Graphene surface analysis and layer counting using scanning low energy electron microscopy

0517435 - ÚPT 2020 PT eng A - Abstrakt
Průcha, Lukáš - Piňos, Jakub - Kizovský, Martin - Mikmeková, Eliška
Graphene surface analysis and layer counting using scanning low energy electron microscopy.
5th Edition of the European Graphene Forum 2019. Book of Abstracts. Lisbon: SETCOR, 2019.
[Edition of the European Graphene Forum 2019 /5./. 23.10.2019-25.10.2019, Lisbon]
Institucionální podpora: RVO:68081731
Klíčová slova: graphene analysis * low energy electron microscopy * scanning electron microscopy * layer counting
Obor OECD: Nano-materials (production and properties)

Scanning low energy electron microscopy (SLEEM) can be a very useful tool when it comes to the surface analysis and layer de-termination of graphene. This approach can be much more precise than conventional methods for the graphene layers determina-tion, such as Raman spectroscopy. In this work, we want to show, that through our SLEEM system MAMOTH, we can easily analyze graphene surface, count the graphene layers and even clean the surface out of air-adsorbed hydrocarbons with the same elec-tron beam. Thanks to this approach we are able to optically determine the morphology of layers of graphene flakes. In this study, we also want to show that our approach of the graphene layer analysis has more precise outcome than the conventional Raman analy-sis. The layer counting is carried out through the change in the reflectivity of the graphene flakes (layers) when low energy electrons (energy less than 50 eV) interact with the sur-face. As the electron energy goes higher, starting from 0 eV (thanks to the cathode lens), the reflectivity of graphene layers changes and creates for n-layered graphene n-1 reflectivity minima (Figure 1). For this work, all graphene samples were prepared in our prototype CVD furnace on copper foils. Also, graphene samples with different layers (ranging from one layer to FLG) were pre-pared through the change of the CVD system production parameters, so we can analyze and compare more different samples.
Trvalý link: http://hdl.handle.net/11104/0302742