Improved compressive and flexural performances of functionally graded graphene nanoplatelet reinforced cement composites: Experiments and modelling

Graphene reinforced cement composites (GRCCs) have demonstrated competitive mechanical and physical properties. Instead of uniform distribution, functionally graded distribution of the graphene fillers can effectively utilize the advantages of each constituents with improved performances and reduced cost. This paper conducts experiments and modelling on mechanical properties of functionally graded graphene nanoplatelet reinforced cement composites (FG-GNPRCCs). Samples with three functionally graded distributions (X, A and O types) together with uniform distribution (H-type) are prepared and tested. Compared to uniform distribution, the flexural strength and maximum compressive load of functionally graded distributions are significantly increased. For example, the flexural strength of X-5 pattern is increased by 24.36% and the maximum compressive load of O-3 pattern is increased by 13.42%. Based on effective medium theory (EMT) and Mori-Tanaka (MT) model, a parallel triple-inclusion model is developed to predict the Young's modulus of GNPRCCs. The effects of GNP dispersion, agglomeration and pores on the mechanical properties of the composites are comprehensively studied. Moreover, the cracking load for FG-GNPRCCs is evaluated by combining experiments and modelling, which can provide reference for the design and optimization of high-performance of cement composites and structures.