Predictions of electrical percolation of graphene‐based nanocomposites by the three‐dimensional Monte Carlo simulation

Abstract

Disk model is usually used to represent graphene nanoplatelets (GNPs) which are considered as frame‐like structure with edges and corners, and it has lack of quantitative accuracy. In order to minimize error caused by morphology, distribution, and interaction between GNPs and matrix, square and folded plate models were constructed to predict the percolation volume fraction (ϕc) of GNPs‐based nanocomposites by calculating connection possibility. Meanwhile, disk model is used for comparison. The results revealed that the ϕc of square and folded plate models is smaller than that of disk model with consistent parameters, and it is concluded that the ϕc of GNPs‐based nanocomposites predicted by disk model should be higher than that of experimental. The correctness of mixed model of square and folded plate is also verified by experimental. Due to the agglomeration of GNPs under the actual situation, the result of simulation is slightly smaller than that of experiment.

Charge Transport in Functionalized Octopus-Shaped Multi-Walled Carbon Nanotube/Graphene Hybrids: Implications for Extremely Stretchable Conductors

“…The higher φ gc,sim than φ gc can be related to the numerous simplifying assumptions implemented in the current simulation, such as ignoring the flexibility of graphenes or the length distribution of MWCNTs. 67,68 However, the acquired results for φ gc,sim of the composites of monofiller and physically mixed fillers are comparable with other simulation studies. 66 It must be emphasized that since MWCNTs and graphenes in all model systems are uniformly dispersed, the lower φ gc,sim of HG than G is a purely geometrical effect.…”

Advances in Monte Carlo Method for Simulating the Electrical Percolation Behavior of Conductive Polymer Composites with a Carbon-Based Filling

“… ( a ) Schematic diagrams of the disk model, square model, and folded plate model of graphene; ( b ) model predictions and experimental percolation threshold results [ 111 ]; ( c – f ) effective conductivity versus volume fraction for different parameters; ( c ) tunneling distance dc; ( d ) interface thickness; ( e ) polymer barrier; ( f ) graphene thickness [ 113 ]. …”

“…The rectangular plate and the folded plate Presently, most of the conductive material models in the research are generated by the "rand" function, but there exists the problem of the uneven probability distribution of the model orientation, which affects the position and normal vector of the conductive material model. Liu et al [111] proposed the "uniform_real_distribution" function in C++ to generate the decimals uniformly distributed between 0 and 1, thus obtaining uniform polar and azimuthal angles for the graphene model. Thus, uniform polar and azimuthal angles are obtained for the graphene model, and the 3D Monte Carlo model of the graphene filled polymer is constructed on the basis of this function.…”