TY - JOUR
T1 - A morphological investigation of conductive networks in polymers loaded with carbon nanotubes
AU - Lubineau, Gilles
AU - Mora Cordova, Angel
AU - Han, Fei
AU - Odeh, I.N.
AU - Yaldiz, R.
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: 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).
PY - 2017/1/13
Y1 - 2017/1/13
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/622802
UR - http://www.sciencedirect.com/science/article/pii/S0927025617300022
UR - http://www.scopus.com/inward/record.url?scp=85009230396&partnerID=8YFLogxK
U2 - 10.1016/j.commatsci.2016.12.041
DO - 10.1016/j.commatsci.2016.12.041
M3 - Article
SN - 0927-0256
VL - 130
SP - 21
EP - 38
JO - Computational Materials Science
JF - Computational Materials Science
ER -