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1.
Nanoscale ; 7(30): 13011-6, 2015 Aug 14.
Article in English | MEDLINE | ID: mdl-26169222

ABSTRACT

In this work, we introduce a combined experimental and computational approach to describe the conductivity of metallic nanowire networks. Due to their highly disordered nature, these materials are typically described by simplified models in which network junctions control the overall conductivity. Here, we introduce a combined experimental and simulation approach that involves a wire-by-wire junction-by-junction simulation of an actual network. Rather than dealing with computer-generated networks, we use a computational approach that captures the precise spatial distribution of wires from an SEM analysis of a real network. In this way, we fully account for all geometric aspects of the network, i.e. for the properties of the junctions and wire segments. Our model predicts characteristic junction resistances that are smaller than those found by earlier simplified models. The model outputs characteristic values that depend on the detailed connectivity of the network, which can be used to compare the performance of different networks and to predict the optimum performance of any network and its scope for improvement.

2.
ACS Nano ; 8(9): 9542-9, 2014 Sep 23.
Article in English | MEDLINE | ID: mdl-25153920

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 nonconducting. Nonelectrical activation methods can enhance conductivity but destroy the memristive behavior of the junctions that comprise the network. We show through both simulation and experiment that electrical stimulation, microstructured electrode geometry, and feature scaling can all be used to manipulate the connectivity and thus electrical conductivity of networks of silver nanowires with a nonconducting polymer coating. More generally, these results describe a strategy to integrate nanomaterials into controllable, adaptive macroscale materials.

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