2019
DOI: 10.1002/pola.29348
|View full text |Cite
|
Sign up to set email alerts
|

Membrane preparation from hyperbranched perfluorinated polymers

Abstract: In this research, membrane formation with hyperbranched perfluorinated polymers (HBFP) was investigated. To create a tough membrane, HBFP was blended and crosslinked with a tougher linear polymer. Blending only or crosslinking only was not sufficient to create a tough membrane, but combining blending with crosslinking was successful. Miscibility, phase separation, and thermal and mechanical properties were evaluated for a variety of systems. By using a toughening linear polymer with lower polarity, reduced pha… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2023
2023

Publication Types

Select...
5

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(1 citation statement)
references
References 40 publications
(91 reference statements)
0
1
0
Order By: Relevance
“…One of the most important classes of membrane materials is polymer membranes, because, in addition to their transport properties and selectivity, their important functional characteristics are strength, elasticity, and stability [ 10 ]. Perfluorinated materials have the best chemical stability among polymeric membranes, so they are constantly at the center of the attention of researchers and engineers working in the field of membrane technology [ 11 , 12 , 13 , 14 ].…”
Section: Introductionmentioning
confidence: 99%
“…One of the most important classes of membrane materials is polymer membranes, because, in addition to their transport properties and selectivity, their important functional characteristics are strength, elasticity, and stability [ 10 ]. Perfluorinated materials have the best chemical stability among polymeric membranes, so they are constantly at the center of the attention of researchers and engineers working in the field of membrane technology [ 11 , 12 , 13 , 14 ].…”
Section: Introductionmentioning
confidence: 99%