JOURNAL ARTICLE

Novel recycling of plastic waste into high impact resistant ultralightweight thermally insulated hybrid composite.

  • Published In: Journal of Thermoplastic Composite Materials, 2024, v. 37, n. 4. P. 1462 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Ibrahim, Juhaina; Bhowmik, Shantanu 3 of 3

Abstract

This article focuses on the development and evaluation of a high-performance hybrid composite made from recycled plastic waste, specifically combining polycarbonate sheets and cross-linked polyethylene (XLPE) foam bonded with silicone adhesive. The composite is designed to be ultralightweight, thermally insulated, and highly impact resistant, targeting applications in cold regions such as the Himalayan area of India where traditional concrete and plastic tanks face durability and insulation challenges. Experimental tests, including drop impact, compression, dry ice exposure, and thermogravimetric analysis, alongside numerical simulations using Abaqus/Explicit, demonstrated that the composite maintains thermal insulation at temperatures as low as −78.6°C, withstands significant impact loads, and offers superior mechanical properties compared to conventional materials. The study highlights the composite's potential as a sustainable alternative for water and septic tanks in extreme cold environments, leveraging recycled plastics to address environmental and functional concerns.

Additional Information

  • Source:Journal of Thermoplastic Composite Materials. 2024/04, Vol. 37, Issue 4, p1462
  • Document Type:Article
  • Subject Area:Environmental Sciences
  • Publication Date:2024
  • ISSN:0892-7057
  • DOI:10.1177/08927057231196079
  • Accession Number:176105608
  • 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.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.