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Cited by 294

The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.

Surface State Transport and Ambipolar Electric Field Effect in Bi2Se3 Nanodevices

Open access
Steinberg, Hadar, Gardner, Dillon R., Lee, Young S., Jarillo-Herrero, Pablo·2010·Nano Letters

Abstract

Electronic transport experiments involving the topologically protected states found at the surface of Bi2Se3 and other topological insulators require fine control over carrier density, which is challenging with existing bulk-doped material. Here we report on electronic transport measurements on thin (<100 nm) Bi2Se3 devices and show that the density of the surface states can be modulated via the electric field effect by using a top-gate with a high-k dielectric insulator. The conductance dependence on geometry, gate voltage, and temperature all indicate that transport is governed by parallel surface and bulk contributions. Moreover, the conductance dependence on top-gate voltage is ambipolar, consistent with tuning between electrons and hole carriers at the surface.

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Crossref · 10.1021/nl1032183

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Metadata

Authors
Steinberg, H., Gardner, D. R., Lee, Y. S., & Jarillo-Herrero, P.
Venue
Nano Letters
Published
2010-11-01
Volume
10
Issue
12
Pages
5032-5036
ISSN
  • 1530-6984 (ISSN-L)
  • 1530-6992
OpenAlex
W2119269698
Cited by
294
References
27
FWCI
20.17
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Surface State Transport and Ambipolar Electric Field Effect in Bi2Se3 Nanodevices. https://app.cochat.ai/papers/10.1021/nl1032183
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Steinberg, H., Gardner, D. R., Lee, Y. S., & Jarillo-Herrero, P. (2010). Surface State Transport and Ambipolar Electric Field Effect in Bi2Se3 Nanodevices. Nano Letters. https://doi.org/10.1021/nl1032183

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.