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.

Processing characteristics and mechanical properties of metallocene catalyzed linear low-density polyethylene foams for rotational molding

The object of this work is to assess the suitability of metallocene catalyzed linear low-density polyethylenes for the rotational molding of foams and to link the material and processing conditions to cell morphology and part mechanical properties (flexural and compressive strength). Through adjustments to molding conditions, the significant processing and physical material parameters that optimize metallocene catalyzed linear low-density polyethylene foam structure have been identified. The results obtained from an equivalent conventional grade of Ziegler-Natta catalyzed linear low-density polyethylene are used as a basis for comparison. The key findings of this study are that metallocene catalyzed LLDPE can be used in rotational foam molding to produce a foam that will perform as well as a ZieglerNatta catalyzed foam and that foam density Is by far the most Influential factor over mechanical properties of foam. © 2004 Society of Plastics Engineers.

Melt processing and properties of linear low density polyethylene-graphene nanoplatelet composites

Composites of Linear Low Density Polyethylene (LLDPE) and Graphene Nanoplatelets (GNPs) were processed using a twin screw extruder under different extrusion conditions. The effects of screw speed, feeder speed and GNP content on the electrical, thermal and mechanical properties of composites were investigated. The inclusion of GNPs in the matrix improved the thermal stability and conductivity by 2.7% and 43%, respectively. The electrical conductivity improved from 10−11 to 10−5 S/m at 150 rpm due to the high thermal stability of the GNPs and the formation of phonon and charge carrier networks in the polymer matrix. Higher extruder speeds result in a better distribution of the GNPs in the matrix and a significant increase in thermal stability and thermal conductivity. However, this effect is not significant for the electrical conductivity and tensile strength. The addition of GNPs increased the viscosity of the polymer, which will lead to higher processing power requirements. Increasing the extruder speed led to a reduction in viscosity, which is due to thermal degradation and/or chain scission. Thus, while high speeds result in better dispersions, the speed needs to be optimized to prevent detrimental impacts on the properties.

Effect of two types of graphene nanoplatelets on the physico–mechanical properties of linear low–density polyethylene composites

The influence of two types of graphene nanoplatelets (GNPs) on the physico-mechanical properties of linear low-density polyethylene (LLDPE) was investigated. The addition of these two types of GNPs – designated as grades C and M – enhanced the thermal conductivity of the LLDPE, with a more pronounced improvement resulting from the M-GNPs compared to C-GNPs. Improvement in electrical conductivity and decomposition temperature was also noticed with the addition of GNPs. In contrast to the thermal conductivity, C-GNPs resulted in greater improvements in the electrical conductivity and thermal decomposition temperature. These differences can be attributed to differences in the surface area and dispersion of the two types of GNPs.