4.7 Article

Entanglement network formed in miscible PLA/PMMA blends and its role in rheological and thermo-mechanical properties of the blends

期刊

POLYMER
卷 80, 期 -, 页码 38-45

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.polymer.2015.10.037

关键词

Molecular entanglement; Rheological property; Shape memory polymer

资金

  1. China Scholarship Council

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The miscible amorphous/semi-crystalline polymer blends with shape memory potential has received increasing interests in recent years. In this work, the shape memory mechanism of the miscible amorphous PMMA/semi-crystalline PLA blends was investigated using thermo-mechanical and rheological approaches. With the incorporation of PMMA into PLA, a broad glass transition and increased glass transition temperature T-g were observed by differential scanning calorimetry (DSC) measurements. The broadening of glass transition is attributed to the local nanoscale heterogeneities in the miscible blend system which is related to the self-concentration of the components. The degree of molecular entanglement of the blends was derived based on the oscillatory rheological measurements, showing that the dissimilar chains are more likely to entangle with each other than the similar ones, and the entanglement density ve is enhanced with increased PMMA content up to 50% where a 100% recovery of the initial shape is yielded. After that, ve is reduced with the addition of PMMA. The mechanism underlying the shape memory property is further validated by performing the shape memory test on the PLA/PMMA blend films at respective Tg. It is evident that for the semi-crystalline blends (PLA rich), PLA crystallites and molecular entanglement provide physical cross-links for shape recording, while a negative effect of crystallinity on the shape recovery ratio is obtained due to the strain-induced crystallization and chain slippage between the crystalline and amorphous chains. In contrast, for the amorphous blends (PMMA rich), the shape recovery ratio shows a strong positive linear dependence on ve, and the entanglement network is regard as the most important factor in the shape memory performance. (C) 2015 Elsevier Ltd. All rights reserved.

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