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A highly stretchable autonomous self-healing elastomer

Overview of attention for article published in Nature Chemistry, April 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#19 of 2,430)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
25 news outlets
blogs
9 blogs
policy
1 policy source
twitter
68 tweeters
patent
2 patents
facebook
6 Facebook pages
video
1 video uploader

Citations

dimensions_citation
413 Dimensions

Readers on

mendeley
607 Mendeley
Title
A highly stretchable autonomous self-healing elastomer
Published in
Nature Chemistry, April 2016
DOI 10.1038/nchem.2492
Pubmed ID
Authors

Cheng-Hui Li, Chao Wang, Christoph Keplinger, Jing-Lin Zuo, Lihua Jin, Yang Sun, Peng Zheng, Yi Cao, Franziska Lissel, Christian Linder, Xiao-Zeng You, Zhenan Bao

Abstract

It is a challenge to synthesize materials that possess the properties of biological muscles-strong, elastic and capable of self-healing. Herein we report a network of poly(dimethylsiloxane) polymer chains crosslinked by coordination complexes that combines high stretchability, high dielectric strength, autonomous self-healing and mechanical actuation. The healing process can take place at a temperature as low as -20 °C and is not significantly affected by surface ageing and moisture. The crosslinking complexes used consist of 2,6-pyridinedicarboxamide ligands that coordinate to Fe(III) centres through three different interactions: a strong pyridyl-iron one, and two weaker carboxamido-iron ones through both the nitrogen and oxygen atoms of the carboxamide groups. As a result, the iron-ligand bonds can readily break and re-form while the iron centres still remain attached to the ligands through the stronger interaction with the pyridyl ring, which enables reversible unfolding and refolding of the chains. We hypothesize that this behaviour supports the high stretchability and self-healing capability of the material.

Twitter Demographics

The data shown below were collected from the profiles of 68 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 607 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 1%
South Africa 1 <1%
Brazil 1 <1%
Chile 1 <1%
Israel 1 <1%
Japan 1 <1%
Germany 1 <1%
Unknown 592 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 192 32%
Student > Master 84 14%
Researcher 82 14%
Student > Bachelor 57 9%
Student > Doctoral Student 34 6%
Other 79 13%
Unknown 79 13%
Readers by discipline Count As %
Chemistry 181 30%
Materials Science 122 20%
Engineering 106 17%
Chemical Engineering 39 6%
Physics and Astronomy 11 2%
Other 39 6%
Unknown 109 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 291. 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 15 November 2019.
All research outputs
#55,119
of 15,774,705 outputs
Outputs from Nature Chemistry
#19
of 2,430 outputs
Outputs of similar age
#1,793
of 265,780 outputs
Outputs of similar age from Nature Chemistry
#2
of 60 outputs
Altmetric has tracked 15,774,705 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,430 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 31.8. This one has done particularly well, scoring higher than 99% 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 265,780 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.