Thermal Behavior Prediction of MDPE Nanocomposite/Cloisite Na+ Using Artificial Neural Network and Neuro-Fuzzy Tools
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 sta...
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Veröffentlicht in: | Journal of nanotechnology in engineering and medicine 2010-11, Vol.1 (4) |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
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Zusammenfassung: | 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. |
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ISSN: | 1949-2944 1949-2952 |
DOI: | 10.1115/1.4002703 |