Diffusive boundary definition

The problems already mentioned at the solvent/vacuum boundary, which always exists regardless of the size of the box of water molecules, led to the definition of so-called periodic boundaries. They can be compared with the unit cell definition of a crystalline system. The unit cell also forms an "endless system without boundaries" when repeated in the three directions of space. Unfortunately, when simulating hquids the situation is not as simple as for a regular crystal, because molecules can diffuse and are in principle able to leave the unit cell. 

A system is the region in space that is the subject of the thermodynamic study. It can be as large or small, or as simple or complex, as we want it to be, but it must be carefully and consistently defined. Sometimes the system has definite and precise physical boundaries, such as a gas enclosed in a cylinder so that it can be compressed or expanded by a piston. However, it may be also something as diffuse as the gaseous atmosphere surrounding the earth. 

The case of the prescribed material flux at the phase boundary, described in Section 2.5.1, corresponds to the constant current density at the electrode. The concentration of the oxidized form is given directly by Eq. (2.5.11), where K = —j/nF. The concentration of the reduced form at the electrode surface can be calculated from Eq. (5.4.6). The expressions for the concentration are then substituted into Eq. (5.2.24) or (5.4.5), yielding the equation for the dependence of the electrode potential on time (a chronopotentiometric curve). For a reversible electrode process, it follows from the definition of the transition time r (Eq. 2.5.13) for identical diffusion coefficients of the oxidized and reduced forms that... 

The limitation of using such a model is the assumption that the diffusional boundary layer, as defined by the effective diffusivity, is the same for both the solute and the micelle [45], This is a good approximation when the diffusivities of all species are similar. However, if the micelle is much larger than the free solute, then the difference between the diffusional boundary layer of the two species, as defined by Eq. (24), is significant since 8 is directly proportional to the diffusion coefficient. If known, the thickness of the diffusional boundary layer for each species can be included directly in the definition of the effective diffusivity. This approach is similar to the reaction plane model which has been used to describe acid-base reactions. 

The region near the electrode where the concentration of a species differs from that of its bulk value is referred to as the diffusion layer. The boundary between that region and the bulk of the bath is, naturally, not sharp. By definition, however, the region in which the concentration of a particular species differs from its bulk concentration by 1% is the diffusion layer. Figure 18.5 depicts the metal ion concentration near a cathode during electrodeposition. 

Since the electro-osinotic flow is induced by the interaction of the externally applied electric field with the space charge of the diffuse electric double layers at the channel walls, we shall concentrate in our further analysis on one of these 0 1 2) thick boundary layers, say, for definiteness, at... 

Table I presents six basic equations in a general way. Those on the left apply to transfer within a phase A, and those on the right to transfer across a phase boundary AB. The top row expresses the mutual definition of force F, proportionality constant K, and potential . The second row expresses the phenomenological proportionality between flux J and force F. The bottom row states the conservation constraints. The left equation says merely that in a given volume the difference between the accumulation rate and the emanation rate must be attributed to a source S. As stated, these equations apply to any conserved quantity which is diffusing, either within a phase under the influence of a potential gradient or across a phase under the influence of a potential difference.

Gas-solid chromatography is best described by this theory. Here one finds diffuse front and rear boundaries with definite tailing of the rear boundary. Mathematical descriptions of systems of this type can become very complex however, with proper assumptions mathematical treatments do fairly represent the experimental data. The bands (zones) are similar to those shown in Figures 1.16 and 1.17. 

Enzymatic reactions coupled to optical detection of the product of the enzymatic reaction have been developed and successfully used as reversible optical biosensors. By definition, these are again steady-state sensors in which the information about the concentration of the analyte is derived from the measurement of the steady-state value of a product or a substrate involved in highly selective enzymatic reaction. Unlike the amperometric counterpart, the sensor itself does not consume or produce any of the species involved in the enzymatic reaction it is a zero-flux boundary sensor. In other words, it operates as, and suffers from, the same problems as the potentiometric enzyme sensor (Section 6.2.1) or the enzyme thermistor (Section 3.1). It is governed by the same diffusion-reaction mechanism (Chapter 2) and suffers from similar limitations. 

The boundary conditions normally associated with Equation (9.14) are known as the Danckwerts or closed boundary conditions. They are obtained from mass balances across the inlet and outlet of the reactor. We suppose that the piping to and from the reactor is small and has a high Re. Thus, if we were to apply the axial dispersion model to the inlet and outlet streams, we would find Din = Dout = 0, which is the definition of a closed system. See Figure 9.8. The flux in the inlet pipe is due solely to convection and has magnitude Qi ain. The flux just inside the reactor at location z = 0+ has two components. One component, Qina(0+), is due to convection. The other component, —DAc[da/dz 0+, is due to diffusion (albeit eddy diffusion) from the relatively high concentrations at the inlet toward the lower concentrations within the reactor. The inflow to the plane at z = 0 must be matched by material leaving the plane at z = 0+ since no reaction occurs in a region that has no volume. Thus,... 

The process of mathematical fitting is error-prone, and especially two different issues have to be considered, the first one dealing with the boundary conditions of the fitting procedure itself A pure diffusion process is considered here as the only transport mechanism for fluorine in the sample. A constant value for the diffusion constant D, invariant soil temperatures and a constant supply of fluorine (e.g. a constant soil humidity) are assumed, the latter effect theoretically resulting in a constant surface fluorine concentration for samples collected at the same burial site. In mathematical terms, Dt is influenced by the spatial resolution of the scanning beam, the definition of the exact position of the bone surface, which usually coincides with the maximum fluorine concentration, and by the original fluorine concentration in the bulk of the object, which in most cases is still detectable. A detailed description on... 

Here the value of the boundary concentration is specified. A familiar example in the present context is the outer boundary, beyond the diffusion space, where the concentration usually remains at the initial bulk value during the whole period over which the simulation is carried out. This also applies to the case of the Reinert-Berg mechanism (page 20), in which the bulk concentration itself changes with time, but we know the bulk value at any time, because chemical reaction kinetics, uncomplicated by transport effects, is well understood. In such cases, we can set a given bulk concentration, albeit time-varying. Another familiar example arises from the Cottrell experiment, in which the concentration at the electrode, Co, is set to zero. This is a particular case of that concentration being set to a definite value, not necessarily zero. 

The rationale of using hybrid simulation here is that a classic diffusion-adsorption type of model, Eq. (2), can efficiently handle large distances between steps by a finite difference coarse discretization in space. As often happens in hybrid simulations, an explicit, forward discretization in time was employed. On the other hand, KMC can properly handle thermal fluctuations at the steps, i.e., provide suitable boundary conditions to the continuum model. Initial simulations were done in (1 + 1) dimensions [a pseudo-2D KMC and a ID version of Eq. (2)] and subsequently extended to (2 + 1) dimensions [a pseudo-3D KMC and a 2D version of Eq. (2)] (Schulze, 2004 Schulze et al., 2003). Again, the term pseudo is used as above to imply the SOS approximation. Speedup up to a factor of 5 was reported in comparison with KMC (Schulze, 2004), which while important, is not as dramatic, at least for the conditions studied. As pointed out by Schulze, one would expect improved speedup, as the separation between steps increases while the KMC region remains relatively fixed in size. At the same time, implementation is definitely complex because it involves swapping a microscopic KMC cell with continuum model cells as the steps move on the surface of a growing film. 

Equation 8.2 shows how the net flux density of substance depends on its diffusion coefficient, Dj, and on the difference in its concentration, Ac] 1, across a distance Sbl of the air. The net flux density Jj is toward regions of lower Cj, which requires the negative sign associated with the concentration gradient and otherwise is incorporated into the definition of Acyin Equation 8.2. We will specifically consider the diffusion of water vapor and C02 toward lower concentrations in this chapter. Also, we will assume that the same boundary layer thickness (Sbl) derived for heat transfer (Eqs. 7.10-7.16) applies for mass transfer, an example of the similarity principle. Outside Sbl is a region of air turbulence, where we will assume that the concentrations of gases are the same as in the bulk atmosphere (an assumption that we will remove in Chapter 9, Section 9.IB). Equation 8.2 indicates that Jj equals Acbl multiplied by a conductance, gbl, or divided by a resistance, rbl. 

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