水性环氧树脂基石墨烯传感元件制备及其机敏特性
Preparation of waterborne epoxy resin based graphene sensor and its smart properties
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摘要: 为适应工程结构智能化转型升级对新型传感器的需求,以水性环氧树脂(WER)为基体,还原氧化石墨烯(RGO)为导电填料,纳米纤维素(CNF)为分散剂,采用溶液共混法,制备了RGO-CNF/WER传感元件,对其力学、电学和机敏性能进行了测试和分析,并建立了考虑应变率效应的机敏响应模型。结果表明:CNF能有效搭载RGO在水中均匀分散,协助其在WER中形成三维导电网络,RGO逾渗阈值约为0.15%。传感元件能承受超过70%的拉伸应变,初始的应变电阻响应不稳定,经过4次预拉伸后导电网络趋于完善,呈现较好的可重复和可回复性。当传感元件应变小于4%,电阻变化率与应变正线性相关,灵敏系数可达32;应变大于4%后,电阻变化率呈指数型增大,应变电阻响应强度随应变率的增大而增大。Abstract: To meet the demand for new sensors in the intelligent transformation and upgrading of engineering structures, using waterborne epoxy resin (WER) as the matrix, reduced graphene oxide (RGO) as the conductive filler, and cellulose nanofiber (CNF) as the dispersant, RGO-CNF/WER sensor was prepared using a solution blending method. The mechanical, electrical and smart properties were tested and analyzed, and a smart response model considering strain rate effects was established. The results indicated that CNF can effectively carry RGO for uniform dispersion in water, assisting in the formation of a three-dimensional conductive network in WER. The percolation threshold of RGO is about 0.15%. The sensor can withstand over 70% tensile strain, and its initial strain resistance response is unstable. After about 4 pre-stretching cycles, the conductive network tends to be perfected, showing good repeatability and recoverability. When the strain of the sensor is less than 4%, the resistance change rate is positively correlated with the strain, and the sensitivity coefficient can reach 32. After the strain exceeds 4%, the resistance change rate increases exponentially. The response strength of strain resistance increases with the increase of strain rate.