Self-sensing Cementitious Composites with Graphene Nanoplatelets
Jiang, Zhangfan, Civil Engineering - School of Engineering and Applied Science, University of Virginia
Ozbulut, Osman, Department of Civil Engineering, University of Virginia
Traditional strategies in structural health monitoring of civil infrastructure systems involve a limited number of distributed sensors over a relatively large area. The high cost, low durability, and weak compatibility with host structure are among the challenges for conventional sensors. Cement-based self-sensing composites with intrinsic strain- and damage-sensing capabilities can be a more practical and sustainable alternative to monitor the health of concrete structures. Numerous research studies have been conducted to explore behavior of self-sensing cementitious composites with different functional fillers. Most of previous studies investigated the use of fillers such as carbon fiber (CF), carbon nanofiber (CNF), and carbon nanotubes (CNTs) in cement composites as a method to develop multifunctionality in the base material. More recently, graphene nanoplatelets (GNPs), which have very thin (several layer thickness of graphene sheet) but wide aspect ratio, are gaining traction in the graphene market due to their advantages such as ease of processing and excellent material properties at a very low cost. However, the understanding of behavior of cementitious composites with GNPs is still in its infancy. In addition, although a large number of efforts have been made to develop intrinsically self-sensing cementitious materials with different nano fillers, fewer efforts have been made to find simple, repeatable, and large-scale fabrication procedures of these multifunctional composites. Therefore, there is a need for further research on the practical and scalable fabrication methods for the development of cement-based self-sensing composites using GNPs.
The objective of this study is to explore the development of self-sensing cementitious composites with GNPs using a simple fabrication method and investigate the piezoelectric characteristics of the developed composites. Systematic studies were conducted to determine the influence of GNP concentration ratio and mixing method on the electrical conductivity of GNP-based self-sensing cementitious composites. In particular, two fabrication methods that do not require any special treating procedure such as ultrasonication and covalent treatment were considered. For the detection of percolation threshold, which roughly represents the optimal quantity of the GNPs required achieving satisfactory self-sensing, the specimens with various GNP concentration were prepared. For measuring the electrical resistivity, four copper meshes were used as electrodes and embedded into the specimens immediately after casting. Cyclic compression tests were conducted to explore piezoresistive behavior of the specimens with different GNP concentrations. To better assess the GNP dispersion at the specimens prepared using different mixing method, scanning electron microscopy images of the tested specimens were taken. Results revealed that the GNP-reinforced cementitious composites exhibit good piezoresistive behavior with high gage factors up to 125 under cyclic compressive loads when the GNP ratio exceeds 5% by weight of cement. Recommendations for further investigations to fully characterize both mechanical and piezoresistive behavior of GNP-reinforced cement composites were provided.
MS (Master of Science)
Self-sensing, Graphene nanoplatelets