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Strong Suppression of Electrical Noise in Bilayer Graphene Nanodevices
Open accessAbstract
Low-frequency 1/f noise is ubiquitous and dominates the signal-to-noise performance in nanodevices. Here we investigate the noise characteristics of single-layer and bilayer graphene nanodevices and uncover an unexpected 1/f noise behavior for bilayer devices. Graphene is a single layer of graphite, where carbon atoms form a two-dimensional (2D) honeycomb lattice. Despite the similar composition, bilayer graphene (two graphene monolayers stacked in the natural graphite order) is a distinct 2D system with a different band structure and electrical properties. 1,2In graphene monolayers, the 1/f noise is found to follow Hooge's empirical relation with a noise parameter comparable to that of bulk semiconductors. However, this 1/f noise is strongly suppressed in bilayer graphene devices and exhibits an unusual dependence on the carrier density, different from most other materials. The unexpected noise behavior in graphene bilayers is associated with its unique band structure that varies with the charge distribution among the two layers, resulting in an effective screening of potential fluctuations due to external impurity charges. The findings here point to exciting opportunities for graphene bilayers in low-noise applications.
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Cites
Two-dimensional gas of massless Dirac fermions in graphene
Novoselov, K. S., Geim, A. K., Morozov, S. V., Jiang, D., Katsnelson, M. I., Grigorieva, I. V., Dubonos, S. V., & Firsov, A. A. (2005) · Nature · doi:10.1038/nature04233 · Cited by 21,611
Experimental observation of the quantum Hall effect and Berry's phase in graphene
Zhang, Y., Tan, Y.-W., Stormer, H. L., & Kim, P. (2005) · Nature · doi:10.1038/nature04235 · Cited by 13,435
Biased Bilayer Graphene: Semiconductor with a Gap Tunable by the Electric Field Effect
Castro, E. V., Novoselov, K. S., Morozov, S. V., Peres, N. M. R., dos Santos, J. M. B. L., Nilsson, J., Guinea, F., Geim, A. K., & Neto, A. H. C. (2007) · Physical Review Letters · doi:10.1103/physrevlett.99.216802 · Cited by 2,033
Asymmetry gap in the electronic band structure of bilayer graphene
McCann, E. (2006) · Physical Review B · doi:10.1103/physrevb.74.161403 · Cited by 1,275
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Jiao, L., Zhang, L., Wang, X., Diankov, G., & Dai, H. (2009) · Nature · doi:10.1038/nature07919 · Cited by 2,441
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Eda, G., & Chhowalla, M. (2010) · Advanced Materials · doi:10.1002/adma.200903689 · Cited by 2,283
Reduced Graphene Oxide Molecular Sensors
Robinson, J. T., Perkins, F. K., Snow, E. S., Wei, Z., & Sheehan, P. E. (2008) · Nano Letters · doi:10.1021/nl8013007 · Cited by 1,772
Biological and chemical sensors based on graphene materials
Liu, Y., Dong, X., & Chen, P. (2012) · Chem. Soc. Rev. · doi:10.1039/c1cs15270j · Cited by 1,748
Carbon Nanomaterials in Biosensors: Should You Use Nanotubes or Graphene?
Yang, W., Ratinac, K. R., Ringer, S. P., Thordarson, P., Gooding, J. J., & Braet, F. (2010) · Angewandte Chemie International Edition · doi:10.1002/anie.200903463 · Cited by 1,431
Yuan, W., & Shi, G. (2013) · Journal of Materials Chemistry A · doi:10.1039/c3ta11774j · Cited by 1,073
Self‐Assembled Free‐Standing Graphite Oxide Membrane
Chen, C., Yang, Q., Yang, Y., Lv, W., Wen, Y., Hou, P., Wang, M., & Cheng, H. (2009) · Advanced Materials · doi:10.1002/adma.200803726 · Cited by 937
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Meng, Z., Stolz, R. M., Mendecki, L., & Mirica, K. A. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00311 · Cited by 773
Low-frequency 1/f noise in graphene devices
Balandin, A. A. (2013) · Nature Nanotechnology · doi:10.1038/nnano.2013.144 · Cited by 649
Tyagi, D., Wang, H., Huang, W., Hu, L., Tang, Y., Guo, Z., Ouyang, Z., & Zhang, H. (2020) · Nanoscale · doi:10.1039/c9nr10178k · Cited by 508
Zhu, W., Perebeinos, V., Freitag, M., & Avouris, P. (2009) · Physical Review B · doi:10.1103/physrevb.80.235402 · Cited by 485
Self-citationControlling graphene plasmons with resonant metal antennas and spatial conductivity patterns
Alonso-González, P., Nikitin, A. Y., Golmar, F., Centeno, A., Pesquera, A., Vélez, S., Chen, J., Navickaite, G., Koppens, F., Zurutuza, A., et al. (2014) · Science · doi:10.1126/science.1253202 · Cited by 379
Thermal contact resistance between graphene and silicon dioxide
Chen, Z., Jang, W., Bao, W., Lau, C. N., & Dames, C. (2009) · Applied Physics Letters · doi:10.1063/1.3245315 · Cited by 349
Chemical Doping of Large-Area Stacked Graphene Films for Use as Transparent, Conducting Electrodes
Kasry, A., Kuroda, M. A., Martyna, G. J., Tulevski, G. S., & Bol, A. A. (2010) · ACS Nano · doi:10.1021/nn100508g · Cited by 342
Recent Advances in Sensing Applications of Graphene Assemblies and Their Composites
Tung, T. T., Nine, M. J., Krebsz, M., Pasinszki, T., Coghlan, C. J., Tran, D. N. H., & Losic, D. (2017) · Advanced Functional Materials · doi:10.1002/adfm.201702891 · Cited by 294
Interactions of graphene and graphene oxide with proteins and peptides
Zhang, Y., Wu, C., Guo, S., & Zhang, J. (2013) · Nanotechnology Reviews · doi:10.1515/ntrev-2012-0078 · Cited by 235
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Metadata
- Authors
- Lin, Y.-M., & Avouris, P.
- Venue
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2008-02-26
- Volume
- 8
- Issue
- 8
- Pages
- 2119-2125
- ISSN
- 1530-6984 (ISSN-L)
- 1530-6992
- OpenAlex
- W2077969050
- Cited by
- 396
- References
- 4
- FWCI
- 17.68
- Type
- journal article
- Language
- en
- Open access
- green
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