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同济大学材料科学与工程学院,上海,201804
Published:20 January 2016,
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Jiang Du, Xue-liang Yao, Yan-liang Liu, De-cheng Wan, Hong-ting Pu. Novel Blending Methods for Preparation of Shape Memory Polymers. [J]. Acta Polymerica Sinica (1):14-24(2016)
DOI:
Jiang Du, Xue-liang Yao, Yan-liang Liu, De-cheng Wan, Hong-ting Pu. Novel Blending Methods for Preparation of Shape Memory Polymers. [J]. Acta Polymerica Sinica (1):14-24(2016) DOI: 10.11777/j.issn1000-3304.2016.15190.
形状记忆高分子材料(shape memory polymers
SMPs)作为一种特点突出、性能优良的智能材料具有极高的研究和实用价值
受到各国研究人员的广泛关注
新的制备方法和材料体系不断涌现
显示出巨大的发展潜力.本文总结了近年来出现的以共混方式为基础的多种重要制备方法
包括聚合物与聚合物直接熔融共混、溶液共混、借助增容剂或交联剂进行共混、通过新型微层共挤出技术进行交替层状共混、以及利用静电纺丝技术进行三维网络结构共混等.相较于化学合成方法
这些共混方法具有操作简单、原料易得、制备效率高、产品性能调节方便、制备过程更为环保等优点
并且能够得到与化学合成方法性能相同甚至更好的产品
优势突出
是今后制备形状记忆高分子材料的一大趋势.本文从这些新型共混材料的制备过程、微观结构、形状记忆性能等角度详细分析了不同方法的特点和优势.这些近年来出现的共混制备方法对于形状记忆高分子材料的发展和未来应用将是至关重要的.
As a sort of smart materials
shape memory polymers (SMPs) have outstanding features and excellent performance with high research and practical values.Especially in recent years
novel methods and new material systems for SMPs spring up at an increasing rate
showing great potential for development.This article summarizes the latest progress in blending methods
including direct blending of polymers
blending with the aid of compatibilizers
blending by microlayer coextrusion
and blending based on the 3D networks from electrospinning.Compared to chemical synthesis methods
these blending methods are efficient
simple to operate
available for wider diversity of raw materials
convenient to manipulate product properties
environment-friendly
and achieve products with equal or better performance
which facilitate blending method to be a major trend of preparing SMPs in the future.In this article
the features and advantages of different blending methods are analyzed from the aspects of preparation processes
microstructures and shape memory properties of the products
with the purpose of spurring future developments.
形状记忆高分子材料共混制备方法相结构形状记忆性能
Hape memory polymersBlending methodsPhase structureShape memory performance
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