Self‐Healing Functional Electronic Devices

Gai, Yansong; Li, Hu; Zhou, Li

doi:10.1002/smll.202101383

Cited by 67 publications

(51 citation statements)

References 132 publications

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“…Similar to the development of the capsule-based method, the activating mechanisms of the microvascular approach have been validated and the repairing capability has been characterized. Importantly, the vascular technique enables recurrent repairing of successive fracture events because of access to a vast reservoir of healing agent and the ability to replenish the network ( Figure 2 b) [ 45 ].…”

Section: Self-healing Mechanismsmentioning

confidence: 99%

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Self-Healing Materials for Electronics Applications

Mashkoor

Lee

et al. 2022

IJMS

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Self-healing materials have been attracting the attention of the scientists over the past few decades because of their effectiveness in detecting damage and their autonomic healing response. Self-healing materials are an evolving and intriguing field of study that could lead to a substantial increase in the lifespan of materials, improve the reliability of materials, increase product safety, and lower product replacement costs. Within the past few years, various autonomic and non-autonomic self-healing systems have been developed using various approaches for a variety of applications. The inclusion of appropriate functionalities into these materials by various chemistries has enhanced their repair mechanisms activated by crack formation. This review article summarizes various self-healing techniques that are currently being explored and the associated chemistries that are involved in the preparation of self-healing composite materials. This paper further surveys the electronic applications of self-healing materials in the fields of energy harvesting devices, energy storage devices, and sensors. We expect this article to provide the reader with a far deeper understanding of self-healing materials and their healing mechanisms in various electronics applications.

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Section: Self-healing Mechanismsmentioning

confidence: 99%

“…All of these factors strongly influence the lifecycle of flexible batteries [ 196 ]. Hence, the development of both macroscopically and microscopically self-healable LIBs is important for improving their lifecycle and cycle stability [ 45 , 198 ].…”

Section: Applications Of Self-healing Materialsmentioning

confidence: 99%

Self-Healing Materials for Electronics Applications

Mashkoor

Lee

et al. 2022

IJMS

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“…[38] In terms of flexible wearable sensors, the remarkable process has been made with different structures and materials in the past few years. [39][40][41] Till now, several basic approaches are adopted for diversified HMIs and robotic perception, including conductive nanocomposites, [42,43] capacitive variation, [44,45] piezoelectric or triboelectric effect, [46,47] etc. For instance, a cutaneous mechanoreceptor using capacitive variation was developed for soft machines, physiological sensing, and amputee prostheses, showing its outstanding sensitivity and wide pressure range.…”

Section: Introductionmentioning

confidence: 99%

Wearable Triboelectric Sensors Enabled Gait Analysis and Waist Motion Capture for IoT‐Based Smart Healthcare Applications

et al. 2021

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Gait and waist motions always contain massive personnel information and it is feasible to extract these data via wearable electronics for identification and healthcare based on the Internet of Things (IoT). There also remains a demand to develop a cost‐effective human‐machine interface to enhance the immersion during the long‐term rehabilitation. Meanwhile, triboelectric nanogenerator (TENG) revealing its merits in both wearable electronics and IoT tends to be a possible solution. Herein, the authors present wearable TENG‐based devices for gait analysis and waist motion capture to enhance the intelligence and performance of the lower‐limb and waist rehabilitation. Four triboelectric sensors are equidistantly sewed onto a fabric belt to recognize the waist motion, enabling the real‐time robotic manipulation and virtual game for immersion‐enhanced waist training. The insole equipped with two TENG sensors is designed for walking status detection and a 98.4% identification accuracy for five different humans aiming at rehabilitation plan selection is achieved by leveraging machine learning technology to further analyze the signals. Through a lower‐limb rehabilitation robot, the authors demonstrate that the sensory system performs well in user recognition, motion monitoring, as well as robot and gaming‐aided training, showing its potential in IoT‐based smart healthcare applications.

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“…16 Inspired by nature, developing artificial materials capable of healing themselves with recovered mechanical properties and functions is of great interest. 17 Advancement of polymer science and supramolecular chemistry allowed fabrication of self-healing materials with elasticity, 18,19 sensing ability, 20–22 superhydrophobicity, 23–25 electrical conductivity, 26,27 proton conductivity, 28,29 discoloration ability, 30,31 and so forth. 32,33 These self-healing functional materials can heal damage spontaneously or under external stimuli, greatly improving their service life and reliability.…”

Section: Introductionmentioning

confidence: 99%