Bioinspired Ultrasensitive and Stretchable MXene-Based Strain Sensor via Nacre-Mimetic Microscale “Brick-and-Mortar” Architecture

标度系数 材料科学 微尺度化学 耐久性 复合材料 胶凝的 MXenes公司 纳米技术 制作 灰浆 水泥 数学 医学 病理 数学教育 替代医学
作者
Xinlei Shi,Huike Wang,Xueting Xie,Qingwen Xue,Jingyu Zhang,Siqi Kang,Conghui Wang,Jiajie Liang,Yongsheng Chen
出处
期刊:ACS Nano [American Chemical Society]
卷期号:13 (1): 649-659 被引量:381
标识
DOI:10.1021/acsnano.8b07805
摘要

The development of wearable strain sensors with simultaneous large stretchability (strain >55%) and high sensitivity (gauge factor >100) remains a grand challenge to this day. Drawing on inspiration from nature, nacre has demonstrated outstanding mechanical properties, especially combining high strength and toughness, which is due in part to its delicate hierarchical layered architecture with rich interfacial interactions. We demonstrate that strain sensors based on this nacre-mimetic microscale "brick-and-mortar" architecture can simultaneously achieve ultrahigh sensitivity and large stretchability while performing well in linearity, reliability, long-term durability, and monotonicity. The bioinspired sensor demonstrated a gauge factor >200 over a range of working strains up to 83% and achieved a high gauge factor exceeding 8700 in the strain region of 76-83%. This successful combination of high sensitivity and large stretchability is attributed to (1) the microscale hierarchical architecture derived from the amalgamation of 2D titanium carbide (MXene) Ti3C2T x/1D silver nanowire "brick" and poly(dopamine)/Ni2+ "mortar" and (2) the synergistic toughing effects from interfacial interactions of hydrogen and coordination bonding, layer slippage, and molecular chain stretching. The synergistic behavior of the "brick" and "mortar" allows for controlled crack generation for high sensitivity but can also dissipate considerable loading energy to promote the stepwise propagation of cracks while stretching, guaranteeing the significant comprehensive sensing performance. Moreover, this bioinspired strain sensor is employed to monitor human activities under different motion states to demonstrate its feasibility for wearable, full-spectrum human health and motion monitoring systems.
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