Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/148769
Title: Inkjet‐printed iontronics for transparent, elastic, and strain‐insensitive touch sensing matrix
Authors: Gao, Dace
Wang, Jiangxin
Ai, Kaixuan
Xiong, Jiaqing
Li, Shaohui
Lee, Pooi See
Keywords: Engineering::Materials
Issue Date: 2020
Source: Gao, D., Wang, J., Ai, K., Xiong, J., Li, S. & Lee, P. S. (2020). Inkjet‐printed iontronics for transparent, elastic, and strain‐insensitive touch sensing matrix. Advanced Intelligent Systems, 2(7), 2000088-. https://dx.doi.org/10.1002/aisy.202000088
Project: Competitive Research Program /NRF-CRP13-2014-02 
NRF Investigatorship /NRF-NRFI2016-05 
Journal: Advanced Intelligent Systems 
Abstract: Next‐generation soft electronics are expected to be intrinsically stretchable, skin conformable, and fully integrated with diverse receptive modules to facilitate bidirectional human–machine interactions. Receptive touch sensors, in particular, should provide stable touch sensing outputs without being affected by external force‐induced strains. Herein, the design and fabrication of an iontronic touch sensing matrix, based on the fringe‐field capacitive mechanism, are introduced for robust touch mapping under large deformation. Enabled by our well‐formulated ink, ionic gel electrodes are directly inkjet printed onto elastomeric substrate to impart superior transparency and elasticity, and hybridized with a customized electronic circuitry through electrical double layers (EDLs) for the multiplexing and transduction of capacitive signals. Notably, the coplanar “interlocking‐diamond” electrode layout in a stretchable modality is adopted for the first time, which helps to boost touch sensitivity and suppress strain‐induced artifacts under static/dynamic deformations. For practical applications, the iontronic matrix demonstrates the capabilities of proximity sensing, multitouch detection, and gesture communication in real time, leading to a robust touch sensing interface that captures high‐fidelity signals during complex human–machine interactions.
URI: https://hdl.handle.net/10356/148769
ISSN: 2640-4567
DOI: 10.1002/aisy.202000088
Schools: School of Materials Science and Engineering 
Rights: © 2020 The Authors. Published by WILEY-VCH Verlag GmbH & Co. KGaA,Weinheim. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MSE Journal Articles

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