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STEM characterization of metal clusters in/on oxides

Posted on:2010-06-21Degree:Ph.DType:Thesis
University:University of California, DavisCandidate:Mehraeen, SharegheFull Text:PDF
GTID:2441390002476244Subject:Engineering
Abstract/Summary:
Dispersed metal clusters in or on a support matrix are key phenomenons in many technological fields. Two widely used examples of them which are investigated in this thesis are supported-metal clusters in heterogeneous catalysis and transition metal clusters in diluted magnetic semiconductors (DMS) applied in spintronics. The catalytic activity and selectivity of catalysts often depend sensitively on structure parameters, such as particles size and shape. With the same analogy, the magnetic properties of DMS oxides are sensitively related to the crystal defects of the host material as a consequence of doping the transition metal. Therefore it is essential to develop and understand the correlation between nanostructure and function of these materials. STEM Z-contrast imaging is the best candidate for this type of study because of a high degree of resolution it provides and the unique ability it offers to detect and differentiate between the clusters and oxide matrix due to the large difference between their atomic numbers. Moreover the technique development in the STEM field fosters the conjugation of electron energy Loss Spectroscopy (EELS) and Z-contrast imaging and their widespread use for nearly atomic level chemical analysis at interface, second phases, and isolated defects. The advanced preparation method of supported clusters catalysts which is by carbonyl ligands offers a controlled cluster size and shape. MgO-supported Os clusters and SiO2-supported Ta clusters prepared by this method are adsorbed on oxide to convert into single-sized supported metal aggregates. The last step of preparation method is by removal of the ligands (decarbonylation) which is very important because it determines the final size distribution and shape of such clusters.;Reaching carbonylated decaosmium clusters with the size of theoretically 0.295 nm and the tetrahedral-shape geometry are the aim of the preparation method. The size distribution measurements of sub-nanoclusters of osmium on MgO support after decarbonylation by a modified blurring propagation method of data analysis in Z-contrast images showed a reduction in size compared to the carbonylated clusters and therefore partial decarbonylation of such clusters.;STEM analysis of silica-supported tantalum catalyst showed a relatively wide range in the size of subnanoclusters. In contrast to the first catalyst system there is no theoretical information about the desired size and structure of the tantalum clusters. Therefore in the next step the numbers of Ta atoms in each cluster was measured in order to reveal the shape of the clusters. This was done by quantifying the contribution of the clusters to the contrast in the Z-contrast images by mean of cross section factors. Based on these results two models of atomic Ta clusters were introduced.;In the study of Co-doped TiO2 in the class of DMS oxides the HAADF-STEM images of the thin film Co0.04Ti0.96O 2 grown in vacuum and in 100 mTorr Ar+H2 gas were compared. STEM images of the first system showed no evidence of clustering and EELS analysis showed the identical intensity for Co-L2,3 peaks across the thin film to prove the homogeneity in the microstructure, therefore there is a strong probability for the origin of ferromagnetism in the thin film to be intrinsic by the contribution of the 3d dopant ions of substitutional Co. STEM/EELS analysis on the second system confirmed the presence of embedded Co clusters with the mixed valance state for the Co and therefore the mechanism of FM to be by the mean of carrier-mediated exchange responsible for magnetism.;In this thesis ability of the combined STEM techniques, fast characterization and direct interpretation in the analysis of nanoscale materials and nanostructures provided the basis for predictive material design with more desirable physical properties.
Keywords/Search Tags:Clusters, STEM, Size
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