材料科学
标度系数
电阻式触摸屏
复合材料
各向异性
复合数
模数
拉伤
应变计
灵敏度(控制系统)
纳米复合材料
硅酮
光学
电子工程
计算机科学
制作
医学
替代医学
物理
病理
内科学
计算机视觉
工程类
作者
Ting Fan,Yuanyuan Zhang,Shan-Shan Xue,Yuan‐Qing Li,Pei Huang,Ning Hu,Kin Liao,Shao‐Yun Fu
标识
DOI:10.1016/j.compscitech.2022.109565
摘要
Anisotropic strain sensors are crucial to accurately detecting the complex strain states in wearable devices and robotics. Large directional sensitivity differences are the key for strain sensors to differentiate loading directions. Here, an ultrasensitive anisotropic strain sensor consisting of orthogonal heterogeneous piezo-resistive composite (HePC) and homogenous piezo-resistive composite (HoPC) is demonstrated for loading direction perception. Benefited by a unique stiff-soft-stiff segment structure design, the HePCs with ultrahigh strain sensitivity were fabricated with carbon black (CB)/silicone nanocomposite with a low Young's modulus as the soft segment (SoS) and carbon-fiber-reinforced CB/silicone nanocomposite with a high Young's modulus as the stiff segment (StS). The HePC with a length ratio (LStS/LSoS) of 14:1 offers an average gauge factor of 70 (ε < 1%), which is increased more than 60 times than that of HoPC, due to the strain concentration effect in the SoS of HePC. Moreover, the anisotropic strain sensor fabricated demonstrates significant directional sensitivity differences due to the heterogeneous structure, and their relative resistance changes (RCR) vary considerably from positive to negative upon the change of loading directions. This makes the sensor highly effective to distinguish strain magnitude and direction simultaneously, and succeeding in monitoring complex human body gestures. Meanwhile, the relation between the loading direction and the measured parameter K (RCR in X-direction over that in Y-direction) is proposed to predict the loading angle. Considering its ultrahigh sensitivity and loading-direction-perception capability, the anisotropic strain sensor with the heterogeneous structure of stiff-soft-stiff segments is promising in wearable devices, robotic systems, artificial intelligence, etc.
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