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Discrete distribution of implanted and annealed arsenic atoms in silicon nanowires and its effect on device performance

Overview of attention for article published in Nanoscale Research Letters, December 2012
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Title
Discrete distribution of implanted and annealed arsenic atoms in silicon nanowires and its effect on device performance
Published in
Nanoscale Research Letters, December 2012
DOI 10.1186/1556-276x-7-685
Pubmed ID
Authors

Masashi Uematsu, Kohei M Itoh, Gennady Mil'nikov, Hideki Minari, Nobuya Mori

Abstract

We have theoretically investigated the effects of random discrete distribution of implanted and annealed arsenic (As) atoms on device characteristics of silicon nanowire (Si NW) transistors. Kinetic Monte Carlo simulation is used for generating realistic random distribution of active As atoms in Si NWs. The active As distributions obtained through the kinetic Monte Carlo simulation are introduced into the source and drain extensions of n-type gate-all-around NW transistors. The current-voltage characteristics are calculated using the non-equilibrium Green's function method. The calculated results show significant fluctuation of the drain current. We examine the correlation between the drain current fluctuation and the factors related to random As distributions. We found that the fluctuation of the number of dopants in the source and drain extensions has little effect on the on-current fluctuation. We also found that the on-current fluctuation mainly originated from the randomness of interatomic distances of As atoms and hence is inherent in ultra-small NW transistors.

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 33%
Unknown 2 67%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 67%
Student > Postgraduate 1 33%
Readers by discipline Count As %
Physics and Astronomy 1 33%
Materials Science 1 33%
Engineering 1 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 21 December 2012.
All research outputs
#2,907,372
of 3,626,769 outputs
Outputs from Nanoscale Research Letters
#89
of 380 outputs
Outputs of similar age
#222,439
of 278,204 outputs
Outputs of similar age from Nanoscale Research Letters
#18
of 120 outputs
Altmetric has tracked 3,626,769 research outputs across all sources so far. This one is in the 2nd percentile – i.e., 2% of other outputs scored the same or lower than it.
So far Altmetric has tracked 380 research outputs from this source. They receive a mean Attention Score of 0.9. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 278,204 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.