4.8 Article

Tuning and fine morphology control of natural resource-derived vertical graphene

期刊

CARBON
卷 159, 期 -, 页码 668-685

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.carbon.2019.10.060

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资金

  1. PEGASUS (Plasma Enabled and Graphene Allowed Synthesis of Unique nano-Structures) project - European Union's Horizon research and innovation programme [766894]
  2. OSTIn-SRP/EDB
  3. National Research Foundation
  4. AcRF Singapore [Rp6/16 Xs]
  5. School of Chemistry, Physics and Mechanical Engineering, Science and Engineering Faculty, Queensland University of Technology
  6. Australian Research Council

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Tunability and fine control of structure and morphology in the patterns of vertically-oriented graphenes is of high importance for their efficient functionalization and application. In this work, we present an experimental and simulation insight into the formation of graphene structures. Detailed simulations by an ad hoc model based on a large number of interacting elemental processes were implemented to ensure a deeper insight into the processes which cannot be directly measured and assessed in the experiments, such as relative densities of adsorbed species and density of ion current at the nanostructures. The combination of the experimental and simulation approaches provided a new level of understanding of the processes that govern formation of the graphene network morphology. Moreover, the potential of novel analytical techniques such as Hough transformations, fractal dimension distributions and Minkovski connectivity, 2D FFT transforms, Hough transformation spectra and others for analysis of the graphene array morphology was successfully demonstrated. The evolution of surface morphology of graphene derived from cold-pressed Citrus sinensis oil, a by-product of orange juice production by centrifugation, synthesised via a catalyst-free process, was investigated using experimental analyses, Raman spectroscopy, scanning electron microscopy and X-ray photoelectron spectroscopy, and numerous advanced analytical techniques such as distributions of fractal dimensions. (C) 2019 Elsevier Ltd. All rights reserved.

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