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Eliminating Common Biases in Modelling Electrical Conductivity of Carbon Nanotubes-Polymer Nanocomposites

Abstract

Modelling carbon nanotube-polymer nanocomposites to predict their electrical conductivity demands high computational power. Past research usually assumed the conductive network follow a periodic pattern; however, the impacts of the underlying biases had never been investigated. This work provides insights to evaluate such biases and eliminate them to improve simulation accuracy.

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Publication details

The article was received on 16 Mar 2018, accepted on 12 Apr 2018 and first published on 12 Apr 2018


Article type: Communication
DOI: 10.1039/C8CP01715H
Citation: Phys. Chem. Chem. Phys., 2018, Accepted Manuscript
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    Eliminating Common Biases in Modelling Electrical Conductivity of Carbon Nanotubes-Polymer Nanocomposites

    L. T. Hoang, S. N. Leung and Z. H. Zhu, Phys. Chem. Chem. Phys., 2018, Accepted Manuscript , DOI: 10.1039/C8CP01715H

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