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pmid: 32173928
AbstractIntegrating self‐healing capabilities into soft electronic devices and sensors is important for increasing their reliability, longevity, and sustainability. Although some advances in self‐healing soft electronics have been made, many challenges have been hindering their integration in digital electronics and their use in real‐world conditions. Herein, an electronic skin (e‐skin) with high sensing performance toward temperature, pressure, and pH levels—both at ambient and/or in underwater conditions is reported. The e‐skin is empowered with a novel self‐repair capability that consists of an intrinsic mechanism for efficient self‐healing of small‐scale damages as well as an extrinsic mechanism for damage mapping and on‐demand self‐healing of big‐scale damages in designated locations. The overall design is based on a multilayered structure that integrates a neuron‐like nanostructured network for self‐monitoring and damage detection and an array of electrical heaters for selective self‐repair. This system has significantly enhanced self‐healing capabilities; for example, it can decrease the healing time of microscratches from 24 h to 30 s. The electronic platform lays down the foundation for the development of a new subcategory of self‐healing devices in which electronic circuit design is used for self‐monitoring, healing, and restoring proper device function.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 131 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
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