4.6 Article

Analyzing conducting rod networks using centrality

Journal

ELECTROCHIMICA ACTA
Volume 370, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.electacta.2021.137725

Keywords

Network; Centrality; Nanowire; Conducting rod; Conductivity

Funding

  1. National Research Foundation of Korea (NRF) - Korea government (MSIT) [NRF-2018R1A5A1024127, NRF-2020R1A2C2008141]

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Transparent conductive films made of metallic nanowires have complex microstructures composed of nanoscale conducting rods, which determine the electrical performance of the film. A network model was created using a multi-nodal representation and converted into an equivalent circuit using Laplacian eigenmap. Centrality concepts such as betweenness centrality, closeness centrality, and degree centrality were used to extract structural information and correlate with the conductivity of the network.
Recently, transparent conductive films made of metallic nanowires have been closely studied owing to their excellent optoelectric and mechanical performance. Microstructures inside the films are made up of intricate networks composed of nanoscale conducting rods, and the electrical performance of the film is determined by these structures. Therefore, it has become necessary to quantify their macroand/or micro-structural information using reasonable indicators, which could be used as metrics for optimizing film performance. In this study, a network was modeled using a multi-nodal representation and was converted into an equivalent circuit using the Laplacian eigenmap. Using the Laplacian eigenmap, internal and junction resistances can be clearly visualized, the main backbone distinguished from dangling loops, and the importance of nodes investigated. To extract structural information, we applied the concept of centrality, where betweenness centrality (beta), closeness centrality (gamma), and degree centrality (delta) were considered. We also introduced representative centralities for a given network, which not only correlated with the conductivity of the network but can also be used as a quantitative indicator. (C) 2021 Elsevier Ltd. All rights reserved.

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