A multiscale model for osmotic-driven dual-network shape memory polymer composites with inhomogeneous structure

Inspired by biological osmoregulation, we propose a multiscale model for osmotic-driven shape memory polymers (SMPs). This framework describes the shape memory behavior of inhomogeneous structures governed by a synergistic “permanent-reversible” dual-network mechanism. This study incorporates a synergistic process from a diffusion-induced swelling of permanent networks and an association-dissociation of reversible networks, to investigate the role of the dualnetwork in the formation of inhomogeneous structure and its osmotic-driven shape memory behaviors. A multiscale framework that integrates thermodynamics with statistics is established to quantify the osmotic pressure-induced shape recovery behaviors of SMPs, in which the network parameters and structural features regulate the thermodynamic swelling and chemical association/dissociation kinetics. Experimental validations of 1D artificial muscle fibers, 2D hydrogel films, and 3D bilayer composite actuators demonstrate an excellent agreement with the analytical results obtained from the proposed dual-network model. This work provides a physical framework for the design of SMPs in bioinspired robotics and biomedical systems.