論文

査読有り 本文へのリンクあり
2020年4月

Well-dispersed cellulose nanofiber in low density polyethylene nanocomposite by liquid-Assisted extrusion

Polymers
  • Tengku Arisyah Tengku Yasim-Anuar
  • ,
  • Hidayah Ariffin
  • ,
  • Mohd Nor Faiz Norrrahim
  • ,
  • Mohd Ali Hassan
  • ,
  • Yoshito Andou
  • ,
  • Takayuki Tsukegi
  • ,
  • Haruo Nishida

12
4
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.3390/POLYM12040927
出版者・発行元
MDPI

Two different liquid assisted processing methods: internal melt-blending (IMB) and twin-screw extrusion (TWS) were performed to fabricate polyethylene (PE)/cellulose nanofiber (CNF) nanocomposites. The nanocomposites consisted maleic anhydride-grafted PE (PEgMA) as a compatibilizer, with PE/PEgMA/CNF ratio of 97/3/0.5-5 (wt./wt./wt.), respectively. Morphological analysis exhibited that CNF was well-dispersed in nanocomposites prepared by liquid-assisted TWS. Meanwhile, a randomly oriented and agglomerated CNF was observed in the nanocomposites prepared by liquid-assisted IMB. The nanocomposites obtained from liquid-assisted TWS exhibited the best mechanical properties at 3 wt.% CNF addition with an increment in flexural strength by almost 139%, higher than that of liquid-assisted IMB. Results from this study indicated that liquid feeding of CNF assisted the homogenous dispersion of CNF in PE matrix, and the mechanical properties of the nanocomposites were affected by compounding method due to the CNF dispersion and alignment.

リンク情報
DOI
https://doi.org/10.3390/POLYM12040927
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000535587700197&DestApp=WOS_CPL
Scopus
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85084839658&origin=inward 本文へのリンクあり
Scopus Citedby
https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85084839658&origin=inward
URL
https://www.mdpi.com/2073-4360/12/4/927
ID情報
  • DOI : 10.3390/POLYM12040927
  • eISSN : 2073-4360
  • ORCIDのPut Code : 72557003
  • SCOPUS ID : 85084839658
  • Web of Science ID : WOS:000535587700197

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