Thermal Behavior Prediction of MDPE Nanocomposite/Cloisite Na+ Using Artificial Neural Network and Neuro-Fuzzy Tools

Abstract

Recently, we successfully prepared medium density polyethylene (MDPE) nanocomposite with 3 wt %, 6 wt %, and 9 wt % cloisite Na+ and the thermal stability of nanocomposite was investigated using the thermogravimetric analysis (TGA). The TGA in air atmosphere showed significantly improved thermal stability of 3 wt %, 6 wt %, and 9 wt % cloisite Na+ nanocomposite in comparison to pure MDPE. In this paper, the results of TGA of MDPE/cloisite Na+ nanocomposites were predicted by the artificial neural network (ANN). The ANN and adaptive neural fuzzy inference systems (ANFIS) models were developed to predict the degradation of MDPE/cloisite Na+ nanocomposite with temperature. The results revealed that there was a good agreement between predicted thermal behavior and actual values. The findings of this study also showed that the artificial neural networks and ANFIS techniques can be applied as a powerful tool.