Monte Carlo model for the study of percolation thresholds in composites filled with circular conductive nano-disks

Oskouyi, Amirhossein Biabangard; Mertiny, Pierre

doi:10.1016/j.proeng.2011.04.068

Cited by 25 publications

(21 citation statements)

References 18 publications

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“…Using simulation in physics allows the number of experiments to be reduced and thus time and cost for development at laboratory and industry scale by linking theory and experimentation [10][11][12][13][14][15][16]. Functionalisation of nanoparticles, when they are dispersed in an epoxy resin, could have two aims: improving the dispersion quality by decreasing the interaction between nanoparticles [17][18][19], and improving the mechanical properties of the composite by improving the interfacial bonding between matrix, nanoparticles and micro-reinforcement [20][21][22][23].…”

Section: Fabrication Challengesmentioning

confidence: 99%

Effect of pre and Post-Dispersion on Electro-Thermo-Mechanical Properties of a Graphene Enhanced Epoxy

Poutrel

Wang

et al. 2016

Appl Compos Mater

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Graphene nanoplatelet (GNP) modified epoxy nanocomposites are becoming attractive to aerospace due to possible improvements in their mechanical, electrical and thermal properties at no weight cost. The process of obtaining reliable material systems provides many challenges, especially at larger scale (a volume effect). This paper reports on the main fabrication stages of GNP-based epoxy composites, namely (i) pre-dispersion, (ii) dispersion, and (iii) post-dispersion. Each stage is developed to show the interest and potential it delivers for property enhancement. Chemical modification of GNP is presented; functionalisation by Triton X-100 shows elastic modulus improvements of the epoxy at low particle content (≤3%). The post-dispersion step as an alignment of GNP into the epoxy by an electrical field is discussed. The electrical conductivity is below the simulated percolation threshold and an improvement of the thermal diffusivity of 220% when compared to non-oriented GNP epoxy sample is achieved. The work demonstrates how the addition of functionalised graphene platelets to an epoxy resin will allow it to act as electrical and thermal conductor rather than as insulator

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Section: Fabrication Challengesmentioning

confidence: 99%

Effect of pre and Post-Dispersion on Electro-Thermo-Mechanical Properties of a Graphene Enhanced Epoxy

Poutrel

Wang

et al. 2016

Appl Compos Mater

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“…As far as the percolation models are concerned, there is a wide variety of proposed methodologies taking into account the filler shape, aspect ratio, tunnelling distance, overlapping, and the formation of agglomerations. Oskouyi et al [16] apply the Monte Carlo method to model the percolation threshold for disk-shaped fillers, simulating the conductive network formed by inclusions like graphene nanoplatelets (GNP). Later, Ambrosetti et al [17] conducted a numerical study to investigate a system's percolative properties consisting of hard oblate ellipsoids of revolution surrounded with soft penetrable shells.…”

Section: Electrical Simulation Modelsmentioning

confidence: 99%

“…Finally, the orientation of graphene layers in the volume is modelled by the orientation of the local coordinate system with rotation angles of THXY ∈ [0, 90], THZY ∈ [0, 90] and THXZ ∈ [−90, 90]. The elements, which have not been chosen to represent graphene sheets, are simulated as pure insulating matrix with electrical resistivity of 10 16 Ωm. The RVE model was built up under the same principles as the unit cell one.…”

Section: Representative Volume Element (Rve)mentioning

confidence: 99%

Predictive Model of Graphene Based Polymer Nanocomposites: Electrical Performance

2016

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In this computational work, a new simulation tool on the graphene/polymer nanocomposites electrical response is developed based on the finite element method (FEM). This approach is built on the multi-scale multi-physics format, consisting of a unit cell and a representative volume element (RVE). The FE methodology is proven to be a reliable and flexible tool on the simulation of the electrical response without inducing the complexity of raw programming codes, while it is able to model any geometry, thus the response of any component. This characteristic is supported by its ability in preliminary stage to predict accurately the percolation threshold of experimental material structures and its sensitivity on the effect of different manufacturing methodologies. Especially, the percolation threshold of two material structures of the same constituents (PVDF/Graphene) prepared with different methods was predicted highlighting the effect of the material preparation on the filler distribution, percolation probability and percolation threshold. The assumption of the random filler distribution was proven to be efficient on modelling material structures obtained by solution methods, while the through-the -thickness normal particle distribution was more appropriate for nanocomposites constructed by film hot-pressing. Moreover, the parametrical analysis examine the effect of each parameter on the variables of the percolation law. These graphs could be used as a preliminary design tool for more effective material system manufacturing.

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“…Most of them are based on molecular dynamics and geometrical programming routines, being able mainly to predict the percolation threshold of the nanocomposites with high computational cost. Oskouyi et al [16] appeared to be the first to apply the method of Monte Carlo model to study the percolation threshold for disk-shaped fillers, simulating the conductive network formed by inclusions like graphene nanoplatelets. Later, Hicks et al [17] developed a tunnelling-percolation model to investigate electrical transport in graphene-based nanocomposites, covering the need of a suitable model able to predict the full electrical response of semiconducting 2D element reinforced materials.…”

Section: Introductionmentioning

confidence: 99%

Multi-Scale Finite Element Analysis of Graphene/Polymer Nanocomposites Electrical Performance

Manta¹,

Grésil²,

Soutis³

2016

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)

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Monte Carlo model for the study of percolation thresholds in composites filled with circular conductive nano-disks

Cited by 25 publications

References 18 publications

Effect of pre and Post-Dispersion on Electro-Thermo-Mechanical Properties of a Graphene Enhanced Epoxy

Effect of pre and Post-Dispersion on Electro-Thermo-Mechanical Properties of a Graphene Enhanced Epoxy

Predictive Model of Graphene Based Polymer Nanocomposites: Electrical Performance

Multi-Scale Finite Element Analysis of Graphene/Polymer Nanocomposites Electrical Performance

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