Recent two dimensional nuclear magnetic resonance (NMR) techniques access exchange in pore structures through surface relaxation and diffusion based relaxation [1-4]. This research applies these techniques to measure pore changes due to biofilm growth and the impact this growth has on diffusion transport. The porous media used in this study are model beadpacks constructed from borosilicate glass beads with diameters approximately 100 um. This research shows that through changes in the relaxation rates, NMR can be used to verify biofilm growth in porous media.

MR imaging of moisture ingression into porous tissue of decayed teeth in vitro with resolution of 30´120´180 μm3 was obtained using a 4.7 T research MRI scanner and a spinecho pulse sequence. High resolution images allowed the visualisation of the 3D structure of tooth pores and the estimation of their size and extent. Using a Single Point Imaging method, images of the mineralized tissue of teeth were obtained.

Pore-pore relaxation exchange experiments are a recent development and hold great promise to spectrally derive length scales and connectivity information relevant for transport in porous media. However, for large pores, NMR diffusion-relaxation techniques reach a limit because bulk relaxation becomes dominant. A combination of NMR and Xray-CT techniques could be beneficial and lead to better models for regions of unresolved porosity in CT images, increasing the accuracy of image based calculations of transport properties. In this study we carry out numerical NMR pore-pore exchange experiments on selected Xray-CT images of sandstones and carbonate rock, while at the same time tracking information about the geometry and topology of the pore space. We use pore partitioning techniques and geometric distance fields to relate T2-T2 relaxation exchange spectra to underlying structural quantities. It is shown that T2-T2 pore-pore exchange measurements at room temperatures for the samples considered likely reflect exchange between pores and throats or pores and roughness.

Transport of micronutrients (iron, cobalt, nickel, etc.) within biofilms matrixes such as methanogenic granules is of high importance, because these are either essential or toxic for the microorganisms living inside the biofilm. The present study demonstrates quantitative measurements of metal transport inside these biofilms using T1 weighted 3D RARE. It is shown that iron(II)-EDTA diffusion within the granule is independent of direction or the inner structure of the granules. Assuming position dependence of the spin-lattice relaxivity, Fick’s law for diffusion in a sphere can be applied to simulate the diffusion within the methanogenic granules under investigation. A relatively low diffusion coefficient of 2.5*10-11 m2·s-1 was obtained for iron diffusion within the methanogenic granule.

129Xe NMR spectra of natural abundant xenon gas trapped in fully dehydrated mesoporous materials with pore sizes smaller than 2 nm in diameter were observed under atmospheric pressure in the temperature range between 168 and 373 K. The average pore diameters of the materials studied in this paper were 0.5, 1 and about 2 nm for molecular sieves 5A and 13X and synthesized mesoporous silica, respectively. The samples were fully dehydrated using an ultra-high vacuum (UHV) system and xenon gas was introduced with the sample pre-cooled to 168 K just above the boiling point of xenon. The 129Xe NMR spectra were observed as a function of increasing temperature and the 129Xe shift were observed at each temperature for the three samples under atmospheric pressure. The behaviors of xenon atoms in small pores observed in equilibrium states can provide important information on relationships between the pore structure and 129Xe chemical shift.

While diffusion MRI promises an insight into white matter microstructure in vivo, the axonal pathways that connect different brain regions together can only partially be segmented using current methods. Here we present a novel method for estimating the tissue composition of each voxel in the brain from diffusion MRI data, thereby providing a foundation for computing the volume of different pathways in both health and disease. With the tissue dependent diffusion model described in this thesis, white matter is segmented by removing the ambiguity caused by the isotropic partial volumes: both grey matter and cerebrospinal fluid. Apart from the volume fractions of all three tissue types, we also obtain estimates of fibre orientations for tractography as well as diffusivity and anisotropy parameters which serve as proxy indices of pathway coherence. We assume Gaussian diffusion of water molecules for each tissue type. The resulting three-tensor model comprises one anisotropic (white matter) compartment modelled by a cylindrical tensor and two isotropic compartments (grey matter and cerebrospinal fluid). We model the measurement noise using a Rice distribution. Markov chain Monte Carlo sampling techniques are used to estimate posterior distributions over the model’s parameters. In particular, we employ a Metropolis Hastings sampler with a custom burn-in and proposal adaptation to ensure good mixing and efficient exploration of the high-probability region. This way we obtain not only point estimates of quantities of interest, but also a measure of their uncertainty (posterior variance). The model is evaluated on synthetic data and brain images: we observe that the volume maps produced with our method show plausible and well delineated structures for all three tissue types. Estimated white matter fibre orientations also agree with known anatomy and align well with those obtained using current methods. Importantly, we are able to disambiguate the volume and anisotropy information thus alleviating partial volume effects and providing measures superior to the currently ubiquitous fractional anisotropy. These improved measures are then applied to study brain differences in a cohort of healthy volunteers aged 25-65 years. Lastly, we explore the possibility of using prior knowledge of the spatial variability of our parameters in the brain to further improve the estimation by pooling information among neighbouring voxels.

Cuticles are extracellular membranes covering the primary aerial parts of vascular plants. They consist of a multifunctional polymeric material with embedded soluble components, called waxes and serve as the interface between plants and their atmospheric environment, first of all protecting them from desiccation. Waxes are produced within the epidermal cells, then transported to the leaf surface and finally integrated into the polymer or deposited upon the cuticle. Remarkably, damaged wax layers may become repaired within a few hours. Base on an earlier hypothesis we present a theoretical framework explaining how waxes are transported through the plant epidermis by a combination of advection and diffusion. This combination suggests also a self-regulating repair mechanism, based on the assumption that intact cuticles induce an antagonistic equilibrium between advection and diffusion: whenever a wax layer is damaged, the equilibrium is disturbed in favour of advection, starting a repair process, which is intrinsically coming to an end after the cuticle has gained its original thickness.

1H and 19F spin lattice relaxation rates of catalyst layer materials (CLM) of polymer electrolyte membrane fuel cells were measured by the fast field cycling (FFC) method. In contrast to ionomer membranes, 1H relaxation rates of adsorbed water in both platinum-Ketjen black (Pt-KB) catalyst powder and CLM were strongly dependent on Larmor frequency approximated by a power law due to the strong surface interaction of adsorbed water. The difference in the frequency dependence in the Pt-KB and the CLM was attributed to higher acidity of the CLM.

P diffuses predominantly by the interstitial mechanism in Si. Assuming that there is a strong binding energy between P and I, therefore, the basic process of P diffusion is the diffusion of (PI), where I and (PI) represent self-interstitials and P-I pairs, respectively. In the high-P-concentration region, excess I is generated by the dissociation of (PI) and the limiting process of P diffusion depends on whether or not excess I is controlled. That is, if the concentration of excess I decreases relatively to the equilibrium I concentration due to the effect of the decrease in quasi self-interstitial formation energy, or if excess I is removed by the recombination with vacancies, P diffuses fast and the plateau is formed; if not, P diffuses slowly and the rapid fall is formed. In the tail region, the P concentration is low and the limiting process of P diffusion is the basic process of P diffusion, that is, the diffusion of (PI). Excess I generated in the high-P-concentration region diffuses into the low-P-concentration region, and I is supersaturated there. Therefore, the concentration of (PI) increases, resulting in the fast diffusion of P and the formation of the tail.

We study the conditions for reactivity enhancement of catalytic processes in porous solids by use of molecular traffic control (MTC) as a function of grain size. We extend a recently introduced two dimensional model system to three dimensions. With dynamic Monte-Carlo simulations and analytical solution of the associated Master equation we obtain a quantitative description of the MTC effect in the limit of fast reactivity. The efficiency ratio (compared with a topologically and structurally similar reference system without MTC) is inversely proportional to the grain diameter.