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Self-sorted Oligophenylvinylene and Perylene Bisimide Hydrogels

Overview of attention for article published in Scientific Reports, August 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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6 X users

Citations

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Title
Self-sorted Oligophenylvinylene and Perylene Bisimide Hydrogels
Published in
Scientific Reports, August 2017
DOI 10.1038/s41598-017-08644-0
Pubmed ID
Authors

Ana M. Castilla, Emily R. Draper, Michael C. Nolan, Christopher Brasnett, Annela Seddon, Laura L. E. Mears, Nathan Cowieson, Dave J. Adams

Abstract

We describe two component hydrogels with networks composed of self-sorted fibres. The component gelators are based on 1,4-distyrylbenzene (OPV3) and perylene bisimide (PBI) units. Self-sorted gels can be formed by a slow decrease in pH, which leads to sequential assembly. We demonstrate self-sorting by NMR, rheology and small angle X-ray scattering (SAXS). Photoconductive xerogels can be prepared by drying these gels. The wavelength response of the xerogel is different to that of the PBI alone.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 47%
Student > Bachelor 3 8%
Researcher 3 8%
Professor 3 8%
Professor > Associate Professor 2 6%
Other 3 8%
Unknown 5 14%
Readers by discipline Count As %
Chemistry 22 61%
Materials Science 3 8%
Chemical Engineering 1 3%
Physics and Astronomy 1 3%
Unknown 9 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 August 2017.
All research outputs
#7,525,674
of 23,806,312 outputs
Outputs from Scientific Reports
#50,852
of 128,553 outputs
Outputs of similar age
#115,939
of 318,827 outputs
Outputs of similar age from Scientific Reports
#2,219
of 5,896 outputs
Altmetric has tracked 23,806,312 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 128,553 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.5. This one has gotten more attention than average, scoring higher than 59% 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 318,827 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 63% of its contemporaries.
We're also able to compare this research output to 5,896 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 62% of its contemporaries.