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- Polyorganosiloxane (3) (entfernen)
Characterization of polymer nanoparticles by asymmetrical flow field flow fractionation (AF-FFF)
(2010)
Here, we present the synthesis, characterization and magnetic separation of magnetic polyorganosiloxane nanoparticles. Magnetic iron oxide nanoparticles with average particle radii of 3.2 nm had been synthesized by a simple coprecipitation process of iron(II) and iron(III) salt in basic solution. Afterwards, the particles were successfully incorporated into a polyorganosiloxane network via a polycondensation reaction of trimethoxymethylsilane (T), diethoxydimethylsilane (D) and the functional monomer (chloromethylphenyl)trimethoxysilane (ClBz-T) in aqueous dispersion. A core–shell system was chosen to increase the flexibility of the system concerning size, composition and functionalization possibilities. The magnetic nanocapsules with particle radii below 60 nm were separated from non-magnetic material with a high effectiveness by the use of commercially available separation columns which are commonly used for isolation of microbeads and subsequently characterized via transmission electron microscopy (TEM), asymmetrical flow field-flow fractionation (AF-FFF), superconducting quantum interference device (SQUID) and Mössbauer spectroscopy.
The acid catalyzed solgel type synthesis of polyorganosiloxane core-shell nanoparticles with removable PDMS core in aqueous dispersion leads to the inherent formation of a bimodal size distribution with smaller spheres having approximately 26 nm radii and larger nanoparticles with 60 nm in radius. The origin of the self-organized bimodality is investigated and finally attributed to a combination of stabilization of the growing particles due to i) a miniemulsion-type stabilization by the ultrahydrophobe PDMS and ii) by surface co-stabilization by the employed surfactant. The significant influence of temperature, pH, stirrer speed and amount of the surfactant on the particle sizes allows for the design and fine-tuning of different nanoparticles sizes and distributions.