Prediction of mechanical properties of graphite nanoflake/polydimethylsiloxane nanocomposites as affected by processing method

Abstract

Abstract Porosity is suppressible but unavoidable in manufacturing nanocomposites, therefore affecting their mechanical properties like intrinsic properties and other filler-related factors. Despite all the efforts, it is still regarded as challenging to develop theoretical models for mechanical properties of filler-reinforced nanocomposites which consider void defects created during manufacturing process. Here, graphite nanoflake/polydimethylsiloxane (GnF/PDMS) nanocomposites for paint-on applications are manufactured with different processing methods (i.e., solvent casting, hand lay-up, and spray lay-up) to address imperfections involved in each process and their implication to mechanical properties. The manufacturing processes were found to have almost no alternation on filler-related features (i.e., size, orientation, and distribution) except porosity. The evolution of a porosity is best modeled with the logistic function. We establish a set of prediction models for elastic modulus, fracture strength, and elongation at break by combining the previous models (i.e., Tsai-Hahn, Piggott-Leidner, and Landel-Nielsen models) with the logistic function on porosity. The proposed models are in good agreement with the experimental data on GnF/PDMS nanocomposites. The effect of process method on surface morphology is also discussed.