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Mechanically Robust and UV-Curable Shape-Memory Polymers for Digital Light Processing Based 4D Printing

Zhang, Biao, Li, Honggeng, Cheng, Jianxiang, Ye, Haitao, Sakhaei, Amir Hosein, Yuan, Chao, Rao, Ping, Zhang, Yuan-Fang, Chen, Zhe, Wang, Rong, and others. (2021) Mechanically Robust and UV-Curable Shape-Memory Polymers for Digital Light Processing Based 4D Printing. Advanced Materials, . ISSN 0935-9648. (doi:10.1002/adma.202101298) (KAR id:88799)

Abstract

4D printing is an emerging fabrication technology that enables 3D printed structures to change configuration over “time” in response to an environ-mental stimulus. Compared with other soft active materials used for 4D printing, shape-memory polymers (SMPs) have higher stiffness, and are compatible with various 3D printing technologies. Among them, ultraviolet (UV)-curable SMPs are compatible with Digital Light Processing (DLP)-based 4D printing to fabricate SMP-based structures with complex geometry and high-resolution. However, UV-curable SMPs have limitations in terms of mechanical performance, which significantly constrains their application ranges. Here, a mechanically robust and UV-curable SMP system is reported, which is highly deformable, fatigue resistant, and compatible with DLP-based 3D printing, to fabricate high-resolution (up to 2µm), highly complex 3D structures that exhibit large shape change (up to 1240%) upon heating. More importantly, the developed SMP system exhibits excellent fatigue resistance and can be repeatedly loaded more than 10000 times. The development of the mechanically robust and UV-curable SMPs significantly improves the mechanical performance of the SMP-based 4D printing structures, which allows them to be applied to engineering applications such as aerospace, smart furniture, and soft robots.

Item Type: Article
DOI/Identification number: 10.1002/adma.202101298
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA401 Materials engineering and construction
T Technology > TJ Mechanical engineering and machinery
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Amirhosein Sakhaei
Date Deposited: 22 Jun 2021 15:03 UTC
Last Modified: 17 May 2022 23:00 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/88799 (The current URI for this page, for reference purposes)

University of Kent Author Information

Sakhaei, Amir Hosein.

Creator's ORCID: https://orcid.org/0000-0001-6953-552X
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