An experimental–numerical study on shape memory behavior of PU/PCL/ZnO ternary blend

Author:

Abbasi-Shirsavar M1,Baghani M2ORCID,Taghavimehr M3,Golzar M1,Nikzad M1,Ansari M1,George D4

Affiliation:

1. Department of Mechanical Engineering, Tarbiat Modares University, Tehran, Iran

2. School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran

3. Department of Polymer Engineering, Tarbiat Modares University, Tehran, Iran

4. CNRS, ICube Laboratory, University of Strasbourg, Strasbourg, France

Abstract

Shape memory polymer composites have attracted significant attention due to novel properties and great applications. In this article, we focus on the fabrication and simulation of polyurethane/polycaprolactone nanocomposites. The polyurethane/polycaprolactone blends containing ZnO nanoparticles (5 to 30 wt%) are fabricated using a solution mixing and casting method. It is found that significant improvement of polyurethane/polycaprolactone composites in Young’s modulus is achieved by incorporating 20 wt% of ZnO nanoparticles; also, the results of the shape recovery ratio reveal that adding an optimum amount of ZnO (the reinforcement) can increase the shape recovery ratio (for 20 wt% of ZnO). These results could most likely be explained by the fact that some particles restrict the hard segment–soft segment interactions and provide more mobility to polycaprolactone components, while the other nanoparticles can act as the nucleating agent for polycaprolactone chains. A generalized Maxwell model is then used to examine the shape memory behavior of shape memory polymer composites. The dynamic mechanical thermal analysis results are utilized to define the model coefficients and the simulation is carried out to determine the shape recovery ratio. Simulation of this shape recovery ratio for shape memory polymer composites reveals that the numerical results are in good agreement with those of the experimental data.

Funder

Center for International Scientific Studies & Collaboration

Publisher

SAGE Publications

Subject

Mechanical Engineering,General Materials Science

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3