2018
DOI: 10.1038/s41598-018-34992-6
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Computational characterization and control of electrical conductivity of nanowire composite network under mechanical deformation

Abstract: Quantitative models to predict the electrical performance of 1-D nanowire (NW) composite networks under external deformation such as bending and patterning are developed by Monte-Carlo based computations, and appropriate solutions are addressed to enhance the tolerance of the sheet resistance (Rs) of the NW networks under the deformation. In addition, several strategies are employed to improve further the robustness of the sheet resistance against the network deformation. In the case of bending, outstanding be… Show more

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Cited by 14 publications
(6 citation statements)
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“…In fact, a 1/s-dependency of the resistance with increasing distance is characteristic for 3D transport in a homogeneous material [51]. For an isotropic 2D system, the increase of the resistance with increasing distance s along the 1D collinear 4 point probe assembly is exactly compensated by lateral spread of the electrons, thus the resistance is not dependent on s. In our case, the doped 6H-SiC(0001) substrate is electrically insulating at these temperatures [50,52], thus the 1/s-dependence must be related to the structure of our intercalated 2D phase and were found for nanowire network structures as well [53,54]. Apparently, by increasing the tip distance, the number of percolated electron paths is overcompensating the 1D contribution.…”
Section: In-situ Surface Transport Measurementssupporting
confidence: 53%
“…In fact, a 1/s-dependency of the resistance with increasing distance is characteristic for 3D transport in a homogeneous material [51]. For an isotropic 2D system, the increase of the resistance with increasing distance s along the 1D collinear 4 point probe assembly is exactly compensated by lateral spread of the electrons, thus the resistance is not dependent on s. In our case, the doped 6H-SiC(0001) substrate is electrically insulating at these temperatures [50,52], thus the 1/s-dependence must be related to the structure of our intercalated 2D phase and were found for nanowire network structures as well [53,54]. Apparently, by increasing the tip distance, the number of percolated electron paths is overcompensating the 1D contribution.…”
Section: In-situ Surface Transport Measurementssupporting
confidence: 53%
“…Specifically, a NW network with a confined geometry and higher density less able to accommodate an applied bending strain by stretching. That is, denser Ag NW networks exhibit an increased resistance compared to those of lower-density networks [49,50,51,52,63,66].…”
Section: Mechano-electric Properties Of Ag Nw Networkmentioning
confidence: 99%
“…Comparative cyclic bending test results as a function of time or cycle number for ( a ) Ag NW networks and Ag NW–RGO hybrid after exposure at 70 °C for 132 h. Reproduced with permission from [66]. Copyright 2016 Royal Society of Chemistry.…”
Section: Figures Scheme and Tablementioning
confidence: 99%
“…Monte Carlo (MC) simulation is another kind of effective method to study GRPCs nanocomposites. Hwang et al [149] used MC simulation to develop a quantitative model predicting the electrical performance of graphene-reinforced one-dimensional composite under bending (as shown in Figure 25). Gbaguidi et al [150] developed a 2D MC percolation network model for studying the electromechanical behaviors of carbon nanotube (CTN)-and GNP-reinforced hybrid nanocomposites.…”
Section: Theoretical Modelingmentioning
confidence: 99%