Journal of Nanotechnology in Engineering and Medicine, Volume (1), No (2), Year (2010-10) , Pages (1-5)

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

Authors: Javad Sargolzaei , behdad ahangari ,
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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.

Keywords

, nanocomposite, MDPE, neural networks, neuro-fuzzy, TGA, cloisite
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@article{paperid:1018744,
author = {Sargolzaei, Javad and Ahangari, Behdad},
title = {Thermal Behavior Prediction of MDPE Nanocomposite/Cloisite Na+ Using Artificial Neural Network and Neuro-Fuzzy Tools},
journal = {Journal of Nanotechnology in Engineering and Medicine},
year = {2010},
volume = {1},
number = {2},
month = {October},
issn = {1949-2944},
pages = {1--5},
numpages = {4},
keywords = {nanocomposite; MDPE; neural networks; neuro-fuzzy; TGA; cloisite Na+},
}

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%0 Journal Article
%T Thermal Behavior Prediction of MDPE Nanocomposite/Cloisite Na+ Using Artificial Neural Network and Neuro-Fuzzy Tools
%A Sargolzaei, Javad
%A Ahangari, Behdad
%J Journal of Nanotechnology in Engineering and Medicine
%@ 1949-2944
%D 2010

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