Synthesis of Novel Shape Memory Thermoplastic Polyurethanes (SMTPUs) from Bio-Based Materials for Application in 3D/4D Printing Filaments

Author:

Jung Yang-Sook12,Lee Sunhee3ORCID,Park Jaehyeung2,Shin Eun-Joo1ORCID

Affiliation:

1. Department of Organic Materials and Polymer Engineering, Dong-A University, Busan 49315, Republic of Korea

2. Department of Biofibers and Biomaterials Science, Kyungpook National University, Daegu 41566, Republic of Korea

3. Department of Fashion Design, Dong-A University, Busan 49315, Republic of Korea

Abstract

Bio-based thermoplastic polyurethanes have attracted increasing attention as advanced shape memory materials. Using the prepolymer method, novel fast-responding shape memory thermoplastic polyurethanes (SMTPUs) were prepared from 100% bio-based polyester polyol, poly-propylene succinate derived from corn oil, diphenyl methane diisocyanate, and bio-based 1,3-propanediol as a chain extender. The morphologies of the SMTPUs were investigated by Fourier transform infrared spectroscopy, atomic force microscopy, and X-ray diffraction, which revealed the interdomain spacing between the hard and soft phases, the degree of phase separation, and the intermixing level between the hard and soft phases. The thermal and mechanical properties of the SMTPUs were also investigated, wherein a high hard segment content imparted unique properties that rendered the SMTPUs suitable for shape memory applications at varying temperatures. More specifically, the SMTPUs exhibited a high level of elastic elongation and good mechanical strength. Following compositional optimization, a tensile strength of 24–27 MPa was achieved, in addition to an elongation at break of 358–552% and a hardness of 84–92 Shore A. Moreover, the bio-based SMTPU exhibited a shape recovery of 100%, thereby indicating its potential for use as an advanced temperature-dependent shape memory material with an excellent shape recoverability.

Funder

National Research Foundation of Korea

Publisher

MDPI AG

Subject

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