4.8 Article

Solution-Synthesized Chevron Graphene Nanoribbons Exfoliated onto H:Si(100)

Journal

NANO LETTERS
Volume 17, Issue 1, Pages 170-178

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.nanolett.6b03709

Keywords

graphene nanoribbons; armchair edges; scanning tunneling spectroscopy; current imaging tunneling spectroscopy; silicon; dry contact transfer

Funding

  1. National Science Foundation (NSF) [CHE-1455330]
  2. Office of Naval Research (ONR) [N00014-16-1-2899]
  3. Nebraska Research Initiative
  4. Office of Naval Research [N00014-13-1-0300]
  5. AFOSR [FA9550-12-1-0464]
  6. NSF [1264282, 1420882, 1506619, 1545907]
  7. Direct For Computer & Info Scie & Enginr
  8. Division of Computing and Communication Foundations [1420882] Funding Source: National Science Foundation
  9. Div Of Electrical, Commun & Cyber Sys
  10. Directorate For Engineering [1506619] Funding Source: National Science Foundation

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There has been tremendous progress in designing and synthesizing graphene nanoribbons (GNRs). The ability to control the width, edge structure, and dopant level with atomic precision has created a large class of accessible electronic landscapes for use in logic applications. One of the major limitations preventing the realization of GNR devices is the difficulty of transferring GNRs onto nonmetallic substrates. In this work, we developed a new approach for clean deposition of solution synthesized atomically precise chevron GNRs onto H:Si(100) under ultrahigh vacuum. A clean transfer allowed ultrahigh-vacuum scanning tunneling microscopy (STM) to provide high-resolution imaging and spectroscopy and reveal details of the electronic structure of chevron nanoribbons that have not been previously reported. We also demonstrate STM nanomanipulation of GNRs, characterization of multilayer GNR cross-junctions, and STM nanolithography for local depassivation of H:Si(100), which allowed us to probe GNR Si interactions and revealed a semiconducting-to-metallic transition. The results STM measurements were shown to be in good agreement with first-principles computational modeling.

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