not available and rate parameters cannot be measured in independent experiments, then particle diameters, velocities, and other factors should be varied ana the obsei ved impacl considered in relation to the definitions of the numbers of transfer units. 

Salt flux across a membrane is due to effects coupled to water transport, usually negligible, and diffusion across the membrane. Eq. (22-60) describes the basic diffusion equation for solute passage. It is independent of pressure, so as AP — AH 0, rejection 0. This important factor is due to the kinetic nature of the separation. Salt passage through the membrane is concentration dependent. Water passage is dependent on P — H. Therefore, when the membrane is operating near the osmotic pressure of the feed, the salt passage is not diluted by much permeate water. 

Effectiveness As a reac tant diffuses into a pore, it undergoes a falling concentration gradient and a falling rate of reaction. The concentration depends on the radial position in the pores of a spherical pellet according to... 

The relationship between adsorption capacity and surface area under conditions of optimum pore sizes is concentration dependent. It is very important that any evaluation of adsorption capacity be performed under actual concentration conditions. The dimensions and shape of particles affect both the pressure drop through the adsorbent bed and the rate of diffusion into the particles. Pressure drop is lowest when the adsorbent particles are spherical and uniform in size. External mass transfer increases inversely with d (where, d is particle diameter), and the internal adsorption rate varies inversely with d Pressure drop varies with the Reynolds number, and is roughly proportional to the gas velocity through the bed, and inversely proportional to the particle diameter. Assuming all other parameters being constant, adsorbent beds comprised of small particles tend to provide higher adsorption efficiencies, but at the sacrifice of higher pressure drop. This means that sharper and smaller mass-transfer zones will be achieved. 

Microprobe studies of pack-chromised iron (Cr powder, alumina, CrCl, mixture) shows that the surface Cr concentration builds up with time to 95% in 20 h at 1 300 K ", and that the diffusion coefficient for Cr in a-phase is very concentration dependent. The growth of carbides during pack-chromising and during gas-vanadising have been studied. 

It is important to realize that the migration in an electric field depends on the magnitude of the concentration of the charged species, whereas the diffusion process depends only on the concentration gradient, but not on the concentration itself. Accordingly, the mobility rather than the concentration of electrons and holes has to be small in practically useful solid electrolytes. This has been confirmed for several compounds which have been investigated in this regard so far [13]. 

The concentration dependence of the diffuse-layer minimum poten-tial in dilute solution was determined by Levich etal. using an... 

For example, for alkyl (8-16) glycoside (Plantacare 818 UP) non-ionic surfactant solution of molecular weight 390 g/mol, an increase in surfactant concentration up to 300 ppm (CMC concentration) leads to a significant decrease in surface tension. In the range 300 < C < 1,200 ppm the surface tension was almost independent of concentration. In all cases an increase in liquid temperature leads to a decrease in surface tension. This surface tension relaxation is a diffusion rate-dependent process, which typically depends on the type of surfactant, its diffusion/absorption kinetics, micellar dynamics, and bulk concentration levels. As the CMC is approached the absorption becomes independent of the bulk concentration, and the surfactant... 

The most important mass transfer limitation is diffusion in the micropores of the catalyst. A simplified model of pore diffusion treats the pores as long, narrow cylinders of length The narrowness allows radial gradients to be neglected so that concentrations depend only on the distance I from the mouth of the pore. Equation (10.3) governs diffusion within the pore. The boundary condition at the mouth of the pore is... 

We may contrast this behavior to that found for AOT. As shown in Figure 1, the chromatograms for AOT exhibit sharp fronts and somewhat diffuse tails, intermediate in shape between the symmetrical peaks typical of conventional solutes and the highly asymmetric chromatograms obtained for sodium dodecyl sulfate micelles in water (15). In addition, the concentration dependence of Mp" for AOT is gradual, not abrupt as for lecithin. These differences may be attributed to the lability of the AOT micelles which makes the observed retention time quite sensitive to the initial concentration (12) and leads to broadened chromatograms. 

FIG. 20-77 Permeant-concentration profile in a pervaporation membrane. 1— Upstream side (swollen). 2—Convex curvature due to concentration-dependent permeant diffusivity. 3—Downstream concentration gradient. 4—Exit surface of membrane, depleted of permeant, thus unswollen. Courtesy Elsevier.)... 

B. U. Felderhof and J. M. Deutch, Concentration dependence of the rate of diffusion-controlled reactions, J. Chem. Phys. 64, 4551 (1976). 

The above model was solved numerically by writing finite difference approximations for each term. The equations were decoupled by writing the reaction terms on the previous time steps where the concentrations are known. Similarly the equations were linearized by writing the diffusivities on the previous time step also. The model was solved numerically using a linear matrix inversion routine, updating the solution matrix between iterations to include the proper concentration dependent diffusivities and reactions. 

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