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Issue 19, 2018
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Eliminating common biases in modelling the electrical conductivity of carbon nanotube–polymer nanocomposites

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Abstract

Modelling carbon nanotube–polymer nanocomposites to predict their electrical conductivity demands high computational power. Past research has led to the assumption that conductive networks follow a periodic pattern; however, the impact of the underlying biases had never been investigated. This work provides insights into evaluating such biases and eliminating them to improve simulation accuracy.

Graphical abstract: Eliminating common biases in modelling the electrical conductivity of carbon nanotube–polymer nanocomposites

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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., 2018,20, 13118-13121
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    Eliminating common biases in modelling the electrical conductivity of carbon nanotube–polymer nanocomposites

    L. T. Hoang, S. N. Leung and Z. H. Zhu, Phys. Chem. Chem. Phys., 2018, 20, 13118
    DOI: 10.1039/C8CP01715H

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