Monte Carlo modeling of the fiber curliness effect on percolation of conductive composites

M., H.; Gao, X.-L.; Tolle, Tia Benson

doi:10.1063/1.3309590

Cited by 30 publications

(16 citation statements)

References 21 publications

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“…36,37 The effective aspect ratio of ller gradually increases with its stiffness, which reduces the percolation threshold of PNCs. 13,27,[38][39][40]44 Under the shear eld, it induces the destruction and build-up of the conductive network. CNTs in a shear gradient can pick up other CNTs and stick to each other, which is called the 'picking-up' mechanism.…”

Section: Discussionmentioning

confidence: 99%

“…25 The contribution of longer CNTs to the formation of conductive network is through linking the shorter CNTs. 26,27 By employing molecular dynamics simulation, nanorods are more effective in forming a percolating network at a lower volume fraction than nanoplates and nanospheres. 28 The anisotropy of the electrical property of aligned CNT/polymer composites is mainly affected by the average conductive pathway density of CNTs.…”

Section: Introductionmentioning

confidence: 99%

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Controlling the electrical conductive network formation in nanorod filled polymer nanocomposites by tuning nanorod stiffness

Gao

Zhang

et al. 2018

RSC Adv.

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In this work, by employing a coarse-grained molecular dynamics simulation, we have investigated the effect of the nanorod (NR) stiffness on the relationship between the NR microstructure and the conductive probability of NR filled polymer nanocomposites (PNCs) under the quiescent state and under the shear field. The conductive probability of PNCs is gradually enhanced with the increase of NR stiffness in the quiescent state; however, it first increases and then decreases under the shear field. As a result, the largest conductive probability appears at moderate NR stiffness, which results from the competition between the improved effective aspect ratio of the NR and the breakage of the conductive network.Meanwhile, compared with in the quiescent state, under the shear field the decrease or the increase of the conductive probability depends on the NR stiffness. At low NR stiffness, the increase of the effective aspect ratio of NR enhances the conductive probability, while at high NR stiffness, the breakage of the conductive network reduces the conductive probability. For flexible NRs, the conductive probability first increases and then decreases with increasing the shear rate. The maximum effective aspect ratio of NRs appears at the moderate shear rate, which is consistent with the conductive probability. In summary, this work presents some further understanding about how NR stiffness affects the electric conductive properties of PNCs under the shear field.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Controlling the electrical conductive network formation in nanorod filled polymer nanocomposites by tuning nanorod stiffness

Gao

Zhang

et al. 2018

RSC Adv.

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“…Fillers with high aspect ratios normally involve waviness [10][11][12][13]. For such cases, the results obtained based on ellipsoids should be modified to account for the waviness.…”

Section: Waviness Of Fillers With High Aspect Ratiosmentioning

confidence: 99%

Optimal Percolation Thresholds of Two- and Three-Dimensional Engineering Composites

2012

Journal of Engineering Materials and Technology

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Theoretical prediction of percolation thresholds universally applicable for various composites remains a major theoretical challenge. In the work done by Xu (2011, "Ellipsoidal Bounds and Percolation Thresholds of Transport Properties of Composites," Ada Mech., 223, pp. 765-774), a variational method is developed to predict optimal percolation thresholds for transport properties of three dimensional composites subjected to full dispersion of fillers. In this paper, simplified formulae are provided for engineering applications of 3D composites. New formulae are derived for optimai percolation thresholds of 2D composites, i.e., laminates and thin films, and for composites containing a combination of fillers with different aspect ratios. The effects of dimensionality and waviness are especiaily discussed.

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“…[12][13][14][15][16][17][18][19][20][21][22][23][24] Due to their small cross section compared to their total length, CNT may curve to various degrees and affect the CNT connectivity within the network. 15 Waviness remains a difficult parameter to study experimentally because the presence of curved CNT drastically depends on the experimental conditions used for the CNT growth. 25 In contrast, the wavy nature of CNT has been computationally investigated at different occasions but rarely with an atomistic precision.…”

Section: Introductionmentioning

confidence: 99%

“…25 In contrast, the wavy nature of CNT has been computationally investigated at different occasions but rarely with an atomistic precision. [12][13][14][15][16][17][18] The more usual method to model waviness is by connecting a series of straight segments that form an object and by defining a wave angle between segments. Previous works have modelled flexible CNT made of up to 20 segments, but it appears that 10 segments would be enough to give an appropriate description of waviness.…”

Section: Introductionmentioning

confidence: 99%

Electron percolation in realistic models of carbon nanotube networks

Simoneau

Villeneuve

Rochefort

2015

Journal of Applied Physics

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The influence of penetrable and curved carbon nanotubes (CNT) on the charge percolation in threedimensional disordered CNT networks have been studied with Monte-Carlo simulations. By considering carbon nanotubes as solid objects but where the overlap between their electron cloud can be controlled, we observed that the structural characteristics of networks containing lower aspect ratio CNT are highly sensitive to the degree of penetration between crossed nanotubes. Following our efficient strategy to displace CNT to different positions to create more realistic statistical models, we conclude that the connectivity between objects increases with the hard-core/ soft-shell radii ratio. In contrast, the presence of curved CNT in the random networks leads to an increasing percolation threshold and to a decreasing electrical conductivity at saturation. The waviness of CNT decreases the effective distance between the nanotube extremities, hence reducing their connectivity and degrading their electrical properties. We present the results of our simulation in terms of thickness of the CNT network from which simple structural parameters such as the volume fraction or the carbon nanotube density can be accurately evaluated with our more realistic models. V

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Monte Carlo modeling of the fiber curliness effect on percolation of conductive composites

Cited by 30 publications

References 21 publications

Controlling the electrical conductive network formation in nanorod filled polymer nanocomposites by tuning nanorod stiffness

Controlling the electrical conductive network formation in nanorod filled polymer nanocomposites by tuning nanorod stiffness

Optimal Percolation Thresholds of Two- and Three-Dimensional Engineering Composites

Electron percolation in realistic models of carbon nanotube networks

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