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Fractal characterization of electrical conductivity and mechanical properties of copper particulate polyester matrix composites using image processing

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Abstract

In this study, the electrical conductivity and the mechanical properties of the dendritic-shaped copper powder-filled unsaturated polyester resin were investigated through micro-images using fractal dimension characterization, image processing technique and box-counting method. In these experiments, the polyester matrix is combined with copper particulate filler to determine the effects of filler concentration on the electrical conductivity, material hardness, stiffness and tensile characterization of the composite mixture. It is observed that the fractal dimension is affected by the filler concentration indirectly. The increase in filler concentration added in the resin causes the spatial pattern of the conductive chain formed in the matrix medium to be more complex. Filler particle agglomeration also affects the fractal dimension. The electrical conductivity of agglomerated structures is better than a uniform structure. Image processing technique and fractal dimension parameter are powerful tools for investigating the filler spatial dispersion morphology of the composite material.

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Acknowledgements

The author gratefully acknowledges the moral support of the TÜBİTAK SAGE.

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  1. The Scientific and Technological Research Council of Turkey, Defense Industries Research and Development Institute, (TÜBİTAK SAGE), 06261, Ankara, Turkey

    Kemal Yaman

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  1. Kemal Yaman
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Correspondence to Kemal Yaman.

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Yaman, K. Fractal characterization of electrical conductivity and mechanical properties of copper particulate polyester matrix composites using image processing. Polym. Bull. 79, 3309–3332 (2022). https://doi.org/10.1007/s00289-021-03665-2

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  • DOI: https://doi.org/10.1007/s00289-021-03665-2

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