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Cited by 310

The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.

Bipolar magnetic semiconductors: a new class of spintronics materials

Open access
Li, Xingxing, Wu, Xiaojun, Li, Zhenyu, Yang, Jinlong, Hou, J. G.·2012·Nanoscale

Abstract

Electrical control of spin polarization is very desirable in spintronics, since electric fields can be easily applied locally, in contrast to magnetic fields. Here, we propose a new concept of bipolar magnetic semiconductors (BMS) in which completely spin-polarized currents with reversible spin polarization can be created and controlled simply by applying a gate voltage. This is a result of the unique electronic structure of BMS, where the valence and conduction bands possess opposite spin polarization when approaching the Fermi level. BMS is thus expected to have potential for various applications. Our band structure and spin-polarized electronic transport calculations on semi-hydrogenated single-walled carbon nanotubes confirm the existence of BMS materials and demonstrate the electrical control of spin-polarization in them.

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Crossref · 10.1039/c2nr31743e

Cites

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Metadata

Authors
Li, X., Wu, X., Li, Z., Yang, J., & Hou, J. G.
Venue
Nanoscale
Published
2012
Volume
4
Issue
18
Pages
5680
ISSN
  • 2040-3364 (ISSN-L)
  • 2040-3372
OpenAlex
W2108679281
Cited by
310
References
35
FWCI
4.32
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Bipolar magnetic semiconductors: a new class of spintronics materials. https://app.cochat.ai/papers/10.1039/c2nr31743e
The paper
Li, X., Wu, X., Li, Z., Yang, J., & Hou, J. G. (2012). Bipolar magnetic semiconductors: a new class of spintronics materials. Nanoscale. https://doi.org/10.1039/c2nr31743e

Data sources

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.