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仿生智能软驱动器:具有高强度梯度智能水凝胶的多种可控变形和运动。

Bionic intelligent soft actuators: high-strength gradient intelligent hydrogels with diverse controllable deformations and movements.

机构信息

The Key Laboratory of Bionic Engineering, Ministry of Education, Jilin University, Changchun 130025, China.

School of Mechanical, Aerospace and Civil Engineering, University of Manchester, Manchester, M13 9PL, UK.

出版信息

J Mater Chem B. 2020 Oct 21;8(40):9362-9373. doi: 10.1039/d0tb01927e.

Abstract

A series of novel nanofibrillated cellulose (NFC) reinforced gradient intelligent hydrogels with high response rate, multiple response patterns and diversified self-driven functions were successfully prepared. Based on the effect of the hydroxide radical of NFC on the addition reaction, and on the dehydration synthesis, the variation of NFC significantly regulated the gradient structure of the intelligent hydrogels. In addition to the infiltration property of graphene oxide (GO), reinforcement of NFC enhanced the crosslinking density and Young's modulus, which built a relationship between material characteristics and near infrared laser response rate. Intelligent hydrogel actuators realized bending deformation, curling deformation, switching movements and obstacle avoidance movements. The hydrogels with high Young's modulus exhibited relatively low self-driven rates and efficiency. The self-driven mechanisms of NFC reinforced gradient intelligent hydrogels were revealed effectively by constructing the mathematical relationship curvature variation, bending degree, deformation displacement, material characteristics and incentive intensity. The investigation showed a new path for the combination of mechanical property, intelligent property and functional property of intelligent hydrogels in a bionic soft robot and health engineering.

摘要

成功制备了一系列具有高响应速率、多种响应模式和多样化自驱动功能的新型纳米原纤化纤维素 (NFC) 增强梯度智能水凝胶。基于 NFC 对加成反应的氢氧根离子的影响以及脱水合成,NFC 的变化显著调节了智能水凝胶的梯度结构。除了氧化石墨烯 (GO) 的渗透特性外,NFC 的增强还提高了交联密度和杨氏模量,从而建立了材料特性与近红外激光响应速率之间的关系。智能水凝胶驱动器实现了弯曲变形、卷曲变形、切换运动和避障运动。具有高杨氏模量的水凝胶表现出相对较低的自驱动速率和效率。通过构建曲率变化、弯曲程度、变形位移、材料特性和激励强度之间的数学关系,有效地揭示了 NFC 增强梯度智能水凝胶的自驱动机制。该研究为仿生软体机器人和健康工程中智能水凝胶的机械性能、智能性能和功能性能的结合开辟了一条新途径。

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