Rahmatabadi, D, Yousefi, MA, Shamsolhodaei, S, Baniassadi, M, Abrinia, K, Bodaghi, M ORCID: https://orcid.org/0000-0002-0707-944X and Baghani, M,
2025.
4D printing of polyethylene glycol‐grafted carbon nanotube‐reinforced polyvinyl chloride–polycaprolactone composites for enhanced shape recovery and thermomechanical performance.
Advanced Intelligent Systems.
ISSN 2640-4567
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Abstract
4D printing with carbon nanotube (CNT)-reinforced polymers enables advanced shape-changing materials but faces challenges in CNT dispersion and performance. This study addresses these limitations by functionalizing CNTs with polyethylene glycol (PEG), significantly enhancing dispersion and interfacial bonding within biocompatible polyvinyl chloride (PVC)-polycaprolactone (PCL) composites. The composites, tailored for biomedical applications with a glass transition temperature (Tg) of 37–41 °C, exhibit enhanced mechanical, thermal, and shape-memory properties. At 0.5 wt% CNT, the composite achieves a 25% increase in tensile strength, 95.78% shape fixity, and a 5-s recovery time, offering an optimal balance of strength, flexibility, and rapid shape recovery. Higher CNT concentrations (5 wt%) further improve thermal stability, increasing the decomposition temperature by 20 °C and storage modulus by 670 MPa, although ductility is reduced. PEG grafting prevents CNT agglomeration, enabling high filler loading without compromising printability, as confirmed through uniform nanoparticle dispersion and defect-free fused deposition modeling (FDM)-printed structures. These intelligent composites combine biocompatibility, durability, and excellent shape-memory performance, making them suitable for diverse structural and biomedical applications, such as adaptive medical devices, ergonomic shoe soles, and wearable biosensors. This novel material provides a versatile platform for high-performance, 4D-printed intelligent systems that address current challenges in polymer nanocomposites and advance engineering and biomedical innovations.
Item Type: | Journal article |
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Publication Title: | Advanced Intelligent Systems |
Creators: | Rahmatabadi, D., Yousefi, M.A., Shamsolhodaei, S., Baniassadi, M., Abrinia, K., Bodaghi, M. and Baghani, M. |
Publisher: | Wiley |
Date: | 1 April 2025 |
ISSN: | 2640-4567 |
Identifiers: | Number Type 10.1002/aisy.202500113 DOI 2423378 Other |
Rights: | © 2025 The Author(s). Advanced Intelligent Systems published by Wiley-VCH GmbH. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
Divisions: | Schools > School of Science and Technology |
Record created by: | Laura Borcherds |
Date Added: | 07 Apr 2025 08:35 |
Last Modified: | 07 Apr 2025 08:35 |
URI: | https://irep.ntu.ac.uk/id/eprint/53360 |
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