Electrical conductivity of multifunctional cementitious composites reinforced by graphene derivatives: A finite element-based computational micromechanics model

Abstract

Graphene derivatives (GDs) are known for their considerable conductivity and electron mobility, making them promising candidates for developing electrically conductive cementitious composites (CCs). Consequently, CCs reinforced with GDs (CRGDs) can serve a variety of applications in the construction industry. Despite several experimental studies on the conductivity of CRGDs, finite element (FE) models have rarely been developed to investigate the conductivity of CRGDs. Previous FE models primarily focused on one-dimensional fillers like carbon nanotubes within polymeric matrices, overlooking the distinctive anisotropic behaviour of GDs in cementitious matrices. This study introduces a computational micromechanics model (CMM), integrating the representative elementary volume (REV) concept with FE analysis, to investigate the electrical conductivity of CRGDs. This model is particularly noted for its computational efficiency, as it converts the problem dimensions from 3D to 2D while ensuring an acceptable degree of accuracy. The CMM captures the anisotropic conductivity of GDs and includes critical conductivity mechanisms such as conductive pathways, the tunnelling effect, and field emission. Subsequently, REV size sensitivity analysis is performed to ensure the statistical relevance of the REV, followed by the model's validation against experimental data from the literature. Afterwards, the model's sensitivity analysis clarifies how different parameters, including the constituent properties, influence prediction results. The sensitivity analysis results suggest that the aspect ratio of GDs has considerable impacts on the electrical conductivity and the percolation threshold of CRGDs. Ultimately, this study aims to provide insights into the optimization and design of electrically conductive CRGDs and lay the foundation for future research in this area.