Quantitative Electron Tomography for Nanostructured Materials

Abstract

The controlled assembly of materials on the nanoscale has been a major focus of research across many scientific disciplines. In the nanometer size range, materials characteristics can be tuned not only by composition but more importantly by size and shape of constituent phases, giving rise to exceptional optical, magnetic, electric, mechanical and catalytic properties. To gain insight into the relation between a structure and its properties, dedicated characterization techniques are required that provide detailed 3D information with nanometer resolution. One of the most promising and rapidly developing techniques, in this respect, is electron tomography (ET), a method for obtaining 3D structural information from a series of electron micrographs. ET offers, in addition, the possibility to extract quantitative information on constituent phases which is explored in depth in this thesis. From a materials viewpoint the focus is on catalysts which are indispensable to society because of their prominent role in the manufacture of most chemical products. In supported heterogeneous catalysts, the active components such as transition metals and metal oxides are finely dispersed on a high surface area support to maximize the number of catalytically active sites per unit mass of material. The high surface area support anchors the active components to prevent sintering at elevated temperatures. With case studies of nickel oxide supported on ordered mesoporous silica SBA-15, ruthenium supported on carbon nanotubes, and gold supported inside of mesoporous zirconia spheres, manual and automated quantification approaches in combination with structure modeling are presented. It is shown that knowledge of the active phase particle size, location, neighbor distance, and local loading are key facts to understand and improve catalyst preparation and performance by tuning nanoscale morphologies. Another very interesting avenue to nanomaterials is bottom-up assembly of prefabricated building blocks into large, ordered structures, a concept that is shared across several disciplines. With examples of four binary nanoparticles superlattices it is shown that a comprehensive, quantitative, 3D characterization by ET down to the single nanocrystal level can be achieved. ET and image analysis provide accurate lattice parameters of a given superlattice, unambiguously revealing the crystal structure including possible distortions. Furthermore, the ability to detect defects and their effect on the surrounding lattice are considered to be instrumental in a microscopic understanding of emerging materials properties. This thesis illustrates quantitative approaches into the local 3D morphology of complex nanostructured materials by ET that will contribute in the future to a more rational design of this important class of materials.