An Ultrastretchable and Self-Healable Nanocomposite Conductor Enabled by Autonomously Percolative Electrical Pathways
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Updated: Jan 25, 2026

Application of a Coupling Agent to Improve the Dielectric Properties of Polymer-Based Nanocomposites
Published on: September 19, 2020
Sun Hong Kim1, Hyunseon Seo2, Jiheong Kang3
1Department of Electrical and Computer Engineering, Inter-University Semiconductor Research Center , Seoul National University , 1-Gwanak-ro , Gwanak-gu, Seoul 08826 , Republic of Korea.
Abstract:
Both self-healable conductors and stretchable conductors have been previously reported. However, it is still difficult to simultaneously achieve high stretchability, high conductivity, and self-healability. Here, we observed an intriguing phenomenon, termed "electrical self-boosting", which enables reconstructing of electrically percolative pathways in an ultrastretchable and self-healable nanocomposite conductor (over 1700% strain). The autonomously reconstructed percolative pathways were directly verified by using microcomputed tomography and in situ scanning electron microscopy. The encapsulated nanocomposite conductor shows exceptional conductivity (average value: 2578 S cm-1; highest value: 3086 S cm-1) at 3500% tensile strain by virtue of efficient strain energy dissipation of the self-healing polymer and self-alignment and rearrangement of silver flakes surrounded by spontaneously formed silver nanoparticles and their self-assembly in the strained self-healing polymer matrix. In addition, the conductor maintains high conductivity and stretchability even after recovered from a complete cut. Besides, a design of double-layered conductor enabled by the self-bonding assembly allowed a conducting interface to be located on the neutral mechanical plane, showing extremely durable operations in a cyclic stretching test. Finally, we successfully demonstrated that electromyogram signals can be monitored by our self-healable interconnects. Such information was transmitted to a prosthetic robot to control various hand motions for robust interactive human-robot interfaces.
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