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Laser-Etched Stretchable Graphene–Polymer Composite Array for Sensitive Strain and Viscosity Sensors
Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing; University of Chinese Academy of Sciences, Beijing.
Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing .
Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing;University of Chinese Academy of Sciences, Beijing .
Chinese Academy of Sciences, Urumqi, Xinjiang.
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2019 (English)In: Nano-Micro Letters, ISSN 2150-5551, Vol. 11, no 1, article id 99Article in journal (Refereed) Published
Abstract [en]

The ability to control surface wettability and liquid spreading on textured surfaces is of interest for extensive applications. Soft materials have prominent advantages for producing the smart coatings with multiple functions for strain sensing. Here, we report a simple method to prepare flexible hydrophobic smart coatings using graphene–polymer films. Arrays of individual patterns in the films were created by laser engraving and controlled the contact angle of small drops by pinning the contact lines in a horizontal tensile range of 0–200%. By means of experiments and model, we demonstrate that the ductility of drops is relied on the height-to-spacing ratio of the individual pattern and the intrinsic contact angle. Moreover, the change of drop size was utilized to measure the applied strain and liquid viscosity, enabling a strain sensitivity as high as 1068 μm2/%. The proposed laser-etched stretchable graphene–polymer composite has potential applications in DNA microarrays, biological assays, soft robots, and so on.

Place, publisher, year, edition, pages
2019. Vol. 11, no 1, article id 99
Keywords [en]
Hydrophobic smart coatings, Flexible sensors, Soft materials, Controlled drops Graphene
National Category
Physical Sciences
Identifiers
URN: urn:nbn:se:miun:diva-37822DOI: 10.1007/s40820-019-0333-6ISI: 000496665800001Scopus ID: 2-s2.0-85075034262OAI: oai:DiVA.org:miun-37822DiVA, id: diva2:1373970
Available from: 2019-11-28 Created: 2019-11-28 Last updated: 2020-01-16Bibliographically approved

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Zhang, RenyunOlin, Håkan

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