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    A morphological investigation of conductive networks in polymers loaded with carbon nanotubes

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    Type
    Article
    Authors
    Lubineau, Gilles cc
    Mora Cordova, Angel cc
    Han, Fei cc
    Odeh, I.N.
    Yaldiz, R.
    KAUST Department
    Composite and Heterogeneous Material Analysis and Simulation Laboratory (COHMAS)
    Mechanical Engineering Program
    Physical Science and Engineering (PSE) Division
    Date
    2017-01-13
    Online Publication Date
    2017-01-13
    Print Publication Date
    2017-04
    Permanent link to this record
    http://hdl.handle.net/10754/622802
    
    Metadata
    Show full item record
    Abstract
    Loading polymers with conductive nanoparticles, such as carbon nanotubes, is a popular approach toward improving their electrical properties. Resultant materials are typically described by the weight or volume fractions of their nanoparticles. Because these conductive particles are only capable of charge transfer over a very short range, most do not interact with the percolated paths nor do they participate to the electrical transfer. Understanding how these particles are arranged is necessary to increase their efficiency. It is of special interest to understand how these particles participate in creating percolated clusters, either in a specific or in all directions, and non-percolated clusters. For this, we present a computational modeling strategy based on a full morphological analysis of a network to systematically analyse conductive networks and show how particles are arranged. This study provides useful information for designing these types of materials and examples suitable for characterizing important features, such as representative volume element, the role of nanotube tortuosity and the role of tunneling cutoff distance.
    Citation
    Lubineau G, Mora A, Han F, Odeh IN, Yaldiz R (2017) A morphological investigation of conductive networks in polymers loaded with carbon nanotubes. Computational Materials Science 130: 21–38. Available: http://dx.doi.org/10.1016/j.commatsci.2016.12.041.
    Sponsors
    We thank SABIC for providing funds for this research. In particular, we gratefully acknowledge research support from Dr. Amit Tevtia (SABIC CRD Saudi Arabia). This research was also supported by funding from King Abdullah University of Science and Technology (KAUST).
    Publisher
    Elsevier BV
    Journal
    Computational Materials Science
    DOI
    10.1016/j.commatsci.2016.12.041
    Additional Links
    http://www.sciencedirect.com/science/article/pii/S0927025617300022
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.commatsci.2016.12.041
    Scopus Count
    Collections
    Articles; Physical Science and Engineering (PSE) Division; Mechanical Engineering Program

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