Self-healing electronic skin with high fracture strength and toughness

Jaehoon Jung, Sunwoo Lee, Hyunjun Kim, Wonbeom Lee, Jooyeun Chong, Insang You () and Jiheong Kang ()
Additional contact information
Jaehoon Jung: Korea Advanced Institute of Science and Technology (KAIST)
Sunwoo Lee: Korea Advanced Institute of Science and Technology (KAIST)
Hyunjun Kim: Seoul National University
Wonbeom Lee: Korea Advanced Institute of Science and Technology (KAIST)
Jooyeun Chong: Korea Advanced Institute of Science and Technology (KAIST)
Insang You: Waterloo
Jiheong Kang: Seoul National University

Nature Communications, 2024, vol. 15, issue 1, 1-10

Abstract: Abstract Human skin is essential for perception, encompassing haptic, thermal, proprioceptive, and pain-sensing functions through ion movement. Additionally, it is mechanically resilient and self-healing for protection. Inspired by these unique properties, researchers have attempted to develop stretchable, self-healing sensors based on ion dynamics. However, most self-healing sensors reported to date suffer from low fracture strength and toughness. In this work, we present an ion-based self-healing electronic skin with exceptionally high fracture strength and toughness. We enhanced self-healing polymers and ionic conductors by introducing two types of orthogonal dynamic crosslinking bonds: dynamic aromatic disulfide bonds and 2-ureido-4-pyrimidone moieties. These dynamic bonds provide autonomous self-healing and high mechanical toughness even in the presence of ionic liquids. As a result, our self-healing polymer and self-healing ionic conductor exhibit remarkable stretchability (700%, 850%), fracture strength (34 MPa, 30 MPa), and toughness (78.5 MJ/m3, 87.3 MJ/m3), the highest values reported among self-healing ionic conductors to date. Using our materials, we developed various fully self-healing sensors and a soft gripper capable of autonomously recovering from mechanical damage. By integrating these components, we created a comprehensive self-healing electronic skin suitable for soft robotics applications.

Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-024-53957-0 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-53957-0

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-024-53957-0

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().