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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 (#28 of 2,984)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

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

Citations

dimensions_citation
956 Dimensions

Readers on

mendeley
792 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 64 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 792 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 1%
Germany 1 <1%
Brazil 1 <1%
Chile 1 <1%
Japan 1 <1%
Israel 1 <1%
Unknown 778 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 231 29%
Student > Master 99 13%
Researcher 96 12%
Student > Bachelor 70 9%
Student > Doctoral Student 41 5%
Other 93 12%
Unknown 162 20%
Readers by discipline Count As %
Chemistry 213 27%
Materials Science 150 19%
Engineering 129 16%
Chemical Engineering 45 6%
Physics and Astronomy 11 1%
Other 43 5%
Unknown 201 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 292. 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 05 July 2022.
All research outputs
#96,035
of 22,518,353 outputs
Outputs from Nature Chemistry
#28
of 2,984 outputs
Outputs of similar age
#2,000
of 281,081 outputs
Outputs of similar age from Nature Chemistry
#2
of 61 outputs
Altmetric has tracked 22,518,353 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 2,984 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 35.0. 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 281,081 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 61 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 98% of its contemporaries.