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Revisiting the thickness reduction approach for near-foldable capacitive touch sensors based on a single layer of Ag nanowire-polymer composite structure

Although a percolated network of silver nanowires (AgNWs) is considered the most promising flexible transparent electrode because of its high conductivity, high transmittance, excellent flexibility, and facile patternability, it has encountered a serious delay in its application to most optoelectron...

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Bibliographic Details
Published in:Composites science and technology 2018-09, Vol.165, p.58-65
Main Authors: Kim, Kwang-Seok, Kim, Sun Ok, Han, Chul Jong, Kim, Dae Up, Kim, Jin Soo, Yu, Yeon-Tae, Lee, Cheul-Ro, Kim, Jong-Woong
Format: Article
Language:English
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Summary:Although a percolated network of silver nanowires (AgNWs) is considered the most promising flexible transparent electrode because of its high conductivity, high transmittance, excellent flexibility, and facile patternability, it has encountered a serious delay in its application to most optoelectronic devices. Here, we analyzed the reasons and tried to resolve the current issues to achieve near-foldable transparent touch sensors by employing an inverted layer processing method. A hydroxylated polydimethylsiloxane (PDMS) was used as a preliminary substrate for deposition and patterning of AgNWs, and then the nanowires were completely transferred to the newest version of colorless polyimide (cPI) by hydrophobic recovery of the PDMS surface. For the first time, we designed an automatic apparatus for testing the foldability of the fabricated composite film by a spacer inserting method. The testing of various AgNWs/cPI films with this method revealed that the thickness reduction approach could be an efficient and powerful tool to attain near-foldable electrodes if the AgNWs are solidly adhered to the substrate. Based on these findings, we could successfully demonstrate a near-foldable touch sensor, which is capable of sensing human touches even in the folded state.
ISSN:0266-3538
1879-1050
DOI:10.1016/j.compscitech.2018.06.016