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Skin‐Inspired Piezoelectric Tactile Sensor Array with Crosstalk‐Free Row+Column Electrodes for Spatiotemporally Distinguishing Diverse Stimuli
Author(s) -
Lin Weikang,
Wang Biao,
Peng Guoxiang,
Shan Yao,
Hu Hong,
Yang Zhengbao
Publication year - 2021
Publication title -
advanced science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.388
H-Index - 100
ISSN - 2198-3844
DOI - 10.1002/advs.202002817
Subject(s) - crosstalk , electrode , piezoelectricity , materials science , tactile sensor , column (typography) , optoelectronics , nanotechnology , biomedical engineering , computer science , acoustics , electronic engineering , chemistry , physics , telecommunications , composite material , artificial intelligence , engineering , robot , frame (networking)
Real‐time detection and differentiation of diverse external stimuli with one tactile senor remains a huge challenge and largely restricts the development of electronic skins. Although different sensors have been described based on piezoresistivity, capacitance, and triboelectricity, and these devices are promising for tactile systems, there are few, if any, piezoelectric sensors to be able to distinguish diverse stimuli in real time. Here, a human skin‐inspired piezoelectric tactile sensor array constructed with a multilayer structure and row+column electrodes is reported. Integrated with a signal processor and a logical algorithm, the tactile sensor array achieves to sense and distinguish the magnitude, positions, and modes of diverse external stimuli, including gentle slipping, touching, and bending, in real time. Besides, the unique design overcomes the crosstalk issues existing in other sensors. Pressure sensing and bending sensing tests show that the proposed tactile sensor array possesses the characteristics of high sensitivity (7.7 mV kPa −1 ), long‐term durability (80 000 cycles), and rapid response time (10 ms) (less than human skin). The tactile sensor array also shows a superior scalability and ease of massive fabrication. Its ability of real‐time detection and differentiation of diverse stimuli for health monitoring, detection of animal movements, and robots is demonstrated.

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