Tough and tunable shape memory PLA/PAE melt-blends actuated by temperature View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04-02

AUTHORS

Zhenfang Li, Kangning Li, Haihua He, Yufen Zhou, Zhicai He

ABSTRACT

Development of shape memory materials are very important due to their scientific and technological values. Typically, poly(lactic acid) (PLA) has received increasing attentions because of shape memory properties and biodegradability, however, its semi-crystalline structure restricts its shape recovery ratio and toughness both. Herein, we report a reinforced PLA-based elastomer material prepared by physical blending with different weight ratios of polyamide elastomer (PAE). After the modification, PLA/PAE elastomers show excellent shape recovery (> 99%) from ~ 25 to ~ 70 °C and toughness (impact strength ~ 50 kJ/m2). By regulating the weight ratio of PAE at 10 wt%, the resulting PLA/PAE elastomers showed relative low glass transition temperature (Tg) at ~ 61 °C versus pure PLA (~ 65 °C). Besides, the storage modulus (E′) decreased to ~ 8000 MPa (at 10 wt% PAE) indicated that PAE weakened the PLA crystallinity and promoted its toughness. Comparing with pure PLA, PLA/PAE elastomers showed almost 45% decrease on loss modulus (E″), which indicated that elasticity and shape recovery behavior have been promoted. With the increase of PAE ratio in PLA/PAE elastomers, the initial recovery temperature of blends showed decreasing trend, which indicated that blends are more helpful for shape recovery actuated by temperature. This work provided a new PLA/PAE elastomer with stronger toughness and faster thermo-induced shape recovery that may show great potential for fundamental research and biomedical applications. More... »

PAGES

1-8

Journal

TITLE

Iranian Polymer Journal

ISSUE

N/A

VOLUME

N/A

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13726-019-00706-6

DOI

http://dx.doi.org/10.1007/s13726-019-00706-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1113199953


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