Matias Nordin

A mixed basis approach in the SGP-limit.

A perturbation method for computing quick estimates of the echo decay in pulsed spin echo gradient NMR diffusion experiments in the short gradient pulse limit is presented. The perturbation basis involves (relatively few) dipole distributions on the boundaries generating a small perturbation matrix in O(s(2)) time, where s denotes the number of boundary elements. Several approximate eigenvalues and eigenfunctions to the diffusion operator are retrieved. The method is applied to 1D and 2D systems with Neumann boundary conditions.

Bias Correction of Long-Term Satellite Monthly Precipitation Product (TRMM 3B43) over the Conterminous United States

AbstractThe Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) has provided a valuable precipitation dataset for hydrometeorological studies (1998–2015). However, TMPA shows some differences when compared to the ground-based estimates. In this study, a correction model is developed to improve the accuracy of the TRMM precipitation monthly product by reducing the bias compared to the ground-based estimates. The TRMM 3B43 precipitation product is compared with the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) and with gridded precipitation estimates acquired from the CPC Unified Precipitation Project, two ground-based precipitation estimates, in the conterminous United States. The bias between the satellite and ground-based estimates is compared with mean surface temperature and elevation, respectively. A weak linear relationship is observed between the bias and temperature but a moderate inverse linear relationship is observed between the bias and ...

Magnetic orientation of nontronite clay in aqueous dispersions and its effect on water diffusion

The diffusion rate of water in dilute clay dispersions depends on particle concentration, size, shape, aggregation and water-particle interactions. As nontronite clay particles magnetically align parallel to the magnetic field, directional self-diffusion anisotropy can be created within such dispersion. Here we study water diffusion in exfoliated nontronite clay dispersions by diffusion NMR and time-dependant 1H-NMR-imaging profiles. The dispersion clay concentration was varied between 0.3 and 0.7 vol%. After magnetic alignment of the clay particles in these dispersions a maximum difference of 20% was measured between the parallel and perpendicular self-diffusion coefficients in the dispersion with 0.7 vol% clay. A method was developed to measure water diffusion within the dispersion in the absence of a magnetic field (random clay orientation) as this is not possible with standard diffusion NMR. However, no significant difference in self-diffusion coefficient between random and aligned dispersions could be observed.

Deriving time-dependent diffusion and relaxation rate in porous systems using eigenfunctions of the Laplace operator

Porous systems are investigated using eigendecomposition of the Laplace matrix. Three parameters; tortuosity, surface-to-pore volume ratio and relaxation rate are derived from the eigenvalue spectrum of the Laplace matrix and connected to the parameters in the Padé approximation, an expression often used to describe the time-dependent diffusion coefficient in porous systems. The Padé length is identified for systems with large pore to connector volume ratio. The results are compared with simulations.

Estimation of mass thickness response of embedded aggregated silica nanospheres from high angle annular dark-field scanning transmission electron micrographs

In this study, we investigate the functional behaviour of the intensity in high‐angle annular dark field scanning transmission electron micrograph images. The model material is a silica particle (20 nm) gel at 5 wt%. By assuming that the intensity response is monotonically increasing with increasing mass thickness of silica, an estimate of the functional form is calculated using a maximum likelihood approach. We conclude that a linear functional form of the intensity provides a fair estimate but that a power function is significantly better for estimating the amount of silica in the z‐direction.

From static micrographs to particle aggregation dynamics in three dimensions.

Studies on colloidal aggregation have brought forth theories on stability of colloidal gels and models for aggregation dynamics. Still, a complete link between developed frameworks and obtained laboratory observations has to be found. In this work, aggregates of silica nanoparticles (20 nm) are studied using diffusion limited cluster aggregation (DLCA) and reaction limited cluster aggregation (RLCA) models. These processes are driven by the probability of particles to aggregate upon collision. This probability of aggregation is one in the DLCA and close to zero in the RLCA process. We show how to study the probability of aggregation from static micrographs on the example of a silica nanoparticle gel at 9 wt%. The analysis includes common summary functions from spatial statistics, namely the empty space function and Ripleys K‐function, as well as two newly developed summary functions for cluster analysis based on graph theory. One of the new cluster analysis functions is related to the clustering coefficient in communication networks and the other to the size of a cluster. All four topological summary statistics are used to quantitatively compare in plots and in a least‐square approach experimental data to cluster aggregation simulations with decreasing probabilities of aggregation. We study scanning transmission electron micrographs and utilize the intensity – mass thickness relation present in such images to create comparable micrographs from three‐dimensional simulations. Finally, a characterization of colloidal silica aggregates and simulated structures is obtained, which allows for an evaluation of the cluster aggregation process for different aggregation scenarios. As a result, we find that the RLCA process fits the experimental data better than the DLCA process.