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Computation-accelerated discovery of the K2NiF4-type oxyhydrides combing density functional theory and machine learning approach

Overview of attention for article published in Frontiers in Chemistry, August 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (57th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

twitter
4 X users

Readers on

mendeley
2 Mendeley
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Title
Computation-accelerated discovery of the K2NiF4-type oxyhydrides combing density functional theory and machine learning approach
Published in
Frontiers in Chemistry, August 2022
DOI 10.3389/fchem.2022.964953
Pubmed ID
Authors

Qiang Bai, Yunrui Duan, Jie Lian, Xiaomin Wang

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 50%
Professor > Associate Professor 1 50%
Readers by discipline Count As %
Unspecified 1 50%
Chemistry 1 50%
Attention Score in Context

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 26 August 2022.
All research outputs
#13,665,175
of 23,179,757 outputs
Outputs from Frontiers in Chemistry
#889
of 6,071 outputs
Outputs of similar age
#176,659
of 432,491 outputs
Outputs of similar age from Frontiers in Chemistry
#32
of 511 outputs
Altmetric has tracked 23,179,757 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,071 research outputs from this source. They receive a mean Attention Score of 2.1. This one has done well, scoring higher than 84% 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 432,491 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 57% of its contemporaries.
We're also able to compare this research output to 511 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 92% of its contemporaries.