Thin, soft, 3D printing enabled crosstalk minimized triboelectric nanogenerator arrays for tactile sensing

Jian Li, Yiming Liu, Mengge Wu, Kuanming Yao, Zhan Gao, Yuyu Gao, Xingcan Huang, Tsz Hung Wong, Jingkun Zhou, Dengfeng Li, Hu Li, Jiyu Li, Ya Huang, Rui Shi, Junsheng Yu*, Xinge Yu*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

30 Citations (Scopus)
70 Downloads (CityUHK Scholars)

Abstract

With the requirements of self-powering sensors in flexible electronics, wearable triboelectric nanogenerators (TENGs) have attracted great attention due to their advantages of excellent electrical outputs and low-cost processing routes. The crosstalk effect between adjacent sensing units in TENGs significantly limits the pixel density of sensor arrays. Here, we present a skin-integrated, flexible TENG sensor array with 100 sensing units in an overall size of 7.5 cm × 7.5 cm that can be processed in a simple, low-cost, and scalable way enabled by 3D printing. All the sensing units show good sensitivity of 0.11 V/kPa with a wide range of pressure detection from 10 to 65 kPa, which allows to accurately distinguish various tactile formats from gentle touching (as low as 2 kPa) to hard pressuring. The 3D printing patterned substrate allows to cast triboelectric layers of polydimethylsiloxane in an independent sensing manner for each unit, which greatly suppresses the cross talk arising from adjacent sensing units, where the maximum crosstalk output is only 10.8%. The excellent uniformity and reproducibility of the sensor array offer precise pressure mapping for complicated pattern loadings, which demonstrates its potential in tactile sensing and human-machine interfaces. © 2022 The Authors. Publishing Services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.
Original languageEnglish
Pages (from-to)111-117
JournalFundamental Research
Volume3
Issue number1
Online published4 Feb 2022
DOIs
Publication statusPublished - Jan 2023

Funding

This work was supported in part by InnoHK Project on Project 2.2– AI-based 3D ultrasound imaging algorithm at Hong Kong Centre for Cerebro-cardiovascular Health Engineering (COCHE), in part by Research Grants Council of the Hong Kong Special Administrative Region (21210820, and 11213721), in part by Shenzhen Science and Technology Innovation Commission (JCYJ20200109110201713), and in part by National Natural Science Foundation of China (62122002, and U21A20492).

Research Keywords

  • Crosstalk suppression
  • Human-machine interfaces
  • Self-powering sensors
  • Tactile sensor
  • Triboelectricnanogenerators

Publisher's Copyright Statement

  • This full text is made available under CC-BY-NC-ND 4.0. https://creativecommons.org/licenses/by-nc-nd/4.0/

RGC Funding Information

  • RGC-funded

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