Toward Intelligent Materials with the Promise of Self-Healing Hydrogels in Flexible Devices

Abstract

Flexible sensors are revolutionizing wearable and implantable devices, with conductive hydrogels emerging as key materials due to their biomimetic structure, biocompatibility, tunable transparency, and stimuli-responsive electrical properties. However, their fragility and limited durability pose significant challenges for broader applications. Drawing inspiration from the self-healing capabilities of natural organisms like mussels, researchers are embedding self-repair mechanisms into hydrogels to improve their reliability and lifespan. This review highlights recent advances in self-healing (SH) conductive hydrogels, focusing on synthesis methods, healing mechanisms, and strategies to enhance multifunctionality. It also explores their wide-ranging applications, including in vivo signal monitoring, wearable biochemical sensors, supercapacitors, flexible displays, triboelectric nanogenerators, and implantable bioelectronics. While progress has been made, challenges remain in balancing self-healing efficiency, mechanical strength, and sensing performance. This review offers insights into overcoming these obstacles and discusses future research directions for advancing SH hydrogel-based bioelectronics, aiming to pave the way for durable, high-performance devices in next-generation wearable and implantable technologies.

Keywords: flexible electronics; intelligent materials; mechanism; self-healing hydrogels; sensing performance; wearable technologies.

Scheme 1

A schematic representation of the various crosslinking mechanisms of SH hydrogels.

Figure 1

Illustration of the tensile stress–strain behavior of RILNs-1/1 specimens under different conditions: (a) shows the stress–strain curves of specimens that underwent healing, reprocessing, and subsequent testing in water at neutral pH (pH = 7), demonstrating the material’s ability to restore mechanical integrity after processing; (b) highlights the pH-responsive mechanical properties by comparing the stress–strain curves of healed specimens tested in water at various pH levels; (c,d) focus on the material’s repeated SH performance in water across different pH conditions: (c) acidic (pH = 4), (d) neutral (pH = 7). These results emphasize the adaptability and robustness of RILNs-1/1 in diverse aqueous environments, making them suitable for applications requiring reliable performance across a wide pH range. Reproduced with permission from Ref. [39]. Copyright © 2020, American Chemical Society.

Figure 2

Schematic illustration of the MFHs synthesis via one-pot polymerization, highlighting key interactions within the multifunctional network, including covalent and noncovalent bonds, enabling enhanced mechanical properties, SH, and strain-sensitive conductivity. This figure is adopted from Ref. [43]. Copyright © 2019, American Chemical Society.

Figure 3

Real-time images of PAM-GOBC-0.05% hydrogel demonstrating its self-healing properties: (a) fresh sample, (b) cut sample, (c) healed sample after 20 h, (d) stretched healed sample, (e) double-twisted healed sample, and (f) bent healed sample. The SH mechanism of the PAA-GOBC composite hydrogel: (g) fresh sample, (h) cut sample, and (i) healed sample. The image is adopted from Ref. [2]. Copyright © 2022, Royal Society of Chemistry.

Figure 4

Tensile stress–strain curves of original and self-healed polymer-TA(S) hydrogels: (a) PVA-TA300(S) gels; (b) PAAm-TA300(S) gels. This figure is adopted from Ref. [67]. Copyright © 2018, American Chemical Society.

Figure 5

(a) Images illustrating the excellent stretchability and recovery behavior of PAM/PBA-IL/CNF hydrogel. (b) Demonstration of the hydrogel’s ability to lift a weight. (c) Tensile stress–strain curves along with stress and modulus values of PAM/PBA-IL/CNF hydrogels with varying CNF amounts. (d) Stress and modulus values of the hydrogels at different CNF contents. (e) Strain and toughness measurements of the hydrogels with varying CNF contents with error bars indicating the standard deviation (n = 3). (f,h) Cyclic loading–unloading curves of the PAM/PBA-IL/CNF2 hydrogel at strain levels of 100% and 1000% over 15 cycles. (g,i) Corresponding energy dissipation and energy dissipation ratios under the same conditions. (j) Real image of cyclic loading-unloading analysis. This figure is adopted from Ref. [86] Copyright © 2019, 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany.

Figure 6

(a) Digital images of PU-IL2 ionogel: (i) cut in half, (ii) healed after 2 h, and (iii) stretched. Scale bar: 1 cm. (b) Stress–strain curves of pristine PU-IL2 ionogel and healed samples after 0.5, 1, 2, and 3 h. Cyclic stability tests of healed I-skin under (c) 5% strain for 10,000 cycles and (d) 100% strain for 1000 cycles. Insets show enlarged views of relative resistance changes from the 11th to the 20th cycle and the last 10 cycles. This figure is taken from Ref. [88]. Copyright © 2020, WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany.

Figure 7

Numerous applications of SH hydrogels in soft bioelectronics.

Figure 8

(a) The finger-touch sensor that has been suggested. (a) Conductivity pictures showing a single finger making contact. (b) Images of conductivity displayed concurrently with a single finger [95]. Copyright 2023 @MDPI.

Figure 9

Ionic conductivity performance of hydrogel electrolytes. (a) EIS curves of hydrogel electrolytes containing different electrolytes. (b) EIS curves of PEI–PVA–Bn-LiCl hydrogel electrolytes with varying LiCl concentrations. (c) Optical images demonstrating the self-healing capability and electrical conductivity of the PEI–PVA–Bn-LiCl-1 hydrogel electrolyte. (d) Current variations in the PEI–PVA–Bn-LiCl-1 hydrogel electrolyte under different strain levels, with the inset depicting the circuit setup during sample stretching [126]. Copyright © 2020, American Chemical Society.