Sensing micro-scale damage in a self-sensing nanocomposite material

Abstract

This research makes use of Carbon nanotubes (single-wall and Multi-wall CNT) and Graphene which act as functional fillers. The process of dispersing these materials in the concrete mix is lengthy as they need to be well-dispersed to create an integrated conductive network inside the samples. When the concrete specimen is stressed and deformed, the matrix of the conductive network changes affecting the electrical parameters of the concrete composite. As the concrete material is deformed or stressed, the conductive network inside the material is changed, and thus affects the electrical properties of the cement-based composite material. The objective of this material is to be able to detect any stress, strain, cracking, and damage under static or cyclic loading by measuring the electrical properties of composite material using different amounts of the electrically conductive materials. Using this system of having a conductive sensor network illustrates how the material can monitor the structural health and durability by assessing the behaviour in different environmental conditions. In this research, different tests were carried out to achieve piezometric measurements through Cyclic Compression Testing and Flexural Testing. The compressive and flexural strengths were determined. The different types and quantities of the carbon-based materials added within the conventional concrete mix resulted in different results as expected. The workability of the intrinsic self-sensing concrete mortar was improved. The exfoliation of graphite through sonication was successful in producing multi-layered graphene. The conductive network was seen under the microscope to be homogenously dispersed. This homogonous dispersion to form the conductive network was imperative so that the electrical properties of the carbon-based materials were improved. The electrically conductive materials showed a change in the electrical resistance under cyclic compression loading so the micro-scale damage could be effectively detected. The sample with 0.01% SWCNT had the best piezoresistive properties when being tested. A non-linear graph was achieved for flexural loading indicating that damage was being sensed during the test. The flexural and compressive strengths were improved for all the samples containing the electrically conductive materials.