Ultra-High Sensitivity Anisotropic Piezoelectric Sensors for Structural Health Monitoring and Robotic Perception

锆钛酸铅 结构健康监测 压电 材料科学 灵敏度(控制系统) 压电传感器 声学 计算机科学 电子工程 光电子学 工程类 复合材料 电介质 物理 铁电性
作者
Hao Yin,Yanting Li,Zhiying Tian,Qichao Li,Chenhui Jiang,Enfu Liang,Yiping Guo
出处
期刊:Nano-micro Letters [Springer Science+Business Media]
卷期号:17 (1)
标识
DOI:10.1007/s40820-024-01539-6
摘要

Monitoring minuscule mechanical signals, both in magnitude and direction, is imperative in many application scenarios, e.g., structural health monitoring and robotic sensing systems. However, the piezoelectric sensor struggles to satisfy the requirements for directional recognition due to the limited piezoelectric coefficient matrix, and achieving sensitivity for detecting micrometer-scale deformations is also challenging. Herein, we develop a vector sensor composed of lead zirconate titanate-electronic grade glass fiber composite filaments with oriented arrangement, capable of detecting minute anisotropic deformations. The as-prepared vector sensor can identify the deformation directions even when subjected to an unprecedented nominal strain of 0.06%, thereby enabling its utility in accurately discerning the 5 μm-height wrinkles in thin films and in monitoring human pulse waves. The ultra-high sensitivity is attributed to the formation of porous ferroelectret and the efficient load transfer efficiency of continuous lead zirconate titanate phase. Additionally, when integrated with machine learning techniques, the sensor's capability to recognize multi-signals enables it to differentiate between 10 types of fine textures with 100% accuracy. The structural design in piezoelectric devices enables a more comprehensive perception of mechanical stimuli, offering a novel perspective for enhancing recognition accuracy.
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