Dynamic Na <sup>+</sup> Bridges: A 3D Printing Strategy for Hydrogels With High Strength, Low Hysteresis, Strong Adhesion, and Self‐Healing
Mengyao Chen, Wenjing Qin, Yanli Wang, Hanlin Zhai, Changshun Gu, Xiangchuan Zhao, Ying Bi, Yixin Xu, Shengrong Li, Shu Hu, Xingyue Zhang, Xiaoye Ma, Shougen Yin
- Year
- 2025
- Citations
- 2
Abstract
Abstract The synergistic optimization of high strength, strong adhesion, high conductivity, and rapid self‐healing in hydrogels faces fundamental challenges arising from conflicting mechanisms. Herein, a 3D‐printed, ionically conductive interpenetrating double‐network hydrogel based on poly (acrylic acid) (PAAc) is developed via the innovative introduction of dynamic Na⁺ bridges. This molecular design enables a unique dual mechanism: the Na⁺ ions not only form reversible ionic bonds that accelerate chain diffusion through bond rupture‐recombination but also create an electrostatic shielding effect in the covalent network, which promotes chain extension to improve mechanical strength without sacrificing dynamic properties. Furthermore, Na⁺ ions regulate bound/free water states and reduces energy dissipation during topological rearrangement. These synergistic mechanisms collectively enable the hydrogel to overcome conventional performance trade‐offs. The resulting material concurrently enhances mechanical properties (300 kPa tensile, 1.2 MPa compressive strength), adhesion (160 kPa), and self‐healing (>90% recovery in 1 h). Biomimetic devices such as an underwater octopus‐tentacle gripper, biomimetic crawling suckers, and pressure sensors are fabricated. By integrating hydrogels with 1D convolutional neural network algorithms, a real‐time motion behavior recognition system is further developed. The multi‐property cooperative design strategy offers a new pathway for the application of intelligent hydrogel materials in soft robotics and flexible electronics.
Keywords
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