Processing of Self-Healing Polymers for Soft Robotics

Ellen Roels (Corresponding author), Seppe Terryn, Fumiya Iida, Anton W. Bosman, Sophie Norvez, Frank Clemens, Guy Van Assche, Bram Vanderborght, Joost Brancart

Onderzoeksoutput: Bijdrage aan tijdschriftArtikel recenserenpeer review

85 Citaten (Scopus)
299 Downloads (Pure)


Soft robots are, due to their softness, inherently safe and adapt well to unstructured environments. However, they are prone to various damage types. Self-healing polymers address this vulnerability. Self-healing soft robots can recover completely from macroscopic damage, extending their lifetime. For developing healable soft robots, various formative and additive manufacturing methods have been exploited to shape self-healing polymers into complex structures. Additionally, several novel manufacturing techniques, noted as (re)assembly binding techniques that are specific to self-healing polymers, have been created. Herein, the wide variety of processing techniques of self-healing polymers for robotics available in the literature is reviewed, and limitations and opportunities discussed thoroughly. Based on defined requirements for soft robots, these techniques are critically compared and validated. A strong focus is drawn to the reversible covalent and (physico)chemical cross-links present in the self-healing polymers that do not only endow healability to the resulting soft robotic components, but are also beneficial in many manufacturing techniques. They solve current obstacles in soft robots, including the formation of robust multi-material parts, recyclability, and stress relaxation. This review bridges two promising research fields, and guides the reader toward selecting a suitable processing method based on a self-healing polymer and the intended soft robotics application.

Originele taal-2Engels
Aantal pagina's27
TijdschriftAdvanced Materials
Nummer van het tijdschrift1
StatusGepubliceerd - 6 jan. 2022

Bibliografische nota

Publisher Copyright:
© 2021 Wiley-VCH GmbH


This literature review was performed in relation to and funded by the EU FET Open RIA Project SHERO (828818), the EU Marie Curie ITN project SMART (860108) and the FWO SBO project AMSeR (G028218N). In addition, the authors gratefully acknowledge the FWO (Fonds Wetenschappelijk Onderzoek) for the personal grants of Roels (1S84120N), Terryn (1100416N), and Brancart (12W4719N).

European Union’s Horizon Europe research and innovation programme828818
European External Action Service860108, G028218N
Fonds Wetenschappelijk Onderzoek12W4719N, 1100416N, 1S84120N


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