Stretching Training of Microgel‐Reinforced Composite Hydrogel for Tunable Strain‐Stiffening Property

IF 11.8 2区 材料科学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Small Pub Date : 2026-10-18 DOI:10.1002/smll.76284
Longhui Li, Liwei Wu, Guodong Zhang, Lan Liu, Yuke Zhang, Jie Zhang, Lingling Zhang, Jie Ju, Xi Yao
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Abstract

Achieving tunable strain‐stiffening in tough hydrogels via muscle‐mimicking training remains a key challenge for nonlinear biomimetic mechanics. Microgel‐reinforced composite hydrogels (MR‐gels), combine rigid polyelectrolyte microspheres with a soft polyacrylamide matrix, offering an ideal platform for programming strain‐stiffening behavior via hierarchical microsphere fracture. Here, we report that physical training controlling stretching amplitude and number of repetitions enables stable and tunable strain‐stiffening in MR‐gels. Unlike conventional expectations, a single stretch is insufficient, training equilibrium requires approximately 300 cycles. The resulting MR‐gel exhibit stable and broadly tunable soft‐to‐stiff transition (0.4–3.1), strain‐stiffening capacity (3.1–17.8), and modulus of the soft (240 to 40 kPa) and stiff (814 to 713 kPa) regimes, matching the nonlinear mechanics of diverse biological mechanicals. Mechanistically, the training mode achieves tunable strain‐stiffening by controlling the degree of microgel fracture and entangled polymer chain sliding. At equilibrium, fragmented microgels form an interconnected string‐like network via topological entanglements and covalent crosslinks, raising the fatigue threshold from 689.6 to 1269.8 J/m 2 . Furthermore, the trained MR‐gel enables full envelopment of a high‐speed falling iron ball for effective deceleration and superior impact cushioning. This work establishes a versatile strategy for programming mechanical behavior in soft materials, with broad implications for soft robotics, wearable electronics, and biomedicine.
微凝胶增强复合水凝胶应变强化性能可调的拉伸训练
通过肌肉模拟训练在坚韧的水凝胶中实现可调的应变硬化仍然是非线性仿生力学的关键挑战。微凝胶增强复合水凝胶(MR凝胶)结合了刚性的聚电解质微球和柔软的聚丙烯酰胺基质,为通过分层微球断裂编程应变硬化行为提供了理想的平台。在这里,我们报告了控制拉伸幅度和重复次数的物理训练可以在MR凝胶中实现稳定和可调的应变硬化。与传统的期望不同,单次拉伸是不够的,训练平衡需要大约300次循环。所得到的MR凝胶表现出稳定和广泛可调的软-硬过渡(0.4-3.1),应变-硬化能力(3.1-17.8),以及软(240至40 kPa)和硬(814至713 kPa)的模量,与各种生物力学的非线性力学相匹配。在机械上,训练模式通过控制微凝胶断裂和纠缠聚合物链滑动的程度来实现可调的应变硬化。在平衡状态下,破碎的微凝胶通过拓扑纠缠和共价交联形成相互连接的弦状网络,将疲劳阈值从689.6提高到1269.8 J/ m2。此外,经过训练的MR凝胶能够完全包裹高速下落的铁球,从而实现有效的减速和卓越的冲击缓冲。这项工作为软材料的机械行为编程建立了一种通用策略,对软机器人、可穿戴电子产品和生物医学具有广泛的意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Small
Small 工程技术-材料科学:综合
CiteScore
17.70
自引率
3.80%
发文量
1830
审稿时长
2.1 months
期刊介绍: Small serves as an exceptional platform for both experimental and theoretical studies in fundamental and applied interdisciplinary research at the nano- and microscale. The journal offers a compelling mix of peer-reviewed Research Articles, Reviews, Perspectives, and Comments. With a remarkable 2022 Journal Impact Factor of 13.3 (Journal Citation Reports from Clarivate Analytics, 2023), Small remains among the top multidisciplinary journals, covering a wide range of topics at the interface of materials science, chemistry, physics, engineering, medicine, and biology. Small's readership includes biochemists, biologists, biomedical scientists, chemists, engineers, information technologists, materials scientists, physicists, and theoreticians alike.
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