Tuning mechanical behavior of polymer materials via multi-arm crosslinked network architectures

Crosslinked polymer materials provide tremendous opportunities for delivering unique material properties for a wide variety of applications such as shape-memory and self-healing materials, aerospace materials, and biomedical systems. Most crosslinked polymer networks investigated to date are designed based on covalent or noncovalent crosslinkers that include two-ended connections to the backbone polymer base. In this paper, we investigate the topic of multi-arm crosslinking of polymer materials using a computational platform. We take advantage of molecular dynamics simulations and graph theory to define computational models that describe potential architectures for multi-arm crosslinked polymer networks. We also discuss feasible experimental routes for implementation of these approaches. We investigate how the polymer network architecture affects the mechanical and self-healing behavior of the material. Our results show that the angular stiffness of multi-arm crosslinkers can be adjusted to control the mechanical strength of the overall polymer network. Additionally, using graph theory, we find that the complex connections that exist between the crosslinkers and the backbone polymer chains define the overall connectivity of the polymer network, which in turn dictates the mechanical behavior of the material. Furthermore, we find that increasing the number of crosslinking arms may improve the self-healing behavior, but it can reduce the overall mechanical strength of the polymer network. The findings of this paper can motivate future experimental and data-driven studies to realize more sophisticated crosslinked polymer materials with a large number of degrees of freedom to deliver a variety of tunable properties.