Effects of stacking-up and aggregation of graphene nanoplatelet on the polymernanocomposite effective properties

The aim of the present work is to investigate and model theinfluencing factors including graphene nanoplatelet (GNP)size, aggregation state, stacking-up and random distribution ofGNPs within the polymer nanocomposite. A high-fidelitygeneralized method of cell (HFGMC) analyticalmicromechanical model based on a unit cell is extended toestimate the elastic modulus of GNP-reinforced polymernanocomposite. For reliable modelling and estimating theelastic modulus close to the experimental data, it is assumedthat the GNPs inside the nanocomposite are randomlydistributed. GNP has linear and transversely isotropic elasticbehavior and polymer matrix has linear and isotropic elasticbehavior. By considering the important factors involved in theconstruction of nanocomposite in the current micromechanicalmodeling, including (i) the GNP agglomeration dependent onthe volume fraction, (ii) the GNP size, and (iii) stacking ofGNP inside the nanocomposite, the current model can estimatethe nanocomposite elastic modulus in a way that is very closeto the experimental data. The agglomeration and stacking ofGNPs are modelled through a representative volume element(RVE) of nanocomposite containing two phases includingGNP and polymer matrix. Considering the agglomeration statedependent on the volume fraction of GNP leads to a veryaccurate estimation of the elastic modulus of thenanocomposite compared to the case where the agglomerationis independent of the volume fraction. It is shown that theincrease of GNP stacking and agglomeration state inside thenanocomposite has a detrimental effect on the effectiveproperties of the nanocomposite.

کلیدواژه ها:

Graphene nanoplatelet (GNP) ، GNP-reinforcednanocomposite ، GNP stacking ، aggregation state ، aggregationdependentvolume fraction