From percolating to dense random stick networks: Conductivity model investigation

Žeželj, Milan; Stanković, Igor

doi:10.1103/physrevb.86.134202

Cited by 83 publications

(65 citation statements)

References 36 publications

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“…Furthermore, we visualize these changes in the network, both experimentally using passive voltage contrast electron microscopy techniques, 20 and in simulations of nanowires as line segments connected in a two-dimensional plane by junctions that can either be capacitive before activation or resistive after activation. 9,19,[21][22][23][24] We compare devices of different electrode geometry: two flat electrodes, one serrated and one flat electrode, two serrated electrodes, and one pointed and one flat electrode. By extending our previously developed model of connectivity in these networks, 2 we can predict the effects of microstructuring electrodes on the activation voltage and sheet resistance of networks, confirmed here through experimental data.…”

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confidence: 99%

Effective Electrode Length Enhances Electrical Activation of Nanowire Networks: Experiment and Simulation

et al. 2014

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ABSTRACT. Networks comprised of randomly oriented overlapping nanowires offer the possibility of simple fabrication on a variety of substrates, in contrast with the precise placement required for devices with single or aligned nanowires. Metal nanowires typically have a coating of surfactant or oxide that prevents aggregation, but also prevents electrical connection.Prohibitively high voltages can be required to electrically activate nanowire networks, and even after activation many nanowire junctions remain non-conducting. Non-electrical activation methods can enhance conductivity but destroy the memristive behavior of the junctions that

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confidence: 99%

Effective Electrode Length Enhances Electrical Activation of Nanowire Networks: Experiment and Simulation

et al. 2014

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“…The effectiveness of each contact depends on the potential difference between the two fibres and ݇ is a factor which allows for this effect. By equating the coefficients in our result with those of Žeželj and Stanković [13] for a uniform 2D fibre angular distribution we find ݇ = 0.1696. We determine the number of contacts per fibre in Section IV.C.…”

Section: B Effect Of Contact Conductancementioning

confidence: 84%

“…Fig. 7 compares the results of the MCM with the theory developed here, and the expression given by Žeželj and Stanković [13] for a 2D isotropic sheet with infinite contact conductance. In Figs.…”

Section: A Generation Of the Monte Carlo Modelmentioning

confidence: 87%

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Shielding Effectiveness and Sheet Conductance of Nonwoven Carbon-Fiber Sheets

Dawson

Austin²,

Flintoft

et al. 2017

IEEE Trans. Electromagn. Compat.

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Abstract-Nonwoven carbon-fibre sheets are often used to form a conductive layer in composite materials for electromagnetic shielding and other purposes. While a large amount of research has considered the properties of similar idealised materials near the percolation threshold, little has been done to provide validated analytic models suitable for materials of practical use for electromagnetic shielding. Since numerical models consume considerable computer resource, and do not provide the insight which enables improved material design, an analytic model is of great utility for materials development. This paper introduces a new theoretical model for the sheet conductance of nonwoven carbon-fibre sheets built on the theory of percolation for two-dimensional conducting stick networks. The model accounts for the effects of sample thickness, fibre angle distribution and contact conductance on the sheet conductance. The theory shows good agreement with MonteCarlo simulations and measurements of real materials in the supercritical percolation regime where the dimensionless areal concentration of fibres exceeds about 50. The theoretical model allows the rapid prediction of material shielding performance from a limited number of manufacturing parameters.

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“…where n c is the percolation threshold and t is the universal conductivity exponent (equal to 1.29) [17], [18]. Eq.…”

Section: Electro-optical Propertiesmentioning

confidence: 99%

Silver nanowire networks: Physical properties and potential integration in solar cells

Langley

Giusti

Lagrange

et al. 2014

Solar Energy Materials and Solar Cells

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From percolating to dense random stick networks: Conductivity model investigation

Cited by 83 publications

References 36 publications

Effective Electrode Length Enhances Electrical Activation of Nanowire Networks: Experiment and Simulation

Effective Electrode Length Enhances Electrical Activation of Nanowire Networks: Experiment and Simulation

Shielding Effectiveness and Sheet Conductance of Nonwoven Carbon-Fiber Sheets

Silver nanowire networks: Physical properties and potential integration in solar cells

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