Fabrication of self-healable magnetic nanocomposites via Diels-Alder click chemistry

Yi Huan Lee, Yan Nian Zhuang, Hsin Ta Wang, Ming Feng Wei, Wen Chi Ko, Wei Jen Chang, Tun Fun Way, Syang Peng Rwei

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


In this study, we report a novel approach to fabricate an organic/inorganic magnetic hybrid system capable of self-healing, wherein a polycaprolactone-poly(furfuryl glycidyl ether) copolymer (PCLF) serving as the structure template was first synthesized, followed by the incorporation of iron oxide nanoparticles-decorated multiwalled carbon nanotubes (IONPs-MWCNTs) and 1,1'-(methylenedi-4,1-phenylene)bismaleimide (BMI) into the polymer matrix to form a covalently crosslinked hybrid network via a Diels-Alder (DA) reaction. For this system, the reactive combination of diene and dienophile from furan/maleimide, MWCNT/furan, and MWCNT/maleimide could facilely induce multiple DA reactions that imparted a versatile route to efficiently introduce IONPs-MWCNTs into the organic polymer hosts, resulting in a uniform distribution of IONPs-MWCNTs that led to a hybrid system with superparamagnetic properties. Beside the magnetic behavior, such material synergistically exhibited a superior ability for healing scratch defects via a retro-DA reaction. Therefore, this crosslinked PCLF/BMI/IONPs-MWCNTs hybrid system which exhibits multifunctional properties including superparamagnetic behavior and self-repairability can serve as an intelligent material for developing advanced electromagnetic applications.

Original languageEnglish
Article number506
Pages (from-to)506
JournalApplied Sciences (Switzerland)
Issue number3
Publication statusPublished - Feb 1 2019


  • Copolymer
  • Diels-Alder reaction
  • Iron oxide nanoparticles
  • Nanocomposites
  • Self-healing

ASJC Scopus subject areas

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes


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