412
Views
61
CrossRef citations to date
0
Altmetric
Original Article

Development and characterization of alkali treated abaca fiber reinforced friction composites

, , , , &
Pages 67-82 | Received 26 Feb 2018, Accepted 01 May 2018, Published online: 22 May 2018
 

Abstract

Abaca fibers show tremendous potential as reinforcing components in composite materials. The purpose of this study is to investigate the effect of abaca fiber content on physical, mechanical and tribological properties of abaca fiber reinforced friction composites. The friction composites were fabricated by a compression molder and investigated using a friction test machine. The experiment results show that surface treatment of abaca fibers could improve the mechanical properties of abaca fiber and interface bonding strength of the abaca fiber and composite matrix. Density of friction composites decreased with the increasing of abaca fiber content (0 wt%–4 wt%). The different content of abaca fibers had less effect on hardness of specimens, whereas large of impact strength. The specimen F3 with 3 wt% abaca fibers had the lowest wear rate and possessed the best wear resistance, followed by specimen F4 with 4 wt% abaca fibers. The worn surface morphologies were observed using the Scanning Electron Microscopy for study the tribological behavior and wear mechanism. The results show that a large amount of secondary contact plateaus presented on the worn surface of specimen F3 which had relatively smooth worn surface.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 574.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.