[论文解读] Piezoelectric composite cements: Towards the development of self-powered and self-diagnostic materials

Daniel A. Triana-Camacho, Jorge H. Quintero‐Orozco+3 more|arXiv (Cornell University)|Mar 1, 2023

Smart Materials for Construction被引用 5

一句话总结

本研究通过结合超声分散与一种新型电路模型，开发出具有高机电耦合性能的还原氧化石墨烯-水泥复合材料，实现了自供能、自诊断的结构健康监测。其d₃₃压电系数达到1122.28 ± 246.67 pC/N，较以往水泥基复合材料高出47倍，实现了电能输出与机械应变成线性关系，适用于离网传感应用。

ABSTRACT

Piezoresistivity is the most commonly used sensing principle in cement-based smart composites for strain-monitoring applications. Nonetheless, the need for external electric power to conduct electrical resistivity measurements restricts the scalability of this technology, especially when implemented in remote structures. To address this issue, this manuscript thoroughly analyzes the piezoelectric properties of cement composites doped with reduced graphene oxide (rGO) and evaluates their potential as self-powered strain sensors. To do so, a comprehensive methodology involving voltammetry measurements, open circuit potential determination, and uniaxial compression testing is developed to determine the piezoelectric coefficients of charge $d_{33}$ and voltage $g_{33}$. Furthermore, a novel circuital model for signal processing of the electromechanical response is developed and experimentally validated in terms of time series of output voltage, resistance, and the generated electric power. The developed methodology is applied to laboratory samples manufactured following two different filler dispersion methods. The presented results evidence that samples prepared by ultrasonic cleaner dispersion achieve optimal properties, with a piezoelectric charge coefficient of 1122.28$\mathrm{\pm}$246.67 pC/N, about 47 times greater than previously reported composites in the literature. Unlike piezoresistive cement-based composites, a remarkable nonlinear correlation between the fractional change in the intrinsic resistance of the material and the applied mechanical strain has been observed. Instead, a considerable linearity ($\mathrm{R^2}=0.96$) between the externally applied mechanical strain and the generated (piezoelectric) electric power has been found, which suggests the great potential of the latter for conducting off-the-grid strain monitoring applications.

研究动机与目标

• 为克服压阻型水泥传感器对外部电源的依赖，开发自供能替代方案。
• 研究还原氧化石墨烯掺杂水泥复合材料的压电性能，为其自诊断材料的开发提供基础。
• 建立表征压电系数d₃₃与g₃₃的综合性方法学，结合电化学与机械测试手段。
• 提出并验证一种集总等效电路模型，准确模拟循环载荷下的机电响应。
• 比较超声清洗机与超声探针两种分散技术，优化rGO分布与压电性能。

提出的方法

• 开发了循环伏安法与准静态单轴压缩测试相结合的协议，以提取d₃₃与g₃₃压电系数。
• 采用开路电位（OCP）测量评估rGO-水泥复合材料的本征电化学行为。
• 采用两种分散方法——超声清洗机与超声探针——制备实验室规模的rGO-水泥样品，进行对比分析。
• 提出一种新型集总等效电路模型，将压电电流源与RL串联电路并联，以模拟电压、电阻与电能输出。
• 通过循环载荷过程中输出电压、电阻与生成电能的时间序列数据，对模型进行实验验证。
• 利用决定系数R²分析理论与实验结果的相关性，评估机械应变与电输出之间的线性关系。

实验结果

研究问题

• RQ1 rGO掺杂水泥复合材料是否能表现出足够强的压电性能，以支持自供能传感应用？
• RQ2 分散方法（超声清洗机 vs. 超声探针）如何影响rGO-水泥复合材料的均匀性与压电性能？
• RQ3 rGO-水泥复合材料中生成的电能与施加的机械应变之间的线性相关程度如何？
• RQ4 集总等效电路模型能否准确模拟涉及压电、压阻与压电容效应耦合的复杂机电响应？
• RQ5 rGO-水泥复合材料中d₃₃压电系数的定量值是多少？与现有文献相比有何差异？

主要发现

• 采用超声清洗机分散的rGO-水泥复合材料具有更均匀的rGO分布，其压电性能显著优于超声探针分散方法。
• rGO-水泥复合材料的d₃₃压电电荷系数达到1122.28 ± 246.67 pC/N，较以往报道的PZT基水泥复合材料提高47倍。
• 施加的机械应变与生成的压电电能之间表现出强线性相关性（R² = 0.96），表明其在离网应变监测中具有高度适用性。
• 电路模型准确复现了实验获得的输出电压、电学电阻与电能的时间序列数据，包括由压电、压阻与压电容效应耦合引起的非线性行为。
• 内在电阻的非线性行为被归因于机电耦合效应，而非本征压阻性，挑战了传感器建模中传统的假设。
• 本研究表明，在低rGO掺量条件下，压电效应主导传感响应，使其成为自供能结构健康监测的更优机制。