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Diffusion hopping rates

In this case, if the tunnelling rate exceeds the two diffusive hopping rates, the activation barrier does not impede the rate of reaction On the other hand, if the tunnelling rate is much slower than the diffusive hopping rates, the more complex expression for n reduces to... [Pg.44]

Fig. 6. The hop rate of muonium in KC1 as a function of temperature. The crossover from stochastic to quantum diffusion occurs at about 70 K, as evidence by a dramatic increase in the hop rate at lower temperatures. From Kiefl et al. (1989a). Fig. 6. The hop rate of muonium in KC1 as a function of temperature. The crossover from stochastic to quantum diffusion occurs at about 70 K, as evidence by a dramatic increase in the hop rate at lower temperatures. From Kiefl et al. (1989a).
Fig. 5. Surface diffusion of the rigid rodlike molecule 4-trans-2-(pyrid-4-yl-vinyl) benzoic acid on Pd(110). In (a) and (b) two consecutive STM images taken at 361 K are shown which demonstrate the 1-dim motion. Arrows indicate molecules whose position changed circles mark fractionally imaged molecules moving under the STM tip in the course of the measurement, (c) Model for the flat adsorption geometry explaining the two observed molecular orientations in the STM data. The length of the molecule is 12.5 A. (d) Arrhenius plot of single molecule hopping rates [75]. Fig. 5. Surface diffusion of the rigid rodlike molecule 4-trans-2-(pyrid-4-yl-vinyl) benzoic acid on Pd(110). In (a) and (b) two consecutive STM images taken at 361 K are shown which demonstrate the 1-dim motion. Arrows indicate molecules whose position changed circles mark fractionally imaged molecules moving under the STM tip in the course of the measurement, (c) Model for the flat adsorption geometry explaining the two observed molecular orientations in the STM data. The length of the molecule is 12.5 A. (d) Arrhenius plot of single molecule hopping rates [75].
The importance of the measurements that we have presented so far for the diffusion of embedded tracer atoms becomes evident when we now use these measurements and the model discussed in Section 3 to evaluate the invisible mobility of the Cu atoms in a Cu(00 1) terrace. The results presented in Section 2 imply that not just the tracer atom, but all atoms in the surface are continuously moving. From the tracer diffusion measurements of In/Cu(0 0 1) we have established that the sum of the vacancy formation energy and the vacancy diffusion barrier in the clean Cu(0 01) surface is equal to 717 meV. For the case of self-diffusion in the Cu(0 01) surface we can use this number with the simplest model that we discussed in Section 3.2, i.e. all atoms are equal and no interaction between the vacancy and the tracer atom. In doing so we find a room temperature hop rate for the self-diffusion of Cu atoms in a Cu(00 1) terrace of v = 0.48 s-1. In other words, every terrace Cu atom is displaced by a vacancy, on average, about once per two seconds at room temperature and about 200times/sec at 100 °C. We illustrate this motion by plotting the calculated average displacement rate of Cu terrace atoms vs. 1 /kT in Fig. 14. [Pg.368]

To reconcile this apparent contradiction the membrane skeleton fence and anchored transmembrane picket model was proposed (54). According to this model, transmembrane proteins anchored to and lined up along the membrane skeleton (fence) effectively act as a row of posts for the fence against the free diffusion of lipids (Fig. 11). This model is consistent with the observation that the hop rate of transmembrane proteins increases after the partial removal of the cytoplasmic domain of transmembrane proteins, but it is not affected by the removal of the major fraction of the extracellular domains of transmembrane proteins or extracellular matrix. Within the compartment borders, membrane molecules undergo simple Brownian diffusion. In a sense, the Singer-Nicolson model is adequate for dimensions of about 10 x lOnm, the special scale of the original cartoon depicted by the authors in 1972. However, beyond such distances simple extensions of the fluid mosaic model fail and a substantial paradigm shift is required from a two-dimensional continuum fluid to the compartmentalized fluid. [Pg.1014]

Trammell and Meyer used cyclic voltammetry and ehronoamperometry with absorption measurements to estimate the eleetron hopping rate aeross sensitized nanocrystalline semiconductor surfaces [134]. At high surface eoverages of Ru(bpy)2(dcb) + or Os(bpy)2(dcb)-+, the apparent eharge-transfer diffusion coefficients was measured to be 1.4 x 10 em s in acetonitrile electrolyte. Oxida-... [Pg.2754]

Figure 4. Production rate of AB as a function of time, together with four snapshots of the simulation grid during an oscillation cycle. Grid size 2048 x 2048. Hopping rate for diffusion 30 s. The arrows in the plot indicate at which moments the snapshots were taken. Colors are as in Figure 3. Figure 4. Production rate of AB as a function of time, together with four snapshots of the simulation grid during an oscillation cycle. Grid size 2048 x 2048. Hopping rate for diffusion 30 s. The arrows in the plot indicate at which moments the snapshots were taken. Colors are as in Figure 3.
Figure 17 CO stripping voltammetry from Dynamic Monte Carlo simulations, for pure Pt ( Ru = 0), various Pt-Ru alloy surfaces, and pure Ru. Details of the kinetic rate constants can be found in the original publication. CO surface diffusion is very fast, hopping rate D from site to site of 1000s . (Adapted from Ref. [49].)... Figure 17 CO stripping voltammetry from Dynamic Monte Carlo simulations, for pure Pt ( Ru = 0), various Pt-Ru alloy surfaces, and pure Ru. Details of the kinetic rate constants can be found in the original publication. CO surface diffusion is very fast, hopping rate D from site to site of 1000s . (Adapted from Ref. [49].)...
Figure 5 Multiscale approach to understand rate of CO2 diffusion into and CH4 diffusion out of a structure I hydrate, (left) Molecular simulation for individual hopping rates, (middle) Mesoscale kinetic Monte Carlo simulation of hopping on the hydrate lattice to determine dependence of diffusion constants on vacancy, CO2 and CH4 concentrations, (right) Macroscopic coupled non-linear diffusion equations to describe rate of CO2 infusion and methane displacement. Graph from Stockie. ... Figure 5 Multiscale approach to understand rate of CO2 diffusion into and CH4 diffusion out of a structure I hydrate, (left) Molecular simulation for individual hopping rates, (middle) Mesoscale kinetic Monte Carlo simulation of hopping on the hydrate lattice to determine dependence of diffusion constants on vacancy, CO2 and CH4 concentrations, (right) Macroscopic coupled non-linear diffusion equations to describe rate of CO2 infusion and methane displacement. Graph from Stockie. ...
In principle, i can be treated as the sum of diffusion and drift components, but we need to allow for the fact that disorder in transport energy levels leads to dispersion in the microscopic hopping rates and to charge trapping, which between them lead to diffnsion constants and mobilities that are effectively charge-density-dependent. In addition, the Einstein relation between diffusion constant and mobility is nnlikely to hold (Roichman and Tessler, 2002). [Pg.475]


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