Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

Eco-Friendly and High-Performance Bio-Polyurethane Adhesives from Vegetable Oils: A Review.

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
اقرأ على الانترنت اقرأ أكثر حفظ في قائمتي
  • معلومة اضافية
    • نبذة مختصرة :
      Current petrochemical-based adhesives adversely affect the environment through substantial volatile organic compound (VOC) emissions during production, contributing to air pollution and climate change. In contrast, vegetable oils extracted from bio-resources provide a compelling alternative owing to their renewability, abundance, and compatibility with adhesive formulation chemistry. This review aimed to critically examine and synthesize the existing scholarly literature on environmentally friendly, sustainable, and high-performance polyurethane adhesives (PUAs) developed from vegetable oils. The use of PUAs derived from vegetable oils promises to provide a long-term replacement while simultaneously maintaining or improving adhesive properties. This quality renders these adhesives appropriate for widespread use in various sectors, including construction, automotive manufacturing, packaging, textile, and footwear industries. This review intended to perform a comprehensive assessment and integration of the existing research, thereby identifying the raw materials, strengths, weaknesses, and gaps in knowledge concerning vegetable oil-based PUAs. In doing so, it responded to these gaps and proposes potential avenues for future research. Therefore, this review accomplishes more than merely evaluating the existing research; it fosters the advancement of greener PUA technologies by identifying areas for improvement and innovation towards more sustainable industrial practices by showcasing vegetable oil-based PUAs as viable, high-performance alternatives to their petroleum-based counterparts. [ABSTRACT FROM AUTHOR]
    • نبذة مختصرة :
      Copyright of Polymers (20734360) is the property of MDPI 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.)