4D Printing of Electroactive Triple-Shape Composites

Triple-shape polymers can memorize two independent shapes during a controlled recovery process. This work reports the 4D printing of electro-active triple-shape composites based on thermoplastic blends. Composite blends comprising polyester urethane (PEU), polylactic acid (PLA), and multiwall carbon...

Full description

Saved in:
Bibliographic Details
Published inPolymers Vol. 15; no. 4; p. 832
Main Authors Razzaq, Muhammad Yasar, Gonzalez-Gutierrez, Joamin, Farhan, Muhammad, Das, Rohan, Ruch, David, Westermann, Stephan, Schmidt, Daniel F
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 07.02.2023
MDPI
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:Triple-shape polymers can memorize two independent shapes during a controlled recovery process. This work reports the 4D printing of electro-active triple-shape composites based on thermoplastic blends. Composite blends comprising polyester urethane (PEU), polylactic acid (PLA), and multiwall carbon nanotubes (MWCNTs) as conductive fillers were prepared by conventional melt processing methods. Morphological analysis of the composites revealed a phase separated morphology with aggregates of MWCNTs uniformly dispersed in the blend. Thermal analysis showed two different transition temperatures based on the melting point of the crystallizable switching domain of the PEU ( ~50 ± 1 °C) and the glass transition temperature of amorphous PLA ( ~61 ± 1 °C). The composites were suitable for 3D printing by fused filament fabrication (FFF). 3D models based on single or multiple materials were printed to demonstrate and quantify the triple-shape effect. The resulting parts were subjected to resistive heating by passing electric current at different voltages. The printed demonstrators were programmed by a thermo-mechanical programming procedure and the triple-shape effect was realized by increasing the voltage in a stepwise fashion. The 3D printing of such electroactive composites paves the way for more complex shapes with defined geometries and novel methods for triggering shape memory, with potential applications in space, robotics, and actuation technologies.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:2073-4360
2073-4360
DOI:10.3390/polym15040832