Preparation and characterization of glass fiber-reinforced polyethylene terephthalate/linear low density polyethylene ( GF- PET/ LLDPE) composites.
Saved in:
| Title: | Preparation and characterization of glass fiber-reinforced polyethylene terephthalate/linear low density polyethylene ( GF- PET/ LLDPE) composites. |
|---|---|
| Authors: | Alqaflah, Abdulmajeed M.1, Alotaibi, Muhammad L.1, Aldossery, Jiyad N.2, Alghamdi, Mohammed S.3, Alsewailem, Fares D.1 fsewailm@kacst.edu.sa |
| Source: | Polymers for Advanced Technologies. Jan2018, Vol. 29 Issue 1, p52-60. 9p. |
| Subjects: | Glass fibers, Polyethylene terephthalate, Low density polyethylene, Thermal properties, Thermoplastics |
| Abstract: | Polyethylene terephthalate (PET) was melt blended with linear low density polyethylene (LLDPE) and subsequently compounded with glass fibers (GF) as reinforcements at percentages ranging from 15 to 45 wt% of LLDPE and 5 to 30 wt% of GF. Thermal, morphological, and mechanical properties of the prepared composites were investigated. It was found that compounding PET/LLDPE blends with GF would be beneficial in producing composites that are thermally stable with good mechanical properties. For example, the impact strength of the composites containing 85/15 wt% (PET/LLDPE) at relatively high loading of GF, ie, from 15 to 30 wt%, was higher than that of the GF-reinforced neat PET. When increasing the percentage of LLDPE in the composites, the impact strength increased with increasing GF content, and this was also better than that of GF-reinforced PET whose impact strength drastically decreased upon increasing the GF%. The improvement in mechanical properties of the composite, we suggest, should be correlated with the morphologies of the composites where the visualized interface adhesion tended to be better at higher loadings of both LLDPE and GF. [ABSTRACT FROM AUTHOR] |
| Copyright of Polymers for Advanced Technologies is the property of Wiley-Blackwell 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.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!