4.7 Article

Fully Fabric-Based Triboelectric Nanogenerators as Self-Powered Human-Machine Interactive Keyboards

Journal

NANO-MICRO LETTERS
Volume 13, Issue 1, Pages -

Publisher

SHANGHAI JIAO TONG UNIV PRESS
DOI: 10.1007/s40820-021-00621-7

Keywords

Triboelectric nanogenerators; Self-powered keyboard; Human-machine interface; Wearable electronics; Fully fabric-based

Funding

  1. National Key R & D Project from Minister of Science and Technology [2016YFA0202704]
  2. Beijing Municipal Natural Science Foundation [2212052]
  3. Shanghai Sailing Program [19S28101]
  4. Fundamental Research Funds for the Central Universities [19D128102]

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Combining flexible and stretchable textiles with self-powered sensors introduces a new perspective for wearable functional electronics and cyber security in the era of Internet of Things. A fully fabric-based triboelectric nanogenerator and a self-powered wearable keyboard are developed for biomechanical energy harvesting and real-time biometric authentication, showing promising applications in wearable electronics, self-powered sensors, cyber security, and artificial intelligences.
HighlightsA fully fabric-based mechanical energy harvester with a sandwich structure is developed, which can respond to the pressure change by the fall of leaves.A self-powered keyboard with the ability of biometric recognition is demonstrated, which is able to resist illegal intrusion by judging the keystroke behaviors. AbstractCombination flexible and stretchable textiles with self-powered sensors bring a novel insight into wearable functional electronics and cyber security in the era of Internet of Things. This work presents a highly flexible and self-powered fully fabric-based triboelectric nanogenerator (F-TENG) with sandwiched structure for biomechanical energy harvesting and real-time biometric authentication. The prepared F-TENG can power a digital watch by low-frequency motion and respond to the pressure change by the fall of leaves. A self-powered wearable keyboard (SPWK) is also fabricated by integrating large-area F-TENG sensor arrays, which not only can trace and record electrophysiological signals, but also can identify individuals' typing characteristics by means of the Haar wavelet. Based on these merits, the SPWK has promising applications in the realm of wearable electronics, self-powered sensors, cyber security, and artificial intelligences.

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