Evaluation thermal degradation kinetics of ionic liquid assisted polyetheretherketone-multiwalled carbon nanotubes composites
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...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Published: |
2023
|
| Online Access: | http://scholars.utp.edu.my/id/eprint/34331/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85147218406&doi=10.1002%2fapp.53647&partnerID=40&md5=e6f505e278153abb6e6ff5285bc18bb8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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 (BMIMHSO4), 1-butyl-3-methylimidazolium acetate (BMIMAc), 1-ethyl-3-methylimidazolium acetate (EMIMAc) and 1-ethyl-3-methylimidazolium hydrogen sulfate (EMIMHSO4). 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 BMIMHSO4-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. © 2023 Wiley Periodicals LLC. |
|---|