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Machine learning-assisted exploration of a versatile polymer platform with charge transfer-dependent full-color emission

Overview of attention for article published in Chem, April 2023
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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 1,678)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
15 news outlets
blogs
2 blogs
twitter
25 X users

Citations

dimensions_citation
15 Dimensions

Readers on

mendeley
15 Mendeley
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Title
Machine learning-assisted exploration of a versatile polymer platform with charge transfer-dependent full-color emission
Published in
Chem, April 2023
DOI 10.1016/j.chempr.2022.12.003
Authors

Suiying Ye, Nastaran Meftahi, Igor Lyskov, Tian Tian, Richard Whitfield, Sudhir Kumar, Andrew J. Christofferson, David A. Winkler, Chih-Jen Shih, Salvy Russo, Jean-Christophe Leroux, Yinyin Bao

X Demographics

X Demographics

The data shown below were collected from the profiles of 25 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 27%
Student > Master 2 13%
Professor 1 7%
Student > Doctoral Student 1 7%
Student > Bachelor 1 7%
Other 1 7%
Unknown 5 33%
Readers by discipline Count As %
Chemistry 6 40%
Immunology and Microbiology 1 7%
Mathematics 1 7%
Physics and Astronomy 1 7%
Materials Science 1 7%
Other 0 0%
Unknown 5 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 133. 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 04 October 2023.
All research outputs
#313,524
of 25,392,582 outputs
Outputs from Chem
#28
of 1,678 outputs
Outputs of similar age
#7,387
of 421,804 outputs
Outputs of similar age from Chem
#3
of 69 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,678 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.5. This one has done particularly well, scoring higher than 98% 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 421,804 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 98% of its contemporaries.
We're also able to compare this research output to 69 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 95% of its contemporaries.