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Simulating the effective electric conductivity of polymer composites with high aspect ratio fillers
KTH, School of Chemical Science and Engineering (CHE), Fibre and Polymer Technology.
KTH, School of Chemical Science and Engineering (CHE), Fibre and Polymer Technology, Polymeric Materials.
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2016 (English)In: Composites Science And Technology, ISSN 0266-3538, E-ISSN 1879-1050, Vol. 132, 16-23 p.Article in journal (Refereed) Published
Abstract [en]

Three simulation models have been developed for predicting the electrical conductivity and the electrical percolation threshold of field-grading polymer composites intended for high voltage applications. The three models are based on finite element modelling (FEM), percolation threshold modelling (PTM) and electrical networks modelling (ENM). A Monte Carlo algorithm was used to construct the geometries, with either soft-core (overlapping) or hard-core/soft-shell (non-overlapping) fibres. Conductivity measurements on carbon-fibre/PMMA composites with well-defined fibre aspect ratios were used for experimental validation. The average fibre orientations were calculated from scanning electron micrographs. The soft-core PTM model with experimental fibre orientations and without adjustable parameters gave accurate (R-2 = 0.984) predictions of the electrical percolation threshold as a function of aspect ratio. The corresponding soft-core ENM model, with close-contact conductivity calculated with FEM, resulted in good conductivity predictions for the longest fibres, still without the use of any adjustable parameters. The hard-core/soft-shell versions of the models, using the shell thickness as an adjustable parameter, gave similar but slightly poorer results.

Place, publisher, year, edition, pages
Elsevier, 2016. Vol. 132, 16-23 p.
Keyword [en]
Composites, Carbon-fibre, Field-grading, Simulation, Electrical conductivity
National Category
Composite Science and Engineering
URN: urn:nbn:se:kth:diva-192391DOI: 10.1016/j.compscitech.2016.06.008ISI: 000381653300003ScopusID: 2-s2.0-84975824529OAI: diva2:968777
Swedish Research Council, 6213

QC 20160912

Available from: 2016-09-12 Created: 2016-09-12 Last updated: 2016-09-12Bibliographically approved

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Nilsson, FritjofChen, FeiGedde, Ulf W.Hedenqvist, Mikael S.
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