Abstract
The size of real nanoparticles (NPs) is polydisperse which can influence the electrical property of polymer nanocomposites (PNCs). Here, we explored the percolated network of mixed NPs with different sizes (small NPs and big NPs) by adopting a molecular dynamics simulation. The simulated results reveal that the big NPs are adverse to building the percolated network compared to the small NPs. Thus, the percolation threshold becomes higher along with increasing the mixing ratio, which denotes the concentration ratio of big NPs to the total NPs. For a better understanding of it, the dispersion state and the number and the size of clusters are employed to analyze the percolated network, which can explain the percolation threshold well. Furthermore, by adopting the Sun’s theory (Macromolecules, 2009, 42, 459–463), small and big NPs exhibit a weak antagonistic effect in the simulation if their total concentration is fixed. On the one hand, the number of small NPs is larger than that of big NPs at the same concentration. In addition, one big NP can connect to more others than one small NP. These two contrast effects are responsible for it. Interestingly, the shear flow leads to more contact aggregation structure of NPs which is beneficial to build the new percolated networks. Especially, the big NPs play a more important role in forming the percolated network than small NPs. Consequently, the percolation threshold is reduced at a higher shear rate. In total, our research work provides a further understanding of how the mixed NPs with different sizes form the percolated network in polymer matrix.
Highlights
Conductive polymer nanocomposites (PNCs) are consistent with the polymer matrix and conductive particles (NPs) (graphene, carbon nanotube (CNT), carbon black (CB)), which have been applied in many fields [1,2]
The percolation threshold φc is defined as the volume fraction of NPs at Λ = 0.5, which is calculated by fitting the tration ratio of big NPs to the total NPs
A molecular dynamics simulation is employed to explore the formation of percolated networks of mixed nanoparticles (NPs) with different sizes in polymer nanocomposites (PNCs)
Summary
Conductive polymer nanocomposites (PNCs) are consistent with the polymer matrix and conductive particles (NPs) (graphene, carbon nanotube (CNT), carbon black (CB)), which have been applied in many fields (for example the electromagnetic interference shielding, sensor and conductors) [1,2]. The concentration, the dispersion state of the conductive NPs as well as their shape will influence the distribution state of NPs, which indirectly affect the percolated network. It is proved that the high concentration of NPs is very necessary to build the percolated network, but it will damage the flexibility, elasticity and processing properties, which is necessary to lower the percolation threshold. There are lots of works on improving the electrical conductivity of PNCs by tuning various experimental parameters. The NP surface is modified to improve their miscibility with chains which can reduce the percolation threshold [4]
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