JOURNAL ARTICLE

Effect of teak wood on recycled HDPE/pine wood composites subjected to termite attack and accelerated weathering.

  • Published In: Journal of Thermoplastic Composite Materials, 2024, v. 37, n. 3. P. 1027 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Cruz-Estrada, Ricardo H; Guillén-Mallette, Javier; López-Naranjo, Edgar J; Zacarías-Calderón, Edgar 3 of 3

Abstract

This study investigates the effect of incorporating teak wood flour (TW) into recycled high-density polyethylene (rHDPE) wood-plastic composites (WPC) containing pine wood flour (PW) on resistance to termite attack and accelerated weathering. Using a factorial experimental design, the research measured weight loss and termite mortality, finding that WPC with higher teak content exhibited reduced weight loss and increased termite mortality, attributed to teak’s extractable compounds with termiticidal properties. Surface analyses via scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) revealed that accelerated weathering caused microcracks exposing wood particles, facilitating termite degradation, while teak’s chemical composition, including higher hemicellulose and conjugated quinones, contributed to greater durability. The results suggest that adding teak wood flour enhances the biodegradation resistance and potentially extends the service life of WPC products compared to those made solely with pine wood flour.

Additional Information

  • Source:Journal of Thermoplastic Composite Materials. 2024/03, Vol. 37, Issue 3, p1027
  • Document Type:Article
  • Subject Area:Zoology
  • Publication Date:2024
  • ISSN:0892-7057
  • DOI:10.1177/08927057231190561
  • Accession Number:175500740
  • Copyright Statement:Copyright of Journal of Thermoplastic Composite Materials is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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