Recently, we successfully prepared medium density polyethylene (MDPE) nanocomposite with , , and cloisite and the thermal stability of nanocomposite was investigated using the thermogravimetric analysis (TGA). The TGA in air atmosphere showed significantly improved thermal stability of , , and cloisite nanocomposite in comparison to pure MDPE. In this paper, the results of TGA of MDPE/cloisite 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 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.
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e-mail: sargolzaei@um.ac.ir
e-mail: behdad2005@gmail.com
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November 2010
Research Papers
Thermal Behavior Prediction of MDPE Nanocomposite/Cloisite Using Artificial Neural Network and Neuro-Fuzzy Tools
J. Sargolzaei,
J. Sargolzaei
Department of Chemical Engineering,
e-mail: sargolzaei@um.ac.ir
Ferdowsi University of Mashhad
, Mashhad, 9177948944, Iran
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B. Ahangari
B. Ahangari
Department of Chemical Engineering,
e-mail: behdad2005@gmail.com
Ferdowsi University of Mashhad
, Mashhad, 9177948944, Iran
Search for other works by this author on:
J. Sargolzaei
Department of Chemical Engineering,
Ferdowsi University of Mashhad
, Mashhad, 9177948944, Irane-mail: sargolzaei@um.ac.ir
B. Ahangari
Department of Chemical Engineering,
Ferdowsi University of Mashhad
, Mashhad, 9177948944, Irane-mail: behdad2005@gmail.com
J. Nanotechnol. Eng. Med. Nov 2010, 1(4): 041012 (5 pages)
Published Online: October 29, 2010
Article history
Received:
August 29, 2010
Revised:
September 21, 2010
Online:
October 29, 2010
Published:
October 29, 2010
Citation
Sargolzaei, J., and Ahangari, B. (October 29, 2010). "Thermal Behavior Prediction of MDPE Nanocomposite/Cloisite Using Artificial Neural Network and Neuro-Fuzzy Tools." ASME. J. Nanotechnol. Eng. Med. November 2010; 1(4): 041012. https://doi.org/10.1115/1.4002703
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