Hydrogel-Based Network\nMetamaterials with Biological\nTissue-like Poisson’s Ratio Behavior and Stress Response

Soft network metamaterials are widely used in fields\nsuch as flexible\nelectronics, tissue engineering, and biomedicine due to their superior\nproperties including low density, high stretchability, and high breathability.\nHowever, the prediction and customization of the nonlinear mechanical\nbehavior of soft network metamaterials remain a challenging problem.\nIn this study, a family of hydrogel-based network metamaterials with\nbiological tissue-like mechanical properties are developed based on\na machine learning-driven optimization design method. Numerical and\nexperimental results explain the relationship between the mechanical\nproperties of the designed metamaterials and their microstructural\nfeatures and stretching ratios. The results indicate that the hydrogel-based\nnetwork metamaterials exhibit J-shaped stress-deformation (σ–λ)\nbehavior similar to biological tissues. This phenomenon arises from\nthe transition of the deformation mode of metamaterials from bending-dominated\nto stretching-dominated as the stretching ratio increases. Based on\nthe proposed design scheme, the Poisson’s ratio of metamaterials\ncan be adjusted within a remarkably wide range of −1.06 to\n1.34. Furthermore, through optimizing the design parameters of the\nmetamaterial, the customization of network metamaterials with biological\ntissue-like zero Poisson’s ratio behavior and stress response\nis achieved. The potential applications of hydrogel-based network\nmetamaterials are demonstrated through artificial skin and LED integrated\ndevice. This research offers novel insights into predicting, designing,\nand fabricating the mechanical behavior of soft network metamaterials.