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Using a Novel Approach to Estimate Packing Density and Related Electrical Resistance in Multiwall Carbon Nanotube Networks

In this work, we use contrast image processing to estimate the concentration of multi-wall carbon nanotubes (MWCNT) in a given network. The fractal dimension factor (D) of the CNT network that provides an estimate of its geometrical complexity, is determined and correlated to network resistance. Six...

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Autores principales: Philipose, Usha, Jiang, Yan, Farmer, Gavin, Howard, Chris, Harcrow, Michael, Littler, Chris, Lopes, Vincent, Syllaios, Athanasios J., Sood, Ashok, Zeller, John W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7759792/
https://www.ncbi.nlm.nih.gov/pubmed/33256198
http://dx.doi.org/10.3390/nano10122350
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author Philipose, Usha
Jiang, Yan
Farmer, Gavin
Howard, Chris
Harcrow, Michael
Littler, Chris
Lopes, Vincent
Syllaios, Athanasios J.
Sood, Ashok
Zeller, John W.
author_facet Philipose, Usha
Jiang, Yan
Farmer, Gavin
Howard, Chris
Harcrow, Michael
Littler, Chris
Lopes, Vincent
Syllaios, Athanasios J.
Sood, Ashok
Zeller, John W.
author_sort Philipose, Usha
collection PubMed
description In this work, we use contrast image processing to estimate the concentration of multi-wall carbon nanotubes (MWCNT) in a given network. The fractal dimension factor (D) of the CNT network that provides an estimate of its geometrical complexity, is determined and correlated to network resistance. Six fabricated devices with different CNT concentrations exhibit D factors ranging from 1.82 to 1.98. The lower D-factor was associated with the highly complex network with a large number of CNTs in it. The less complex network, having the lower density of CNTs had the highest D factor of approximately 2, which is the characteristic value for a two-dimensional network. The electrical resistance of the thin MWCNT network was found to scale with the areal mass density of MWCNTs by a power law, with a percolation exponent of 1.42 and a percolation threshold of 0.12 [Formula: see text] g/cm [Formula: see text]. The sheet resistance of the films with a high concentration of MWCNTs was about six orders of magnitude lower than that of less dense networks; an effect attributed to an increase in the number of CNT–CNT contacts, enabling more efficient electron transfer. The dependence of the resistance on the areal density of CNTs in the network and on CNT network complexity was analyzed to validate a two-dimension percolation behavior.
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spelling pubmed-77597922020-12-26 Using a Novel Approach to Estimate Packing Density and Related Electrical Resistance in Multiwall Carbon Nanotube Networks Philipose, Usha Jiang, Yan Farmer, Gavin Howard, Chris Harcrow, Michael Littler, Chris Lopes, Vincent Syllaios, Athanasios J. Sood, Ashok Zeller, John W. Nanomaterials (Basel) Article In this work, we use contrast image processing to estimate the concentration of multi-wall carbon nanotubes (MWCNT) in a given network. The fractal dimension factor (D) of the CNT network that provides an estimate of its geometrical complexity, is determined and correlated to network resistance. Six fabricated devices with different CNT concentrations exhibit D factors ranging from 1.82 to 1.98. The lower D-factor was associated with the highly complex network with a large number of CNTs in it. The less complex network, having the lower density of CNTs had the highest D factor of approximately 2, which is the characteristic value for a two-dimensional network. The electrical resistance of the thin MWCNT network was found to scale with the areal mass density of MWCNTs by a power law, with a percolation exponent of 1.42 and a percolation threshold of 0.12 [Formula: see text] g/cm [Formula: see text]. The sheet resistance of the films with a high concentration of MWCNTs was about six orders of magnitude lower than that of less dense networks; an effect attributed to an increase in the number of CNT–CNT contacts, enabling more efficient electron transfer. The dependence of the resistance on the areal density of CNTs in the network and on CNT network complexity was analyzed to validate a two-dimension percolation behavior. MDPI 2020-11-26 /pmc/articles/PMC7759792/ /pubmed/33256198 http://dx.doi.org/10.3390/nano10122350 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Philipose, Usha
Jiang, Yan
Farmer, Gavin
Howard, Chris
Harcrow, Michael
Littler, Chris
Lopes, Vincent
Syllaios, Athanasios J.
Sood, Ashok
Zeller, John W.
Using a Novel Approach to Estimate Packing Density and Related Electrical Resistance in Multiwall Carbon Nanotube Networks
title Using a Novel Approach to Estimate Packing Density and Related Electrical Resistance in Multiwall Carbon Nanotube Networks
title_full Using a Novel Approach to Estimate Packing Density and Related Electrical Resistance in Multiwall Carbon Nanotube Networks
title_fullStr Using a Novel Approach to Estimate Packing Density and Related Electrical Resistance in Multiwall Carbon Nanotube Networks
title_full_unstemmed Using a Novel Approach to Estimate Packing Density and Related Electrical Resistance in Multiwall Carbon Nanotube Networks
title_short Using a Novel Approach to Estimate Packing Density and Related Electrical Resistance in Multiwall Carbon Nanotube Networks
title_sort using a novel approach to estimate packing density and related electrical resistance in multiwall carbon nanotube networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7759792/
https://www.ncbi.nlm.nih.gov/pubmed/33256198
http://dx.doi.org/10.3390/nano10122350
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