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Dip-and-Drag Lateral Force Spectroscopy for Measuring Adhesive Forces between Nanofibers

Overview of attention for article published in Langmuir, December 2016
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Title
Dip-and-Drag Lateral Force Spectroscopy for Measuring Adhesive Forces between Nanofibers
Published in
Langmuir, December 2016
DOI 10.1021/acs.langmuir.6b03467
Pubmed ID
Authors

Grace K. Dolan, Gleb E. Yakubov, George W. Greene, Nasim Amiralian, Pratheep K. Annamalai, Darren J. Martin, Jason R. Stokes

Abstract

Adhesive interactions between nanofibers strongly influence the mechanical behavior of soft materials composed of fibrous networks. We use atomic force microscopy in lateral force mode to drag a cantilever tip through fibrous networks, and use the measured lateral force response to determine the adhesive forces between fibers of the order of 100 nm diameter. The peaks in lateral force curves are directly related to the detachment energy between two fibers; the data is analyzed using the Jarzynski equality to yield the average adhesion energy of the weakest links. The method is successfully used to measure adhesion forces arising from van der Waals interactions between electrospun polymer fibers in networks of varying density. This approach overcomes the need to isolate and handle individual fibers, and can be readily employed in the design and evaluation of advanced materials and biomaterials which, through inspiration from nature, are increasingly incorporating nanofibers. The data obtained with this technique may also be of critical importance in the development of network models capable of predicting the mechanics of fibrous materials.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 45%
Student > Ph. D. Student 3 14%
Professor 2 9%
Student > Bachelor 1 5%
Lecturer 1 5%
Other 2 9%
Unknown 3 14%
Readers by discipline Count As %
Chemistry 5 23%
Engineering 4 18%
Chemical Engineering 2 9%
Materials Science 2 9%
Neuroscience 1 5%
Other 2 9%
Unknown 6 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 12 January 2017.
All research outputs
#15,034,705
of 23,322,966 outputs
Outputs from Langmuir
#10,407
of 14,207 outputs
Outputs of similar age
#240,515
of 422,089 outputs
Outputs of similar age from Langmuir
#54
of 134 outputs
Altmetric has tracked 23,322,966 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 14,207 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 26th percentile – i.e., 26% 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 422,089 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 134 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.