Lowering the percolation threshold of single-walled carbon nanotubes using polystyrene/poly(3,4-ethylenedioxythiophene): poly(styrene sulfonate) blends

Hermant, MC Marie Claire; Klumperman, Bert; Kyrylyuk, AV Andriy; Schoot, Ppam Paul van der; Koning, CE Cor

doi:10.1039/b814976c

Cited by 78 publications

(69 citation statements)

References 43 publications

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“…The reciprocal weight-average length dependence of the PT that we find agrees with results for interpenetrable sticks 7 and hard rods with monodisperse diameters and connectivity ranges, 12 for which we find − D. The value of λ plausibly depends on the dielectric constant of the host medium 12 and can also effectively be manipulated by a penetrable conductive coating of the CNTs, such as the conductive polymer blend poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS), 21,33 discussed in more detail in Sec. VI.…”

Section: Tetradisperse Distributionsupporting

confidence: 80%

“…53 For such a coating, a polymeric latex known as PEDOT:PSS has been used that also effectively stabilizes the CNTs in a solution. 21,33 We note that the envisaged conduction mechanism of nearest-neighbor hopping in our model may lose its meaning for the rods with the soft conductive coating. Still, if we presume that the effective hopping distance is much larger for a coated CNT than for one without a coating, then the probability of charge transport between two CNTs without a coating is negligible compared to that of a pair with at least one coated particle.…”

Section: Mixtures Of Conductive and Insulating Particlesmentioning

confidence: 99%

“…In support of this conjecture, we note that it is quite plausible that during the sonication of the CNTs, a necessary exfoliation step in the production process of the nanocomposite pushes the distribution of CNTs to become very skewed toward the direction of the shorter rods. 5,21 Indeed, exfoliation goes hand-in-hand with tube scission, and long tubes break more easily than short ones. 49 In fact, wide tubes break less easily than narrow ones, casting doubt on the assumption of independent length and width distributions that we presumed so far.…”

Section: Realistic Size Distributionsmentioning

confidence: 99%

“…19 Another way to achieve the goal of lowering the PT is to make use of an electrically conducting coating of the CNTs, replacing the surfactants that often are used to disperse the CNTs in water in the early stages of the production process of the nanocomposite. 21 This coating then in a way manipulates the (effective) hopping distance λ, provided it is in a way soft and physically penetrable to other CNTs. 53 For such a coating, a polymeric latex known as PEDOT:PSS has been used that also effectively stabilizes the CNTs in a solution.…”

Section: Mixtures Of Conductive and Insulating Particlesmentioning

confidence: 99%

“…From this we obtain an explicit expression for the average cluster size, with the underlying assumption that the network is formed in the fluid stages of the nanocomposite production process. 5,21 For definiteness, we apply our theory to harshly repulsive (nonoverlapping) rodlike carbon nanotubes, invoke a secondvirial approximation, and use a generalized version of the socalled cherry-pit, or core-shell model that considers two particles to be connected if they are sufficiently close to each other. 22,23 This is reasonable because nanotubes in conducting networks do not actually touch each other in the final product and charge transport across nanotubes occurs via electron hopping between them.…”

Section: Introductionmentioning

confidence: 99%

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Connectivity percolation of polydisperse anisotropic nanofillers

Otten¹,

Schoot²

2011

The Journal of Chemical Physics

Self Cite

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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Section: Tetradisperse Distributionsupporting

confidence: 80%

Section: Mixtures Of Conductive and Insulating Particlesmentioning

confidence: 99%

Section: Realistic Size Distributionsmentioning

confidence: 99%

Section: Mixtures Of Conductive and Insulating Particlesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Connectivity percolation of polydisperse anisotropic nanofillers

Otten¹,

Schoot²

2011

The Journal of Chemical Physics

Self Cite

127

168

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Computational Modeling of Carbon Nanoﬁller Networks in Polymer Composites

Mora¹

2022

Nanocomposites

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A Unified View on Nanoscale Packing, Connectivity, and Conductivity of CNT Networks

Gnanasekaran

Grimaldi

With

et al. 2019

Adv Funct Materials

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The design of functional structures from primary building blocks requires a thorough understanding of how size, shape, and particle-particle interactions steer the assembly process. Specifically, for electrically conductive networks build from carbon nanotubes (CNTs) combining macroscopic characterization and simulations shows that the achievable conductivity is mainly governed by CNT aspect ratio, length dispersity and attractive interactions. However, a direct link between the actual 3D network topology that leads to the observed electrical conductivity has not been established yet due to a lack in nanoscale experimental approaches. Here it is shown experimentally for randomly packed (jammed) CNT networks that the CNT aspect ratio determines, as theoretically predicted, the contact number per CNT which in turn scales linearly with the resulting electrical conductivity of the CNT network. Furthermore, nanoscale packing density, contact areas, contact distribution in random and nonrandom configurations, and least resistance pathways are quantified. The results illustrate how complex nanoscale networks can be imaged and quantified in 3D to understand and model their functional properties in a bottom-up fashion.

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Lowering the percolation threshold of single-walled carbon nanotubes using polystyrene/poly(3,4-ethylenedioxythiophene): poly(styrene sulfonate) blends

Cited by 78 publications

References 43 publications

Connectivity percolation of polydisperse anisotropic nanofillers

Connectivity percolation of polydisperse anisotropic nanofillers

Computational Modeling of Carbon Nanoﬁller Networks in Polymer Composites

A Unified View on Nanoscale Packing, Connectivity, and Conductivity of CNT Networks

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