Graphene-Functionalized Natural Microcapsules: Modular Building Blocks for Ultrahigh Sensitivity Bioelectronic Platforms
Natural cellular materials with honeycomb or foam microstructures are excellent inspirations for the biomimetic design of sensitive and robust bioelectronic interfaces. Herein, the fabrication of a hierarchical, self‐assembled platform that combines a natural cellular material (Lycopodium clavatum p...
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Veröffentlicht in: | Advanced functional materials 2016-04, Vol.26 (13), p.2097-2103 |
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Sprache: | eng |
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Zusammenfassung: | Natural cellular materials with honeycomb or foam microstructures are excellent inspirations for the biomimetic design of sensitive and robust bioelectronic interfaces. Herein, the fabrication of a hierarchical, self‐assembled platform that combines a natural cellular material (Lycopodium clavatum pollen spores) with an electrically conductive material (reduced graphene oxide, defined as rGO) for the first time is reported. The spores function as natural building blocks which are functionalized with crumpled rGO and then deposited on a silicon oxide surface, yielding a 3D architecture with electroactive properties. The hybrid material design is incorporated into a field‐effect transistor device and employed in an antibody‐based detection scheme in order to measure the concentration of a target protein with a limit of detection of 1 × 10−15 m, which is five orders of magnitude better than a conventional rGO‐based biosensor tested in comparison. The findings in this work highlight the merit of integrating natural cellular materials with electrically conductive materials, offering a framework to develop high‐sensitivity bioelectronic platforms.
A highly sensitive bioelectronic platform based on graphene oxide functionalized natural microcapsules is reported, integrating a natural cellular material with an electrically conductive material. Modular assembly led to the fabrication of a highly sensitive biosensor which exhibits a 1 × 10−15 m limit of detection, which is five orders of magnitude better than a conventional graphene oxide biosensor. |
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ISSN: | 1616-301X 1616-3028 |
DOI: | 10.1002/adfm.201504940 |