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      Moiré-modulated conductance of hexagonal boron nitride tunnel barriers

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      Collection of raw AFM data in .ibw format and optical images of samples/devices used in all figures of paper (.zip archive) (135.8Mb)
      Publication date
      2018-07-16
      Creators
      Summerfield, Alex
      Metadata
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      Description
      Monolayer hexagonal boron nitride (hBN) tunnel barriers investigated using conductive atomic force microscopy reveal moiré patterns in the spatial maps of their tunnel conductance consistent with the formation of a moiré superlattice between the hBN and an underlying highly ordered pyrolytic graphite (HOPG) substrate. This variation is attributed to a periodic modulation of the local density of states and occurs for both exfoliated hBN barriers and epitaxially-grown layers. The epitaxial barriers also exhibit enhanced conductance at localised sub-nanometre regions which are attributed to exposure of the substrate to a nitrogen plasma source during the high temperature growth process. Our results show clearly a spatial periodicity of tunnel current due to the formation of a moiré superlattice and we argue that this can provide a mechanism for elastic scattering of charge carriers for similar interfaces embedded in graphene/hBN resonant tunnel diodes.
      External URI
      • https://rdmc.nottingham.ac.uk/handle/internal/362
      DOI
      • http://doi.org/10.17639/nott.358
      Related publication DOI
      • 10.1021/acs.nanolett.8b01223
      Subjects
      • Atomic force microscopy
      • Superlattices as materials
      • Boron nitride
      • Graphite composites
      • Molecular beam epitaxy
      • Atomic force microscopy moire tunnel conductance hexagonal boron nitride molecular beam epitaxy
      • Physical sciences::Materials science
      • Q Science::QC Physics::QC170 Atomic physics. Constitution and properties of matter
      Divisions
      • University of Nottingham, UK Campus::Faculty of Science::School of Physics and Astronomy
      Deposit date
      2018-07-16
      Data type
      Imaging data
      Contributors
      • Cheng, Tin s.
      • Kozikov, Aleksey
      • Davies, Andrew
      • Cho, Yong-Jin
      • Khlobystov, Andrei N.
      • Mellor, Christopher J.
      • Foxon, C. Thomas
      • Watanabe, Kenji
      • Taniguchi, Takashi
      • Eaves, Laurence
      • Novoselov, Kostya S.
      • Novikov, Sergei V.
      • Beton, Peter
      Funders
      • Engineering & Physical Sciences Research Council
      • Leverhulme Trust
      • EU Graphene Flagship
      • European Research Council
      • The Royal Society
      • US Army Research Office
      • MEXT Japan
      • CREST
      Grant number
      • EP/L013908/1
      • EP/P019080/1
      • EP/M50810X/1
      • RPG-2014-129
      • W911NF-16-1-0279
      • JPMJCR15F3
      Collection dates
      • 2016-2018
      Data collection method
      Instruments: Asylum Research Cypher-S AFM/STM
      Resource languages
      • en
      Publisher
      The University of Nottingham

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