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Preparation of Hydroxy-PAAm Hydrogels for Decoupling the Effects of Mechanotransduction Cues
Published on: August 28, 2014
Low-temperature-induced recombinant Talin assembly into energy-dissipative hydrogels for machine learning-powered
Zhenchun Li1, Rongfeng Ge1, Zhiyuan Zhao1
1Key Laboratory of Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Changchun, 130012, PR China.
Abstract:
Despite significant advances in tough hydrogels, it remains challenging to simultaneously achieve high mechanical properties, low-temperature stability, and multifunctionality required for sports-related wearable sensing applications, particularly when conventional chemical crosslinkers are avoided to preserve dynamic behavior and biocompatibility. Here, we introduce a novel strategy based on bioinspired energy dissipation and low-temperature-guided ordered assembly to construct a dynamic hydrogel network with a biomimetic hierarchical structure. In this system, acrylated recombinant Talin serves as an intelligent unit integrating crosslinking and energy-dissipation functions, efficiently dissipating energy through molecular-scale sacrificial bond mechanisms, while phytic acid simultaneously fulfills multiple roles as a dynamic crosslinker, conductive medium, and antibacterial agent. The resulting hydrogel achieves breakthrough mechanical performance while maintaining high water content: It exhibits a tensile strength of 2.0 MPa, an elongation at break exceeding 2100%, and a toughness of up to 16.9 MJ/m3, along with excellent fatigue and crack resistance. Furthermore, the material integrates multiple functionalities including frost resistance (conductivity of 0.75 S/m at -20 °C), antibacterial activity, and biocompatibility. Building on this, the developed hydrogel sensor enables stable simultaneous monitoring of multi-joint motion and dynamic plantar pressure. A multimodal wearable system, combined with multilayer perceptron and convolutional neural network algorithms, achieves high-precision recognition of motion amplitude and gait phases across various sports such as running, basketball, and badminton, with an optimal accuracy of 98.67%. This work presents a universal strategy for fabricating multifunctional high-performance hydrogels and establishes a robust and technological foundation for next-generation intelligent flexible sensing platforms for sports science and human-machine interaction.
