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

Author:

Ahmad Aqeel12,Mansor Nurlidia3,Mahmood Hamayoun4,Sharif Faiza5,Safdar Rizwan6,Moniruzzaman Muhammad12ORCID

Affiliation:

1. Department of Chemical Engineering Universiti Teknologi PETRONAS Seri Iskandar Malaysia

2. Center of Research in Ionic Liquids (CORIL) Universiti Teknologi PETRONAS Seri Iskandar Malaysia

3. Centre for Student Development Universiti Teknologi PETRONAS Seri Iskandar Malaysia

4. Department of Chemical, Polymer and Composite Materials Engineering University of Engineering and Technology (UET) Lahore Pakistan

5. Interdisciplinary Research Centre in Biomedical Materials COMSATS University Islamabad Lahore Pakistan

6. Chemical Engineering in Advanced Materials and Renewable Energy Research Group, School of Engineering and Technology Van Lang University Ho Chi Minh City Vietnam

Abstract

AbstractThe 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°C) 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 (R2 ≥ 0.9899). By determining the Root Mean Square Error (RMSE) and R2 for the thermal degradation kinetics data, the artificial neural network (ANN) model was employed. The ANN model accurately predicted the mass loss curves, exhibiting R2 ≥ 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.

Funder

Higher Education Commision, Pakistan

Ministry of Higher Education, Malaysia

Publisher

Wiley

Subject

Materials Chemistry,Polymers and Plastics,Surfaces, Coatings and Films,General Chemistry

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