Effect of the shear field on the conductive percolated network formation in a nanoparticle filled polymer nanocomposites

ABSTRACT

It is very important to improve the electrical conductivity of polymer nanocomposites (PNCs) which can widen their application. In this work, a coarse-grained molecular dynamics simulation is adopted to investigate the effect of the nanoparticle (NP) functionalization on the formation of the conductive network under the quiescent state or under the shear field, which is denoted by the conductive probability. First, the dispersion state of NPs is characterized which varies from the contact aggregation, the relatively uniform dispersion to the local bridging structure via one polymer layer with the increase of the functionalization degree $\alpha$. Corresponding to it, the percolation threshold of PNCs exhibits a continuous decrease with the increase of $\alpha$ under the quiescent state which reflects the high conductive probability. However, the percolation threshold shows a weak increase under the shear field. Thus, the $\alpha$ decides whether the conductive probability increases or decreases under the shear field. The smallest change in the percolation threshold appears at the moderate $\alpha$ which reflects the highest conductive stability. Especially, even though the dispersion state of NPs is different for $\alpha \ge 0.2$, the percolation threshold is similar under the shear field. The connection mode among NPs is considered to determine the formation of the conductive network. In summary, this work can help to understand how the NP functionalization affects the electrical conductivity of PNCs.

KEYWORDS:

• Electrical conductivity
• polymer nanocomposite
• molecular simulation

Acknowledgments

This work is supported from the National Natural Science Foundation of China (51973012, 21704003), National 973 Basic Research Program of China 2015CB654704, the Foundation for Innovative Research Groups of the NSF of China (51521062) and the start-up funding of Beijing University of Chemical Technology for excellent introduced talents (buctrc201710). The authors acknowledge the National Supercomputer Center in Guangzhou, Lvliang and shenzhen.

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