4.8 Article

Self-powered high-sensitivity all-in-one vertical tribo-transistor device for multi-sensing-memory-computing

Journal

NATURE COMMUNICATIONS
Volume 13, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41467-022-35628-0

Keywords

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Funding

  1. National Natural Science Foundation of China [U21A20497]
  2. Natural Science Foundation for Distinguished Young Scholars of Fujian Province [2020J06012]
  3. Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China [2021ZZ129]

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A self-powered vertical tribo-transistor (VTT) based on MXenes has been developed for multi-sensing-memory-computing function and multi-task emotion recognition. This device exhibits a simple structure and high sensitivity, efficiency, and accuracy.
Devices with sensing-memory-computing capability for the detection, recognition and memorization of real time sensory information could simplify data conversion, transmission, storage, and operations between different blocks in conventional chips, which are invaluable and sought-after to offer critical benefits of accomplishing diverse functions, simple design, and efficient computing simultaneously in the internet of things (IOT) era. Here, we develop a self-powered vertical tribo-transistor (VTT) based on MXenes for multi-sensing-memory-computing function and multi-task emotion recognition, which integrates triboelectric nanogenerator (TENG) and transistor in a single device with the simple configuration of vertical organic field effect transistor (VOFET). The tribo-potential is found to be able to tune ionic migration in insulating layer and Schottky barrier height at the MXene/semiconductor interface, and thus modulate the conductive channel between MXene and drain electrode. Meanwhile, the sensing sensitivity can be significantly improved by 711 times over the single TENG device, and the VTT exhibits excellent multi-sensing-memory-computing function. Importantly, based on this function, the multi-sensing integration and multi-model emotion recognition are constructed, which improves the emotion recognition accuracy up to 94.05% with reliability. This simple structure and self-powered VTT device exhibits high sensitivity, high efficiency and high accuracy, which provides application prospects in future human-mechanical interaction, IOT and high-level intelligence.

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