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基于聚吡咯修饰碳纳米管动态构建的神经元启发型自修复复合材料用于智能理化传感

Neuron-Inspired Self-Healing Composites via Dynamic Construction of Polypyrrole-Decorated Carbon Nanotubes for Smart Physiochemical Sensing.

机构信息

State Key Laboratory for Environment-friendly Energy Materials, School of Materials Science and Engineering, Southwest University of Science and Technology, Mianyang 621010, PR China.

出版信息

ACS Appl Mater Interfaces. 2020 Jul 22;12(29):33139-33151. doi: 10.1021/acsami.0c05083. Epub 2020 Jul 9.

DOI:10.1021/acsami.0c05083
PMID:32584533
Abstract

Mimicking human skin's functions to develop intelligent materials have inspired extensive exploration in the design and synthesis of a novel device. However, how to simulate neuron function and integrate highly sensitive, positive perceptions and self-healing into one single material remains a challenge. Here, we prepared a recycled polyurethane (PU) with high tensile strength values (11.37 ± 0.03 MPa), high maximum elongation (1130 ± 11.59%), and high self-healing property (100% for 6 h at 25 °C) and a smart PU composite of polypyrrole-decorated carbon nanotubes with higher sensitivity. The smart composite can not only actively identify physical change such as strain, moisture, and temperature but also proactively detect various chemical environment changes such as acid, alkali, oxidant, and reductant (: 25-90 °C, Δ/ values were 0.1-1.6; strain: 10-150%, Δ/ values were 2.5-27; 0.01-0.1 mol L oxidant solutions, Δ/ values were 0.66-0.75; 0.01-0.1 mol L reductant solutions, Δ/ values were 0.51-0.65; 0.1-0.5 mol L acid solutions, Δ/ values were 0.54-0.58; and 0.1-0.5 mol L alkali solutions, Δ/ values were 0.42-0.46). More importantly, the signal values of the smart composite can quickly return to the initial values after eliminating physical and chemical stimuli. The abovementioned features of the smart composite, the high physicochemical response, and significant restorability make it potentially possible to apply it in intelligent chemical manufacturing.

摘要

模拟人体皮肤的功能来开发智能材料激发了人们对设计和合成新型器件的广泛探索。然而,如何模拟神经元功能并将高灵敏度、正感知和自修复集成到单一材料中仍然是一个挑战。在这里,我们制备了一种具有高拉伸强度值(11.37±0.03 MPa)、高最大伸长率(1130±11.59%)和高自修复性能(在 25°C 下 6 h 内达到 100%)的回收型聚氨酯(PU)和一种具有更高灵敏度的聚吡咯修饰碳纳米管智能 PU 复合材料。智能复合材料不仅可以主动识别应变、湿度和温度等物理变化,还可以主动检测酸、碱、氧化剂和还原剂等各种化学环境变化(温度:25-90°C,Δ/值为 0.1-1.6;应变:10-150%,Δ/值为 2.5-27;0.01-0.1 mol/L 氧化剂溶液,Δ/值为 0.66-0.75;0.01-0.1 mol/L 还原剂溶液,Δ/值为 0.51-0.65;0.1-0.5 mol/L 酸溶液,Δ/值为 0.54-0.58;0.1-0.5 mol/L 碱溶液,Δ/值为 0.42-0.46)。更重要的是,智能复合材料的信号值在消除物理和化学刺激后可以迅速恢复到初始值。智能复合材料的上述特性,即高物理化学响应性和显著的恢复能力,使其有可能应用于智能化学制造。

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