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Neuromorphic Computing-Assisted Triboelectric Capacitive-Coupled Tactile Sensor Array for Wireless Mixed Reality Interaction.
Xie, Xinkai; Wang, Qinan; Zhao, Chun; Sun, Qilei; Gu, Haicheng; Li, Junyan; Tu, Xin; Nie, Baoqing; Sun, Xuhui; Liu, Yina; Lim, Eng Gee; Wen, Zhen; Wang, Zhong Lin.
Afiliação
  • Xie X; Institute of Functional Nano and Soft Materials (FUNSOM), Joint International Research Laboratory of Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123, P. R. China.
  • Wang Q; Department of Electrical and Electronic Engineering, School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou 215123, P. R. China.
  • Zhao C; Department of Electrical and Electronic Engineering, University of Liverpool, Liverpool L693GJ, U.K.
  • Sun Q; Joint International Research Laboratory of Information Display and Visualization, School of Electronic Science and Engineering, Southeast University, Nanjing 210096, P. R. China.
  • Gu H; Department of Electrical and Electronic Engineering, School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou 215123, P. R. China.
  • Li J; Department of Electrical and Electronic Engineering, University of Liverpool, Liverpool L693GJ, U.K.
  • Tu X; Department of Electrical and Electronic Engineering, School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou 215123, P. R. China.
  • Nie B; Department of Electrical and Electronic Engineering, School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou 215123, P. R. China.
  • Sun X; Institute of Functional Nano and Soft Materials (FUNSOM), Joint International Research Laboratory of Carbon-Based Functional Materials and Devices, Soochow University, Suzhou 215123, P. R. China.
  • Liu Y; Department of Electrical and Electronic Engineering, School of Advanced Technology, Xi'an Jiaotong-Liverpool University, Suzhou 215123, P. R. China.
  • Lim EG; Department of Electrical and Electronic Engineering, University of Liverpool, Liverpool L693GJ, U.K.
  • Wen Z; Department of Electrical and Electronic Engineering, University of Liverpool, Liverpool L693GJ, U.K.
  • Wang ZL; School of Electronic and Information Engineering, Soochow University, Suzhou 215006, P. R. China.
ACS Nano ; 18(26): 17041-17052, 2024 Jul 02.
Article em En | MEDLINE | ID: mdl-38904995
ABSTRACT
Flexible tactile sensors show promise for artificial intelligence applications due to their biological adaptability and rapid signal perception. Triboelectric sensors enable active dynamic tactile sensing, while integrating static pressure sensing and real-time multichannel signal transmission is key for further development. Here, we propose an integrated structure combining a capacitive sensor for static spatiotemporal mapping and a triboelectric sensor for dynamic tactile recognition. A liquid metal-based flexible dual-mode triboelectric-capacitive-coupled tactile sensor (TCTS) array of 4 × 4 pixels achieves a spatial resolution of 7 mm, exhibiting a pressure detection limit of 0.8 Pa and a fast response of 6 ms. Furthermore, neuromorphic computing using the MXene-based synaptic transistor achieves 100% recognition accuracy of handwritten numbers/letters within 90 epochs based on dynamic triboelectric signals collected by the TCTS array, and cross-spatial information communication from the perceived multichannel tactile data is realized in the mixed reality space. The results illuminate considerable application possibilities of dual-mode tactile sensing technology in human-machine interfaces and advanced robotics.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: ACS Nano Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: ACS Nano Ano de publicação: 2024 Tipo de documento: Article