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Mendeley readers
Attention Score in Context
| Title |
Conduction Tuning of Graphene Based on Defect-Induced Localization
|
|---|---|
| Published in |
ACS Nano, June 2013
|
| DOI | 10.1021/nn401992q |
| Pubmed ID | |
| Authors |
Shu Nakaharai, Tomohiko Iijima, Shinichi Ogawa, Shingo Suzuki, Song-Lin Li, Kazuhito Tsukagoshi, Shintaro Sato, Naoki Yokoyama |
| Abstract |
The conduction properties of graphene were tuned by tailoring the lattice by using an accelerated helium ion beam to embed low-density defects in the lattice. The density of the embedded defects was estimated to be 2-3 orders of magnitude lower than that of carbon atoms, and they functionalized a graphene sheet in a more stable manner than chemical surface modifications can do. Current modulation through back gate biasing was demonstrated at room temperature with a current on-off ratio of 2 orders of magnitude, and the activation energy of the thermally activated transport regime was evaluated. The exponential dependence of the current on the length of the functionalized region in graphene suggested that conduction tuning is possible through strong localization of carriers at sites induced by a sparsely distributed random potential modulation. |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| Germany | 1 | 1% |
| United Kingdom | 1 | 1% |
| Brazil | 1 | 1% |
| Japan | 1 | 1% |
| China | 1 | 1% |
| Unknown | 72 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 19 | 24% |
| Student > Ph. D. Student | 15 | 19% |
| Student > Master | 7 | 9% |
| Student > Bachelor | 6 | 8% |
| Student > Doctoral Student | 5 | 6% |
| Other | 17 | 22% |
| Unknown | 10 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Physics and Astronomy | 24 | 30% |
| Materials Science | 18 | 23% |
| Engineering | 13 | 16% |
| Chemistry | 9 | 11% |
| Social Sciences | 1 | 1% |
| Other | 3 | 4% |
| Unknown | 11 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 January 2020.
All research outputs
#2,160,498
of 22,713,403 outputs
Outputs from ACS Nano
#2,083
of 12,771 outputs
Outputs of similar age
#19,630
of 196,368 outputs
Outputs of similar age from ACS Nano
#49
of 223 outputs
Altmetric has tracked 22,713,403 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,771 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.4. This one has done well, scoring higher than 83% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 196,368 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 223 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.