Evaluation thermal degradation kinetics of ionic liquid assisted polyetheretherketone-multiwalled carbon nanotubes composites

被引:5
|
作者
Ahmad, Aqeel [1 ,2 ]
Mansor, Nurlidia [3 ]
Mahmood, Hamayoun [4 ]
Sharif, Faiza [5 ]
Safdar, Rizwan [6 ]
Moniruzzaman, Muhammad [1 ,2 ,7 ]
机构
[1] Univ Teknol PETRONAS, Dept Chem Engn, Seri Iskandar, Malaysia
[2] Univ Teknol PETRONAS, Ctr Res Ion Liquids CORIL, Seri Iskandar, Malaysia
[3] Univ Teknol PETRONAS, Ctr Student Dev, Seri Iskandar, Malaysia
[4] Univ Engn & Technol UET, Dept Chem Polymer & Composite Mat Engn, Lahore, Pakistan
[5] COMSATS Univ Islamabad, Interdisciplinary Res Ctr Biomed Mat, Lahore, Pakistan
[6] Van Lang Univ, Sch Engn & Technol, Chem Engn Adv Mat & Renewable Energy Res Grp, Ho Chi Minh City, Vietnam
[7] Univ Teknol PETRONAS, Dept Chem Engn, Seri Iskandar 32610, Perak, Malaysia
关键词
artificial neural network; ionic liquid; multiwalled carbon nanotube; polymer composites; thermal degradation kinetics; NANOCOMPOSITES; PARAMETERS; PYROLYSIS; BEHAVIOR;
D O I
10.1002/app.53647
中图分类号
O63 [高分子化学(高聚物)];
学科分类号
070305 ; 080501 ; 081704 ;
摘要
The incorporation of multiwalled carbon nanotubes (MWCNT) into polyetheretherketone (PEEK) composites has emerged as a promising strategy for enhancing the thermomechanical characteristics of PEEK composite materials. This study investigates the thermal behavior and kinetics prediction of PEEK/MWCNT composites comprising different ionic liquids (ILs), namely 1-butyl-3-methylimidazolium hydrogen sulfate ([BMIM]HSO4), 1-butyl-3-methylimidazolium acetate ([BMIM]Ac), 1-ethyl-3-methylimidazolium acetate ([EMIM]Ac) and 1-ethyl-3-methylimidazolium hydrogen sulfate ([EMIM]HSO4). Three non-isothermal methods Coats-Redfern, Broido, and Horowitz-Metzger, were employed to model the thermal decomposition profiles of fabricated composites to calculate the activation energy. The highest decomposition temperature (580?) was obtained for [BMIM]HSO4-based PEEK/MWCNT composites. Moreover, a 3%-8% increase in the activation energy was obtained compared to PEEK/MWCNT manufactured without ILs. The Coats-Redfern model was superior to Broido and Horowitz-Metzger models in modeling the thermal degradation of developed composites, as evidenced from the higher value of the coefficient of determination (R-2 >= 0.9899). By determining the Root Mean Square Error (RMSE) and R-2 for the thermal degradation kinetics data, the artificial neural network (ANN) model was employed. The ANN model accurately predicted the mass loss curves, exhibiting R-2 >= 0.9815 for the designed model. These findings can assist in establishing an IL-assisted benign approach for PEEK/MWCNT/IL composites with superior thermal characteristics.
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页数:10
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