Higher-order resistivity-strain relations for self-sensing nanocomposites subject to general deformations

• Published in: Composites. Part B, Engineering Vol. 190; p. 107907
• Main Authors: Koo, G.M., Tallman, T.N.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2020
• Subjects: Carbon nanofiber; Nanocomposites; Piezoresistivity; Self-sensing; Smart materials; Carbon nanofiber; Self-sensing; Piezoresistivity; Nanocomposites; Smart materials
• ISSN: 1359-8368; 1879-1069
• DOI: 10.1016/j.compositesb.2020.107907

Nanocomposites have received enormous attention for the development of smart structures and materials with intrinsic self-sensing capabilities via the piezoresistive effect. Consequently, much work has been done to model the resistivity-strain relationship in these materials. To date, the prevailing approach to modeling nanocomposite piezoresistivity has been to track the interaction of individual nanofillers via computational micromechanics-based models or analytical homogenizations thereof. Even though such models have generated great insight into the piezoresistive effect, they are not without limitations. For example, they are computationally expensive, require extensive calibration and/or training data, and are often limited to simple deformations and microscale analyses. In light of the preceding, this work presents a novel higher-order tensor-based resistivity-strain relation that is amenable to general strains and macroscale analyses. Herein, it is shown that higher-order resistivity-strain relations can be described by three piezoresistive constants which can be determined by fitting the model to experimental data. The proposed resistivity-strain relation is applied to three different weight fractions of carbon nanofiber (CNF)-modified epoxy and validated against experimental discrete resistance changes and spatially distributed resistivity changes imaged via electrical impedance tomography (EIT) for complex strain states with good agreement. This work could be of significant impact to a wide range of engineers working with polymer, cementitious, and ceramic-based smart materials who wish to utilize the piezoresistive effect without resorting to in-depth microscale modeling.