Agglomeration of fractal carbon particles into electrically conductive networks in elastomer nanocomposites
Final Report Abstract
Carbon particles from pyrolysis (‘carbon black’) have long been used as fillers in elastomer composites, for example to improve the mechanical properties of tyres and gaskets. The electrical properties of such composites are rarely exploited technically. Today there is an increasing demand for elastic materials that couple mechanical and electrical properties as sensors and actuators. In this project, we studied how this coupling depends on the structure of the conductive networks that carbon black forms in elastomers. We aimed at identifying structureproperty relationships, for example to obtain strong electrical responses to small mechanical deformations. In contrast to highly defined carbon particles such as carbon nanotubes or graphene flakes, carbon black particles are fractal. The transport properties of networks formed by such particles have hardly been studied. In close collaboration between an experimental and a theoretical group, we performed simulations, prepared composites, and characterized them. Our experimental results underline the applicability of carbon black elastomers as low cost, mechanically robust, highly deformable sensor/electrode materials. The identified structureproperty relationships give insight on how to experimentally tune the composites (processing, choice and concentration of components) toward optimal electromechanical properties for sensing applications. Theoretically, we developed a simulation setup to model and analyze the formation of conductive filler networks formed by particles of fractal morphology. In addition, we devised a theoretical framework which allows for analytic predictions on the impact of particle polydispersity, particle anisotropy and particle interactions on the percolation threshold. This framework forms an excellent foundation for the systematic optimization of composite materials.
Publications
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Continuum percolation expressed in terms of density distributions. Physical Review E, 101(6).
Coupette, Fabian; Härtel, Andreas & Schilling, Tanja
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Shape, geometric percolation, and electrical conductivity of clusters in suspensions of hard platelets. Physical Review E, 101(3).
Atashpendar, Arshia; Ingenbrand, Tim & Schilling, Tanja
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Bayesian unsupervised learning reveals hidden structure in concentrated electrolytes. The Journal of Chemical Physics, 154(13).
Jones, Penelope; Coupette, Fabian; Härtel, Andreas & Lee, Alpha A.
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Nearest-neighbor connectedness theory: A general approach to continuum percolation. Physical Review E, 103(4).
Coupette, Fabian; de Bruijn, René; Bult, Petrus; Finner, Shari; Miller, Mark A.; van der Schoot, Paul & Schilling, Tanja
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Percolation of rigid fractal carbon black aggregates. The Journal of Chemical Physics, 155(12).
Coupette, Fabian; Zhang, Long; Kuttich, Björn; Chumakov, Andrei; Roth, Stephan V.; González-García, Lola; Kraus, Tobias & Schilling, Tanja
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Exactly solvable percolation problems. Physical Review E, 105(4).
Coupette, Fabian & Schilling, Tanja
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Microscopic Softening Mechanisms of an Ionic Liquid Additive in an Electrically Conductive Carbon‐Silicone Composite. Advanced Materials Technologies, 7(11).
Zhang, Long; Schmidt, Dominik S.; González‐García, Lola & Kraus, Tobias
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“Percolation: Connecting the Dots”, Ph. D. Thesis, University of Freiburg (2023)
Coupette, F.
