alexa Bio-inspired Synthesis And Self-assembly Of Few Layer Graphene
ISSN: 2169-0022

Journal of Material Sciences & Engineering
Open Access

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Joint Conference: International Conference on DIAMOND AND CARBON MATERIALS & GRAPHENE AND SEMICONDUCTORS
July 17-18, 2017 Chicago, USA

Izabela Janowska
Institute of Chemistry and Processes for Energy, Environment and Health, France
Posters & Accepted Abstracts: J Material Sci Eng
DOI: 10.4172/2169-0022-C1-077
Abstract
The future development of advanced materials depends on several aspects, which are first of all linked to synthesis and then exploitation of the materials in an efficient way. This concerns also the graphene based materials and despite the huge number of efforts devoted to the synthesis of graphene and few layer graphene (FLG) there is still luck of the methods allowing their high scale production together with environment respect. Their efficient use in composites, polymers and films in order to provide or enhance graphene-related properties such as high conductivity, transparency, flexibility, mechanical resistance will depend on the way these “nano” materials are arranged in the macroscopic media. Herein, the bio-compatible, high yield production of solution processable FLG is presented together with a new approach of bio-inspired FLG self-assemblies into fractal like patterns (presently under patent application). Such FLG self-assemblies reduce the percolation threshold between FLG flakes allowing the percolation at lower amount of FLG for a given surface if compared to the random arrangement (fig.1). This can find the application in transparent conductive films (TCF), where the FLG self-assemblies patterns can be optimized in order to achieve variable transparency-conductivity properties according to the TCF final use. This interesting finding recalls the natural tendency of matter to self-organize into functional systems. The fractal like, branched structures are commonly observed in numerous natural systems being in charge of transport function, such as river beds, trees or neural system.
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