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Issue 35, 2018
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A self-sensing, superhydrophobic, heterogeneous graphene network with controllable adhesion behavior

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Abstract

Smart superhydrophobic surfaces with controllable adhesion behavior or sensing capability have become a research hotspot in many areas, such as self-cleaning and microdroplet transportation. Herein, we design and fabricate a superhydrophobic, open-cell graphene network with a polypropylene coating (PP/OCGN) via a new method of boiling coating. The adhesive force of PP/OCGN for water droplets can be controlled easily from 66.8 μN to 32.3 μN by adjusting the soaking time. Using the PP/OCGN with controllable adhesion behavior, the lossless transportation of water microdroplets has been achieved. What's more, because of the boiling coating process, the PP/OCGN exhibits a heterogeneous network, which has the coated graphene on the surface and the uncoated graphene in the inner part. By means of the special network and strong water repellency of PP/OCGN, we report for the first time a conductive, superhydrophobic graphene material with a self-sensing capability for continuously falling water droplets. When the water droplets fall on the surface, the PP/OCGN with low adhesive force not only makes the droplets bounce off successfully, but also has a rapid response to the bouncing process through changing the resistance. The size of falling water droplets can also be determined. Therefore, our multifunctional superhydrophobic PP/OCGN can meet multiple needs simultaneously, such as self-cleaning and detecting raindrops, and it has great application prospects in the future.

Graphical abstract: A self-sensing, superhydrophobic, heterogeneous graphene network with controllable adhesion behavior

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Publication details

The article was received on 02 Jul 2018, accepted on 31 Jul 2018 and first published on 04 Aug 2018


Article type: Paper
DOI: 10.1039/C8TA06303F
Citation: J. Mater. Chem. A, 2018,6, 16992-17000
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    A self-sensing, superhydrophobic, heterogeneous graphene network with controllable adhesion behavior

    G. Ding, W. Jiao, L. Chen, M. Yan, L. Hao and R. Wang, J. Mater. Chem. A, 2018, 6, 16992
    DOI: 10.1039/C8TA06303F

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