Nanodisperse Many-Particle-Systems: Concept, Structure-Property Relationships and Characterization Strategy
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Nanodisperse Many-Particle-Systems: Concept, Structure-Property Relationships and Characterization Strategy Vladimir P. Oleshko University of Virginia, Department of Materials Science & Engineering, Charlottesville, VA 22904-4745 ABSTRACT Nanodisperse many-particle-systems (MPS), often forming compact matter, consist of atomic/molecular nano-sized building units, which interact with each other. The interactions among clusters and with the embedding matrix mainly determine the macroscopic properties of the material. The functional properties of nanostructured matter depend on a number of parameters that describe the single cluster (structure, chemical composition, size and shape), the near-order and far-order effects of a given cluster and which can be modeled using the concept of MPS. The specified parameters have to be considered in a detailed multilevel ultramicroscopic and analytical characterization, and several can be manipulated to tailor new materials with desired optical, electronic or catalytic properties. Such approach provides logical synergism between modeling, engineering and characterization of disperse composite nanomaterials by the combination of analytical electron microscopy and image analysis techniques, as illustrated by examples utilizing chemically stabilized “giant” clusters of noble metals and multifractal percolation nanostructures of Ag filaments. INTRODUCTION A vast number of practically important nanodisperse materials such as nanocrystalline thin films, small-domain-matter, particle-matrix-systems (metal-non-metal systems, imaging materials, cluster tunnel junctions, quantum dots, etc.), designated as many-particle-systems (MPS) [1], are forming macroscopic compact matter and consist of nano-sized atomic/molecular building units, which
Figure 1. Engineering of nanodisperse materials using unit-block-system hierarchical MPS models and characterization by the combination of AEM and digital image analysis techniques.
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interact with each other. The interactions between clusters and with the embedding matrix/support mainly determine the macroscopic properties of the material. The need for knowledge of properties of such systems arises in a variety of contexts, ranging from purely theoretical problems (small particle geometry, bonding, thermodynamics, quantization effects and electronic states, optical response of cluster matter) to numerous applications (adsorption, catalysis, powder techniques, electronics). Properties of nanodisperse matter depend on the number of parameters, which describe the single cluster (unit: atomic/molecular structure, chemical composition, size/shape), the nearorder and far-order effects of a given cluster, N-particle aggregates (block: nano-/microstructure, topography, separateness, microcomposition, filling, fractal dimensions), and macroscopic manyparticle-matter (system: macrostructure, composition, texture). With MPS models (Fig. 1), one can specify parameters that have to be considered in a detailed ultramicroscopic and analytical charac
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