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Article . 2019 . Peer-reviewed
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Mechanocombinatorially Screening Sensitivity of Stretchable Strain Sensors

Authors: Shaowu Pan; Zhiyuan Liu; Ming Wang; Ying Jiang; Yifei Luo; Changjin Wan; Dianpeng Qi; +3 Authors

Mechanocombinatorially Screening Sensitivity of Stretchable Strain Sensors

Abstract

AbstractStretchable strain sensors have aroused great interest for their application in human activity recognition, health monitoring, and soft robotics. For various scenarios involving the application of different strain ranges, specific sensitivities need to be developed, due to a trade‐off between sensor sensitivity and stretchability. Traditional stretchable strain sensors are developed based on conductive sensing materials and still lack the function of customizable sensitivity. A novel strategy of mechanocombinatorics is proposed to screen the sensor sensitivity based on mechanically heterogeneous substrates. Strain redistribution over substrates is optimized by mechanics and structure parameters, which gives rise to customizable sensitivity. As a proof of concept, a local illumination method is used to fabricate heterogeneous substrates with customizable mechanics and structure parameters. A library of mechanocombinatorial strain sensors is created for extracting the specific sensitivity. Thus, not only is an effective strategy for screening of sensor sensitivity demonstrated, but a contribution to the mechanocombinatorial strategy for personalized stretchable electronics is also made.

Country
Singapore
Related Organizations
Keywords

Heterogeneous Substrates, Mechanocombinatorics, 004, Engineering::Materials

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
125
Top 1%
Top 10%
Top 1%
bronze