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

  • Aqeel Ahmad
  • , Nurlidia Mansor
  • , Hamayoun Mahmood
  • , Faiza Sharif
  • , Rizwan Safdar
  • , Muhammad Moniruzzaman*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

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°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.

Original languageEnglish
Article numbere53647
JournalJournal of Applied Polymer Science
Volume140
Issue number12
DOIs
StatePublished - 20 Mar 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 Wiley Periodicals LLC.

Keywords

  • artificial neural network
  • ionic liquid
  • multiwalled carbon nanotube
  • polymer composites
  • thermal degradation kinetics

ASJC Scopus subject areas

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

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