Mechano-statistical Network Models of Electrostatic Hydrogels: Connecting Network Topology and Gel Elasticity

Polyelectrolyte complex (PEC) hydrogels, which are formed by mixing oppositely charged block polyelectrolytes in aqueous media, have become attractive candidates as 3D printable inks and injectable wet adhesives owing to their highly tunable rheological properties. Their rheological behavior is known to be largely dictated by their self-assembled network structures. Yet, a predictive modeling approach that relates their network topology with their elastic properties remains elusive. In this contribution, we employ mechano-statistical transient network models, originally developed for hydrophobically associating triblock copolymers, to model the shear rheological properties of PEC hydrogels, which allows for predicting the concentration-dependent elasticity of PEC networks. By contrasting the theoretical and experimental results, we seek a basic understanding of the variation in network topologies and their role in dictating the hydrogels' elastic properties.