JOURNAL ARTICLE

A comprehensive study on mechanical and fracture properties of polypropylene/ethylene propylene diene monomer/halloysite blend polymer nanocomposites.

  • Published In: Journal of Elastomers & Plastics, 2025, v. 57, n. 5. P. 672 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Nedaei Shekarab, Mahmoud; Ashenai Ghasemi, Faramarz; Fasihi, Mohammad; Rajaee, Pouya 3 of 3

Abstract

This study investigates the mechanical and fracture properties of polypropylene (PP) blend polymer nanocomposites containing ethylene propylene diene monomer (EPDM) and halloysite (HNT) fillers, focusing on both unvulcanized and dynamically vulcanized states with and without the compatibilizer polypropylene-g-maleic anhydride (PP-g-MA). Using a full factorial design and the essential work of fracture (EWF) methodology, the research found that increasing EPDM content to 20 wt.% decreased tensile strength, modulus, and EWF but significantly improved elongation at break and non-EWF, while adding 3 wt.% HNT enhanced tensile strength and fracture toughness, with higher HNT levels causing declines due to agglomeration. Dynamically vulcanized compounds and those with PP-g-MA showed superior mechanical and fracture performance compared to unvulcanized and non-compatibilized counterparts. Fractography indicated ductile fracture dominated by fibrillation and plastic deformation, and optimization suggested that dynamically vulcanized blends with 10 wt.% EPDM, 3 wt.% HNT, and PP-g-MA achieved the best balance of strength, stiffness, and toughness.

Additional Information

  • Source:Journal of Elastomers & Plastics. 2025/08, Vol. 57, Issue 5, p672
  • Document Type:Article
  • Subject Area:Chemistry
  • Publication Date:2025
  • ISSN:0095-2443
  • DOI:10.1177/00952443251331172
  • Accession Number:186417957
  • Copyright Statement:Copyright of Journal of Elastomers & Plastics 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.