Optimization and Prediction of Mechanical and Thermal Properties of Graphene/LLDPE Nanocomposites by Using Artificial Neural Networks

The focus of this work is to develop the knowledge of prediction of the physical and chemical properties of processed linear low density polyethylene (LLDPE)/graphene nanoplatelets composites. Composites made from LLDPE reinforced with 1, 2, 4, 6, 8, and 10 wt% grade C graphene nanoplatelets (C-GNP) were processed in a twin screw extruder with three different screw speeds and feeder speeds (50, 100, and 150 rpm). These applied conditions are used to optimize the following properties: thermal conductivity, crystallization temperature, degradation temperature, and tensile strength while prediction of these properties was done through artificial neural network (ANN). The three first properties increased with increase in both screw speed and C-GNP content. The tensile strength reached a maximum value at 4 wt% C-GNP and a speed of 150 rpm as this represented the optimum condition for the stress transfer through the amorphous chains of the matrix to the C-GNP. ANN can be confidently used as a tool to predict the above material properties before investing in development programs and actual manufacturing, thus significantly saving money, time, and effort.

A boron nitride - graphene - C60 heterostructure

We have fabricated a new van-der-Waals heterostructure composed by BN/graphene/C60. We performed transport measurements on the preliminary BN/graphene device finding a sharp Dirac point at the neutrality point. After the deposition of a C60 thin film by thermal evaporation, we have observed a significant n-doping of the heterostructure. This suggests an unusual electron transfer from C60 into the BN/graphene structure. This BN/graphene/C60 heterostructure can be of interest in photovoltaic applications. It can be used to build devices like p-n junctions, where C60 can be easily deposited in defined regions of a graphene junction by the use of a shadow mask. Our results are contrasted with theoretical calculations.