Embedded Carbon Nanotube Networks for Damage Precursor Detection.

摘要

Current structural health monitoring efforts are limited by the finite number of localized points that can be analyzed. Because of their small size, carbon nanotubes can combine with materials without significantly affecting the original material properties. Adding carbon nanotubes into a material allows researchers to create a distributed conductive network within the material. As damage occurs within these materials, the electrical properties of this network change with it. In this study, Epon 863 (epoxy) dogbone specimens were fabricated with super-aligned multiwall carbon nanotubes for embedded sensing for damage precursor detection. The specimens were under cyclic fatigue loading as the electrical response was monitored. A four-point probe method was used to pass the current through the samples while recording the change in resistance. After the specimen underwent cyclic fatigue, a fractographic analysis was conducted to correlate the type of damage along with the change in resistance.