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A self-healing electrically conductive organogel composite

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Self-healing hydrogels use spontaneous intermolecular forces to recover from physical damage caused by extreme strain, pressure or tearing. Such materials are of potential use in soft robotics and tissue engineering, but they have relatively low electrical conductivity, which limits their application in stretchable and mechanically robust circuits. Here we report an organogel composite that is based on poly(vinyl alcohol)–sodium borate and has high electrical conductivity (7 × 10⁴ S m⁻¹), low stiffness (Young’s modulus of ~20 kPa), high stretchability (strain limit of >400%) and spontaneous mechanical and electrical self-healing. The organogel matrix is embedded with silver microflakes and gallium-based liquid metal microdroplets, which form a percolating network, leading to high electrical conductivity in the material. We also overcome the rapid drying problem of the hydrogel material system by replacing water with an organic solvent (ethylene glycol), which avoids dehydration and property changes for over 24 h in an ambient environment. We illustrate the capabilities of the self-healing organogel composite by using it in a soft robot, a soft circuit and a reconfigurable bioelectrode.
Mechanical, electrical and self-healing properties a, Dynamic mechanical analysis test of the composites after dry annealing for various freezing times (10 min, 20 min and 30 min). b, Tensile test of the composites after dry annealing for various freezing times (10 min, 20 min and 30 min). c, Cyclic test of successive increasing strain of the composite after dry annealing for 10 min of freezing. d, Electrical conductivity comparison of PVA–Borax organogel, Ag–LM–PVA composite and Ag–LM–PVA composite after dry annealing. Boxes indicate the average value among three test specimens, and whiskers correspond to the s.d. among three test specimens. Insets: SEM images of the composite without and after dry annealing. Note that the two images are from two different samples. Scale bars, 20 µm. e, Change in electrical conductivity of three samples of Ag–LM–PVA composite after dry annealing for 24 h under ambient conditions. f, Electromechanical coupling of three Ag–LM–PVA composites after dry annealing. The solid line represents the average value, and the shaded region represents the s.d. calculated among the three samples. g, Stress–strain curves of pristine and post-healed composites, demonstrating the mechanical self-healing property. h, Electrical self-healing property of the composite (10-min freezing time). Inset: optical image of the composite after self-healing. i, Electromechanical coupling test after self-healing. Inset: schematic of the test method.
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Nature Electronics | Volume 6 | March 2023 | 206–215 206
nature electronics
Article
https://doi.org/10.1038/s41928-023-00932-0
A self-healing electrically conductive
organogel composite
Yongyi Zhao1,2, Yunsik Ohm  1,2, Jiahe Liao1,3, Yichi Luo1,2, Huai-Yu Cheng4,
Phillip Won1,2, Peter Roberts1,2, Manuel Reis Carneiro  2,5,
Mohammad F. Islam  4, Jung Hyun Ahn5, Lynn M. Walker6 &
Carmel Majidi  1,2,3,4
Self-healing hydrogels use spontaneous intermolecular forces to recover
from physical damage caused by extreme strain, pressure or tearing. Such
materials are of potential use in soft robotics and tissue engineering,
but they have relatively low electrical conductivity, which limits their
application in stretchable and mechanically robust circuits. Here we report
an organogel composite that is based on poly(vinyl alcohol)–sodium
borate and has high electrical conductivity (7 × 104 S m−1), low stiness
(Young’s modulus of ~20 kPa), high stretchability (strain limit of >400%)
and spontaneous mechanical and electrical self-healing. The organogel
matrix is embedded with silver microakes and gallium-based liquid metal
microdroplets, which form a percolating network, leading to high electrical
conductivity in the material. We also overcome the rapid drying problem
of the hydrogel material system by replacing water with an organic solvent
(ethylene glycol), which avoids dehydration and property changes for
over 24 h in an ambient environment. We illustrate the capabilities of the
self-healing organogel composite by using it in a soft robot, a soft circuit and
a recongurable bioelectrode.
Self-healing materials that are soft, stretchable and electrically con-
ductive are of potential use in soft robotics1, soft electronics2 and
medical devices that require mechanical properties that match those
of natural biological tissue
3
. Among various candidate materials
4,5
,
self-healing hydrogels are particularly promising due to their combi-
nation of high mechanical deformability (strain as high as 2,000%
6
),
low stiffness (Young’s modulus of a few kilopascals
7
), recyclability
8
and biocompatibility9,10. A fluorine-rich ionic gel has, for example,
been developed that can support strains of up to 2,000% and uses
ion–dipole interactions to achieve rapid electrical and mechani-
cal self-healing in various aqueous conditions6. Meanwhile, an
acrylate-based polymeric organogel has been shown to offer robust
adhesion and optical transparency
11
. However, although these material
systems possess low mechanical compliance, high stretchability and
rapid self-healing, they do not exhibit sufficient electrical conduc-
tivity for applications in soft digital circuits and power electronics
12
.
This is because they are only ionically conductive, with a volumetric
conductivity of ~10−3 S cm−1, which is far less than what is required for
digital electronics.
To enhance the conductivity of hydrogels, conductive fillers—
such as metallic micro/nanoparticles,1316, graphene17,18, carbon nano-
tubes1921 and conductive polymers22,23—have been added into the
hydrogel matrix
24
. However, these composites typically require a high
volume fraction of conductive particles to achieve electrically per-
colating pathways
25
. This can lead to substantial degradation of the
mechanical properties—that is, lower strain limit, increased elastic
Received: 19 June 2022
Accepted: 31 January 2023
Published online: 9 March 2023
Check for updates
1Soft Machines Lab, Carnegie Mellon University, Pittsburgh, PA, USA. 2Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
3Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA. 4Materials Science & Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
5Institute of Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, Coimbra, Portugal. 6Department of
Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, USA. e-mail: cmajidi@andrew.cmu.edu
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