Carbon nanotube-filled polymer composites. Numerical simulation of electrical conductivity in three-dimensional entangled fibrous networks

Dalmas, Florent; Dendievel, Rémy; Chazeau, Laurent; Cavaillé, J.Y.; Gauthier, Catherine

doi:10.1016/j.actamat.2006.02.028

Cited by 226 publications

(145 citation statements)

References 39 publications

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“…RISM calculations seem to (approximately) bear this out (40). This conclusion is also corroborated by computer simulations of tortuous rods (33,41,42).…”

Section: Andriy V Kyrylyuk* and Paul Van Der Schootsupporting

confidence: 62%

Continuum percolation of carbon nanotubes in polymeric and colloidal media

Kyrylyuk

Schoot

2008

Proc. Natl. Acad. Sci. U.S.A.

240

188

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We apply continuum connectedness percolation theory to realistic carbon nanotube systems and predict how bending flexibility, length polydispersity, and attractive interactions between them influence the percolation threshold, demonstrating that it can be used as a predictive tool for designing nanotube-based composite materials. We argue that the host matrix in which the nanotubes are dispersed controls this threshold through the interactions it induces between them during processing and through the degree of connectedness that must be set by the tunneling distance of electrons, at least in the context of conductivity percolation. This provides routes to manipulate the percolation threshold and the level of conductivity in the final product. We find that the percolation threshold of carbon nanotubes is very sensitive to the degree of connectedness, to the presence of small quantities of longer rods, and to very weak attractive interactions between them. Bending flexibility or tortuosity, on the other hand, has only a fairly weak impact on the percolation threshold.

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“…RISM calculations seem to (approximately) bear this out (40). This conclusion is also corroborated by computer simulations of tortuous rods (33,41,42).…”

Section: Andriy V Kyrylyuk* and Paul Van Der Schootsupporting

confidence: 62%

Continuum percolation of carbon nanotubes in polymeric and colloidal media

Kyrylyuk

Schoot

2008

Proc. Natl. Acad. Sci. U.S.A.

240

188

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“…In the monodisperse limit we find φ p = D 2 /2λL for hard particles, in agreement with recent analytical work. 32 For ideal particles in the same limit we find 12 This is also consistent with computer simulations 34 and with results that were based on geometric arguments. 9,25,35 In order to highlight the strong cooperative behavior between the rods for small fractions of long ones and to make the highly nonlinear effect of polydispersity more quantitative, we calculate Eq.…”

Section: Tetradisperse Distributionsupporting

confidence: 78%

Connectivity percolation of polydisperse anisotropic nanofillers

Otten¹,

Schoot²

2011

The Journal of Chemical Physics

127

168

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We present a generalized connectedness percolation theory reduced to a compact form for a large class of anisotropic particle mixtures with variable degrees of connectivity. Even though allowing for an infinite number of components, we derive a compact yet exact expression for the mean cluster size of connected particles. We apply our theory to rodlike particles taken as a model for carbon nanotubes and find that the percolation threshold is sensitive to polydispersity in length, diameter, and the level of connectivity, which may explain large variations in the experimental values for the electrical percolation threshold in carbon-nanotube composites. The calculated connectedness percolation threshold depends only on a few moments of the full distribution function. If the distribution function factorizes, then the percolation threshold is raised by the presence of thicker rods, whereas it is lowered by any length polydispersity relative to the one with the same average length and diameter. We show that for a given average length, a length distribution that is strongly skewed to shorter lengths produces the lowest threshold relative to the equivalent monodisperse one. However, if the lengths and diameters of the particles are linearly correlated, polydispersity raises the percolation threshold and more so for a more skewed distribution toward smaller lengths. The effect of connectivity polydispersity is studied by considering nonadditive mixtures of conductive and insulating particles, and we present tentative predictions for the percolation threshold of graphene sheets modeled as perfectly rigid, disklike particles.

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“…Previous studies derived a 2D percolation-based model assuming that the CNTs were straight [41]. While the thin film model was able to explain how different parameters (i.e., length, density, and intrinsic piezoresistivity of nanotubes) were correlated to bulk film electrical and electromechanical properties, other studies reported that the geometry of nanotubes would affect bulk film properties as well [48][49][50]. For example, Yi et al [50] compared the percolation threshold of 2D fibrous networks with different geometries of conductive fibers (i.e., rectangle, sinusoidal, and kinked fibers).…”

Section: Morphology Characterization and Model Generationmentioning

confidence: 99%

“…[48] numerically showed that increasing the tortuosity of CNTs in a 3D fibrous network increased percolation threshold. Berhan et al [52] demonstrated that the effect of the shape of CNTs on percolation threshold increased when its aspect ratio was less than 1,000.…”

Section: Morphology Characterization and Model Generationmentioning

confidence: 99%

Carbon nanotube thin film strain sensors: comparison between experimental tests and numerical simulations

Lee¹,

Loh²

2017

Nanotechnology

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Carbon nanotubes can be randomly deposited in polymer thin film matrices to form nanocomposite strain sensors. However, a computational framework that enables the direct design of these nanocomposite thin films is still lacking. The objective of this study is to derive an experimentally validated and two-dimensional numerical model of carbon nanotube-based thin film strain sensors. This study consisted of two parts. First, multi-walled carbon nanotube (MWCNT)-Pluronic strain sensors were fabricated using vacuum filtration, and their physical, electrical, and electromechanical properties were evaluated. Second, scanning electron microscope images of the films were used for identifying topological features of the percolated MWCNT network, where the information obtained was then utilized for developing the numerical model. Validation of the numerical model was achieved by ensuring that the area ratios (of MWCNTs relative to the polymer matrix) were equivalent for both the experimental and modeled cases. Strain sensing behavior of the percolation-based model was simulated and then compared to experimental test results.

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Carbon nanotube-filled polymer composites. Numerical simulation of electrical conductivity in three-dimensional entangled fibrous networks

Cited by 226 publications

References 39 publications

Continuum percolation of carbon nanotubes in polymeric and colloidal media

Continuum percolation of carbon nanotubes in polymeric and colloidal media

Connectivity percolation of polydisperse anisotropic nanofillers

Carbon nanotube thin film strain sensors: comparison between experimental tests and numerical simulations

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