Intrinsic Correlation between Dynamic Phase Separation and Tunable Multishape Memory Effect in Double-Network Hydrogels

Cooling-induced shape memory hydrogels exhibit great potential for biomedical applications, as they effectively minimize the risk of irreversible thermal damage to human tissues. However, due to the complex phase separation occurring within their internal architecture, the current understanding of the modulatory mechanism governing the shape memory behavior of hydrogels remains unclear. In this study, we propose a dynamic phase separation model to elucidate the mechanisms of association and dissociation within the reversibly cross-linked network of double-network hydrogels in the shape memory temperature range. The dual-network structure consists of a permanently cross-linked network for structural stability and a reversibly cross-linked network for shape fixation and recovery. Based on the proposed model, the formation of the reversibly cross-linked network is governed by the activation energy required for the escape of hydrophobic units from solvation cages. Subsequently, by extending the entropy compensation theory, the dissociation probability of the reversibly cross-linked network upon cooling is well characterized. The validity of the proposed model is verified by its successful application in predicting the multishape memory behavior and stress–strain relationship of double-network hydrogels under various thermochemical coupling conditions. This study is expected to provide a practical methodology for understanding the mechanisms of the thermal stiffening behavior and the multishape memory effect (multi-SME) in double-network hydrogels.