ABSTRACT
We have used Electron Tomography (ET) to reveal the detailed three-dimensional structure of particulate hydrogels, a material category common in e.g. controlled release, food science, battery and biomedical applications. A full understanding of the transport properties of these gels requires knowledge about the pore structure and in particular the interconnectivity in three dimensions, since the transport takes the path of lowest resistance. The image series for ET were recorded using High-Angle Annular Dark Field Scanning Transmission Electron Microscopy (HAADF-STEM). We have studied three different particulate silica hydrogels based on primary particles with sizes ranging from 3.6nm to 22nm and with pore-size averages from 18nm to 310nm. Here, we highlight the nanostructure of the particle network and the interpenetrating pore network in two and three dimensions. The interconnectivity and distribution of width of the porous channels were obtained from the three-dimensional tomography studies while they cannot unambiguously be obtained from the two-dimensional data. Using ET, we compared the interconnectivity and accessible pore volume fraction as a function of pore size, based on direct images on the nanoscale of three different hydrogels. From this comparison, it was clear that the finest of the gels differentiated from the other two. Despite the almost identical flow properties of the two finer gels, they showed large differences concerning the accessible pore volume fraction for probes corresponding to their (two-dimensional) mean pore size. Using 2D pore size data, the finest gel provided an accessible pore volume fraction of over 90%, but for the other two gels the equivalent was only 10-20%. However, all the gels provided an accessible pore volume fraction of 30-40% when taking the third dimension into account.
ABSTRACT
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 Ripley's 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.
