↓ Skip to main content

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

Overview of attention for article published in Langmuir, December 2016
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
15 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
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.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 7%
Unknown 14 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 47%
Student > Ph. D. Student 3 20%
Professor 1 7%
Other 1 7%
Student > Bachelor 1 7%
Other 2 13%
Readers by discipline Count As %
Engineering 3 20%
Chemistry 3 20%
Unspecified 3 20%
Materials Science 2 13%
Physics and Astronomy 1 7%
Other 3 20%

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
#4,058,971
of 8,900,478 outputs
Outputs from Langmuir
#810
of 3,197 outputs
Outputs of similar age
#131,779
of 306,001 outputs
Outputs of similar age from Langmuir
#26
of 110 outputs
Altmetric has tracked 8,900,478 research outputs across all sources so far. This one has received more attention than most of these and is in the 53rd percentile.
So far Altmetric has tracked 3,197 research outputs from this source. They receive a mean Attention Score of 2.8. This one has gotten more attention than average, scoring higher than 72% 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 306,001 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.