Fast diffusion pathways

The picture is less clear for molecular crystals when the molecules deviate strongly from a globular form. NMR data and tracer diffusion data are then often in disagreement. Diffusion profiles (In c, vs. distance) are found to be curved, which is usually attributed to additional heterogeneous and fast diffusion pathways. For plastic crystals, this could indicate that many of them possess a highly defective structure. Even for the aromatic ring molecule benzene, which forms a non-plastic crystal, one finds a D (NMR)/D (tracer) ratio on the order of 103. This cannot be understood unless one invokes other than bulk lattice mechanisms of diffusion. 

Farley, 2000 Reiners and Farley, 1999, 2001), but this relationship breaks down in samples subjected to intensive ductile or brittle deformation (e.g., Amaud and Eide, 2000 Kramar et al, 2001 Mulch et al, 2002). In general, it seems prudent to assume that a is related to the physical grain size when applying Equations (17) and (19) unless samples show textural evidence for the extensive development of subgrain boundaries that may act as fast diffusion pathways, or— in the case of K-feldspar— show direct evidence of the existence of multiple diffusion domains during incremental heating experiments. 

Lee (1995) has proposed a model for fast-track diffusion to explain the effects of combined lattice diffusion and diffusion along fast diffusion pathways through the lattice such as defects. Lee proposed that the combined diffusion could be modeled as two parallel diffusion mechanisms with argon atoms partitioning between the two. The mathematical model produces realistic release patterns, but does not currently take account of the distances between fast track pathways and the time taken for atoms to reach one (cf. Arnaud and Kelley 1995). Future development of the fast track model may provide very fruitful avenues for research. 

Grain boundaries can serve as fast diffusion pathways for vacancies and interstitial atoms when deformation takes place at elevated temperature. The same point can be made with regards to the interface between the matrix and particle phases. However, the particle interfaces that are widely distributed lack interconnectivity with each other, causing them to be less effective as short-circuit diffusion paths than are the more... 

While the surfaces of the planar o-plane GaN films described above were smooth, the TEM images shown in Figure 2.7 and X-ray diffraction data shown in Figure 2.6 indicated that their microstructural quality needed improvement. Threading dislocations in c-plane GaN have been found to act as nonradiative recombination centers, carrier scattering centers, and possibly fast diffusion pathways, limiting device efficiency, speed, and reliabihty. Less is known... 

Nitric oxide and Oy metabolism in the mitochondrial matrix are linked by the very fast, diffusion limited, reaction between NO and Oy to produce peroxynitrite (ONOO ) (reaction 6 [34, 35]). This oxidative utilization of NO is the main (60-70%) pathway of NO metabolism but only a minor part (15%) of mitochondrial Oy utilization, whereas the reductive utilization of NO by ubiquinol and cytochrome oxidase provides a minor (20%) pathway of NO catabolism [12]. 

Thus, when the discharge rate is slow [t > L, /D), the length of the lithium diffusion pathway is important (the whole particle is active), but when the discharge rate is fast [t L /D), the distance traveled by the Li+ ions is small (only a fraction of the particle is working), as illustrated by Fig. 6.9. 

Since diffusion is fastest in the direction parallel to axons in a fiber bundle, diffusion measurements can be used to estimate fiber orientation in each voxel in an MRI data set. If these orientations are interpreted as the local tangent to fiber pathways, then the pathways can be reconstracted by following the fast diffusion direction from point to point along a fiber bundle [5-6]. Fiber tracking based on diffusion data, known as MR tractography, is used to visualize and segment specific anatomical fiber bundles in the brain (Figure 1). This kind of analysis makes it possible to characterize individual fiber bimdles and identify those that are affected by disease. 

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