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    THE DEPENDENCE OF DIELECTRIC PERMEABILITY AND SPECIFIC VOLUME RESISTANCE OF POLYMER COMPOSITES ON THE CONCENTRATION OF NANO-DIMENSIONAL ALUMINIUM PARTICLES AND CARBON BLACK FILLERS

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    Objectives. The main idea of the present study was the production of polymer composites based on synthetic isoprene elastomer and low-density polyethylene containing nanoparticles of carbon black and aluminium in various amounts.Methods. An exponential approach was used throughout the study to better control the region of small additives; this control was impossible to achieve using a linear distribution of nanofillers among the small additives. The composites were filled with nanosized aluminium and DG-100 carbon black particles with a specific adsorption surface of 100 m2 /g and having an average particle size of 20-30 nm. Electrophysical parameters were measured by conventional techniques of electron microscopy, electron shadow microscopy and hydrostatic weighing. Maxwell-Wagner theory and polarisation model were applied.Results. For a composite containing 80% of isoprene synthetic rubber (SCI-3) and 20% of low-density polyethylene, the dielectric permeability and specific volume resistivity dependences were studied experimentally and their graphs were plotted against the concentration of nanosized particles of aluminium and carbon black fillers. The features of these curves were considered. It is shown that, for small amounts of Al and carbon black nanoparticles in the composite, significant changes (extrema) take place on the curves ԑ '= ԑ' (C) and ρᵥ = ρᵥ (C), which do not conform to the Maxwell-Wagner polarisation model. For some heterogeneous polymer mixtures, a distribution of carbon black particles was observed that led to a superadditive electrical resistance.Conclusion. It is shown that for small amounts of Al and carbon black nanoparticles in composite materials, significant changes (extrema) take place on the curves ԑ '= ԑ' (C) and ρᵥ = ρᵥ (C) that do not fit within the framework of the Maxwell-Wagner polarisation model
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