Morphology Classification of Nanocomposite Metal/Plasma Polymer Thin Films

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A fully PC controlled FE SEM intended for both – for high vacuum as well as for low vacuum operations. Outstanding optical properties, flicker-free...


Many efforts have been made in the last decades to obtain nanomaterials with the determined structure and functionality,using nanoscience knowledge and various nanotechnologies. Nanostructured and nanocomposite materials are used in many existing and emerging technologies. In particular, profound interest is taken in nanocomposites consisting of metal nanoparticles embedded into a polymer matrix due to their special functional properties. Nanocomposite metal/plasma polymer films have been prepared by simultaneous metal clusters deposition and plasma polymerization from a mixture of Ar/n-Hexane. The description of basic morphology and structure of the films is based on MIRA3 FE-SEM with STEM adaptor measurements and software module Particles for clusters classifications.

Poor adhesion of nanostructured metal cluster films to the substrate was observed. This is recognized as a complication for further applications of these materials. To solve this problem, metal nanoclusters were embedded into a polymer matrix. Nanocomposite thin films were prepared by codeposition of nanoclusters and polymer matrix onto the substrate from two independent sources as schematically.

Gas Aggregation Source (GAS) based on planar magnetron (Haberland concept) was used for the production of metal clusters. Silver target was chosen as a model metal. RF planar magnetron with graphite target was served as a source for plasma polymerization process and was operated in Ar/n-Hexane gas mixture at a constant power of 20 W.

Software module Particles


Transmission electron microscope is usually used for determination of morphology and structure of the nanocomposite cluster films. The images obtained by STEM detector in bright field demonstrate that for certain thicknesses of nanocomposites films, SEM can be successfully applied. Furthermore with software module Particles, designated exclusively for particle analysis, classification of clusters with statistical output can be easily perfomed.

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