184 resultados para Diffusion flame
Resumo:
Using density functional theory, we investigated the position preference and diffusion mechanisms of interstitial oxygen ions in lanthanum silicate La9.33Si6O26, which is an apatite-structured oxide and a promising candidate electrolyte material for solid oxide fuel cells. The reported lanthanum vacancies were explicitly taken into account by theoretically determining their arrangement with a supercell model. The most stable structures and the formation energies of oxygen interstitials were determined for each charged state. It was found that the double-negatively charged state is stable over a wide range of the Fermi level, and that the excess oxygen ions form split interstitials with the original oxygen ions, while the neutral and the single-negatively charged states preferably form molecular oxygen. These species were found near the lanthanum vacancy site. The theoretically determined migration pathway along the c-axis essentially follows an interstitialcy mechanism. The obtained migration barrier is sensitive to the charge state, and is also affected by the lanthanum vacancy. The barrier height of the double-negatively charged state was calculated to be 0.58 eV for the model structure, which is consistent with the measured activation energy.
Resumo:
A stable Y-doped BaZrO3 electrolyte film, which showed a good performance in proton-conducting SOFCs, was successfully fabricated using a novel ionic diffusion strategy.
Genetic analysis of structural brain connectivity using DICCCOL models of diffusion MRI in 522 twins
Resumo:
Genetic and environmental factors affect white matter connectivity in the normal brain, and they also influence diseases in which brain connectivity is altered. Little is known about genetic influences on brain connectivity, despite wide variations in the brain's neural pathways. Here we applied the 'DICCCOL' framework to analyze structural connectivity, in 261 twin pairs (522 participants, mean age: 21.8 y ± 2.7SD). We encoded connectivity patterns by projecting the white matter (WM) bundles of all 'DICCCOLs' as a tracemap (TM). Next we fitted an A/C/E structural equation model to estimate additive genetic (A), common environmental (C), and unique environmental/error (E) components of the observed variations in brain connectivity. We found 44 'heritable DICCCOLs' whose connectivity was genetically influenced (α2>1%); half of them showed significant heritability (α2>20%). Our analysis of genetic influences on WM structural connectivity suggests high heritability for some WM projection patterns, yielding new targets for genome-wide association studies.
Resumo:
Diffusion in a composite slab consisting of a large number of layers provides an ideal prototype problem for developing and analysing two-scale modelling approaches for heterogeneous media. Numerous analytical techniques have been proposed for solving the transient diffusion equation in a one-dimensional composite slab consisting of an arbitrary number of layers. Most of these approaches, however, require the solution of a complex transcendental equation arising from a matrix determinant for the eigenvalues that is difficult to solve numerically for a large number of layers. To overcome this issue, in this paper, we present a semi-analytical method based on the Laplace transform and an orthogonal eigenfunction expansion. The proposed approach uses eigenvalues local to each layer that can be obtained either explicitly, or by solving simple transcendental equations. The semi-analytical solution is applicable to both perfect and imperfect contact at the interfaces between adjacent layers and either Dirichlet, Neumann or Robin boundary conditions at the ends of the slab. The solution approach is verified for several test cases and is shown to work well for a large number of layers. The work is concluded with an application to macroscopic modelling where the solution of a fine-scale multilayered medium consisting of two hundred layers is compared against an “up-scaled” variant of the same problem involving only ten layers.