Molecular dynamics simulation insight into topological structure dependence of self-healing polymer nanocomposites

Abstract

Polymer nanocomposites (PNCs), which exhibit excellent mechanical properties through the incorporation of fillers into polymers, have been extensively studied to achieve enhanced self-healing capability for their next-generation development. However, there is still a lack of investigation into the influence of the topological structures of nanoparticles (NPs) on the self-healing capability of PNCs. In this study, we utilized coarse-grained molecular dynamics simulations (CGMDs) to construct a series of PNC systems composed of NPs with different topological structures, including Linear, Ring, and Cross topologies. We employed non-bonding interaction potentials to examine the interactions between the polymer and NPs, and varied the parameters to simulate different functional groups. Our results indicate that the stress–strain curves and the rate of performance loss validate that the Linear structure is the optimal topology for mechanical reinforcement and self-healing properties. By analyzing the stress heat map during stretching, we observed that the Linear structure NPs experience significant stress, allowing the matrix chains to dominate in small recoverable deformations during stretching. It can be speculated that NPs oriented in the direction of extrusion are more effective than others in enhancing performance. Overall, this work provides valuable theoretical guidance and a novel strategy for designing and manipulating high-performance, self-healing PNCs.