Robust Three‐Component Elastomer–Particle–Fiber Composites with Tunable Properties for Soft Robotics

A. M. Nasab, Siavash Sharifi, Shuai Chen, Yang Jiao, W. Shan
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引用次数: 15

Abstract

Materials with tunable properties, especially dynamically tunable stiffness, have been of great interest for the field of soft robotics. Herein, a novel design concept of robust three‐component elastomer–particle–fiber composite system with tunable mechanical stiffness and electrical conductivity is introduced. These smart materials are capable of changing their mechanical stiffness rapidly and reversibly when powered with electrical current. One implementation of the composite system demonstrated here is composed of a polydimethylsiloxane (PDMS) matrix, Field's metal (FM) particles, and nickel‐coated carbon fibers (NCCF). It is demonstrated that the mechanical stiffness and the electrical conductivity of the composite are highly tunable and dependent on the volume fraction of the three components and the temperature, and can be reasonably estimated using effective medium theory. Due to its superior electrical conductivity, Joule heating can be used as the activation mechanism to realize ≈20× mechanical stiffness changes in seconds. The performance of the composites is thermally and mechanically robust. The shape memory effect of these composites is also demonstrated. The combination of tunable mechanical and electrical properties makes these composites promising candidates for sensing and actuation applications for soft robotics.
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具有柔性机器人可调性能的三组分弹性-颗粒-纤维复合材料
具有可调性能的材料,特别是具有动态可调刚度的材料,一直是软机器人领域的研究热点。本文提出了一种具有机械刚度和导电性可调的弹性-颗粒-纤维三组分复合材料的鲁棒设计理念。这些智能材料能够在电流驱动下快速可逆地改变其机械刚度。本文演示的一种复合系统由聚二甲基硅氧烷(PDMS)基体、菲尔德金属(FM)颗粒和镍涂层碳纤维(NCCF)组成。结果表明,复合材料的机械刚度和电导率是高度可调的,与三组分的体积分数和温度有关,可以用有效介质理论合理地估计。由于其优越的导电性,焦耳加热可以作为激活机制,在秒内实现≈20倍的机械刚度变化。复合材料的性能是热和机械稳健。同时还证明了复合材料的形状记忆效应。可调的机械和电气性能使这些复合材料成为软机器人传感和驱动应用的有希望的候选者。
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