3D-printable stimuli-responsive covalent adaptable networks based on dynamic reversible urea bonds

The current study focusses on three-dimensional (3D)-printing of switchable covalent adaptable networks (CANs), which are based on dynamic urea bonds. Digital light processing (DLP) has been utilized for the printing of 3D structures based on the CANs. Furthermore, CANs have been prepared by bulk polymerization for comparison. All resulting polymer networks were analyzed by various techniques such as mechanical testing (tensile strength, 3-point-flexure, rheology). Furthermore, their self-healing behavior was studied using a quantification via an indentation method. Particular noteworthy is the self-healing ability in complex 3D-printed structures. Finally, the shape-memory behavior was studied in detail. In this context, recovery rates up to 99% could be obtained. The polymers additionally feature excellent mechanical properties with tensile E-moduli between 0.34 GPa up to 3.43 GPa and flexural moduli between 0.52 GPa up to 0.71 GPa. • 3D-printing of stimuli responsive polymers is performed. • Incorporation of reversible cross-linker confirmed by Raman spectroscopy. • Printed polymers reveal high mechanical strength examined by tensile and flexure tests. • Excellent shape-memory behavior and self-healing efficiencies up to 100% are achieved.

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Publication Details

Journal
Polymer
Published
2026-04-21
DOI
https://doi.org/10.1016/j.polymer.2026.130096
Primary Topic
Polymer composites and self-healing
Type
article
Field-Weighted Citation Impact
0.00

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article

3D-printable stimuli-responsive covalent adaptable networks based on dynamic reversible urea bonds

Milena Jäger, Patrick Feßer, Michael Schmitt, Julius Bartels et al.
Polymer
Polymer composites and self-healing
article

3D-printable stimuli-responsive covalent adaptable networks based on dynamic reversible urea bonds

Milena Jäger, Patrick Feßer, Michael Schmitt, Julius Bartels, Jürgen Popp, Stefan Zechel, Michael F. Agyemang, Michael Klein, Martin D. Hager
article en

Abstract

The current study focusses on three-dimensional (3D)-printing of switchable covalent adaptable networks (CANs), which are based on dynamic urea bonds. Digital light processing (DLP) has been utilized for the printing of 3D structures based on the CANs. Furthermore, CANs have been prepared by bulk polymerization for comparison. All resulting polymer networks were analyzed by various techniques such as mechanical testing (tensile strength, 3-point-flexure, rheology). Furthermore, their self-healing behavior was studied using a quantification via an indentation method. Particular noteworthy is the self-healing ability in complex 3D-printed structures. Finally, the shape-memory behavior was studied in detail. In this context, recovery rates up to 99% could be obtained. The polymers additionally feature excellent mechanical properties with tensile E-moduli between 0.34 GPa up to 3.43 GPa and flexural moduli between 0.52 GPa up to 0.71 GPa. • 3D-printing of stimuli responsive polymers is performed. • Incorporation of reversible cross-linker confirmed by Raman spectroscopy. • Printed polymers reveal high mechanical strength examined by tensile and flexure tests. • Excellent shape-memory behavior and self-healing efficiencies up to 100% are achieved.

PolymerVol. 357
Helmholtz Institute Jena (DE), Helmholtz-Zentrum Berlin für Materialien und Energie (DE), Leibniz Institute of Photonic Technology (DE), Friedrich Schiller University Jena (DE)
Carl-Zeiss-Stiftung, Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 15%
Polymer composites and self-healing
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