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Dynamics of mechanical waves in periodic graphene nanoribbon assemblies

Overview of attention for article published in Discover Nano, June 2011
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Title
Dynamics of mechanical waves in periodic graphene nanoribbon assemblies
Published in
Discover Nano, June 2011
DOI 10.1186/1556-276x-6-430
Pubmed ID
Authors

Fabrizio Scarpa, Rajib Chowdhury, Kenneth Kam, Sondipon Adhikari, Massimo Ruzzene

Abstract

We simulate the natural frequencies and the acoustic wave propagation characteristics of graphene nanoribbons (GNRs) of the type (8,0) and (0,8) using an equivalent atomistic-continuum FE model previously developed by some of the authors, where the C-C bonds thickness and average equilibrium lengths during the dynamic loading are identified through the minimisation of the system Hamiltonian. A molecular mechanics model based on the UFF potential is used to benchmark the hybrid FE models developed. The acoustic wave dispersion characteristics of the GNRs are simulated using a Floquet-based wave technique used to predict the pass-stop bands of periodic mechanical structures. We show that the thickness and equilibrium lengths do depend on the specific vibration and dispersion mode considered, and that they are in general different from the classical constant values used in open literature (0.34 nm for thickness and 0.142 nm for equilibrium length). We also show the dependence of the wave dispersion characteristics versus the aspect ratio and edge configurations of the nanoribbons, with widening band-gaps that depend on the chirality of the configurations. The thickness, average equilibrium length and edge type have to be taken into account when nanoribbons are used to design nano-oscillators and novel types of mass sensors based on periodic arrangements of nanostructures.PACS 62.23.Kn · 62.25.Fg · 62.25.Jk.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 3%
Unknown 28 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 31%
Student > Master 5 17%
Professor > Associate Professor 3 10%
Researcher 2 7%
Professor 1 3%
Other 2 7%
Unknown 7 24%
Readers by discipline Count As %
Engineering 9 31%
Physics and Astronomy 8 28%
Materials Science 2 7%
Philosophy 1 3%
Chemistry 1 3%
Other 0 0%
Unknown 8 28%
Attention Score in Context

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 16 February 2013.
All research outputs
#19,942,887
of 25,371,288 outputs
Outputs from Discover Nano
#668
of 1,146 outputs
Outputs of similar age
#105,166
of 125,984 outputs
Outputs of similar age from Discover Nano
#14
of 17 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,146 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.