热塑性聚氨酯
丙酮
材料科学
复合材料
溶解度参数
醋酸
聚氨酯
聚合物
乙醚
溶解度
残余应力
化学工程
弹性体
有机化学
化学
工程类
作者
Changchun Wang,Bo Kou,Zusheng Hang,Xuejuan Zhao,Tianxuan Lu,Ziqi Wu,Jinpeng Zhang
出处
期刊:Pigment & Resin Technology
[Emerald (MCB UP)]
日期:2017-10-26
卷期号:47 (1): 7-13
被引量:8
标识
DOI:10.1108/prt-03-2017-0021
摘要
Purpose This study aims to present that the chemo-responsive shape recovery of thermoplastic polyurethane (TPU) is tunable by solvents with different solubility parameters, and it is generic for chemo-responsive shape-memory polymer and its composites. Design/methodology/approach Two kinds of commercial TPU samples with different thicknesses were prepared by panel vulcanizer and injection molding (an industrial manner) to investigate their chemo-responsive shape memory properties in acetic ether and acetone. Findings Results showed that all of TPU films with different thicknesses can fully recover their original shapes weather they recover in acetic ether or acetone. But the recovery time of TPU films in acetone is greatly reduced, especially for the twisting samples. The residual strains of recovery TPU samples after extension reduce obviously. Research limitations/implications The great decrement of recovery time is related to two factors. One is due to the bigger solubility parameter of acetone with higher dipole moment compared with those of acetic ether, and the other is the remained internal stress of TPU films after preparation. The internal stress is identified to have an effect on the shape-memory properties by comparing the recovery process of samples with/without annealing. The reduced residual strains of recovery TPU samples after extension is due to the increasing mobility of polymer segments after molecules of acetic ether penetrates into the polymeric chains. Originality/value This is a universal strategy to control the recovery process of shape-memory materials or composites. The underlying mechanism is generic and should be applicable to chemo-responsive shape-memory polymers or their composites.
科研通智能强力驱动
Strongly Powered by AbleSci AI