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Machine Learning Assisted Discovery of Efficient MOFs for One-Step C2H4 Purification from Ternary C2H2/C2H4/C2H6 Mixtures

Overview of attention for article published in Journal of Chemical & Engineering Data, June 2024
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Title
Machine Learning Assisted Discovery of Efficient MOFs for One-Step C2H4 Purification from Ternary C2H2/C2H4/C2H6 Mixtures
Published in
Journal of Chemical & Engineering Data, June 2024
DOI 10.1021/acs.jced.4c00244
Authors

Tongan Yan, Zhengqing Zhang, Chongli Zhong

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Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 28 June 2024.
All research outputs
#23,535,922
of 26,205,030 outputs
Outputs from Journal of Chemical & Engineering Data
#1,461
of 1,546 outputs
Outputs of similar age
#121,389
of 153,901 outputs
Outputs of similar age from Journal of Chemical & Engineering Data
#2
of 2 outputs
Altmetric has tracked 26,205,030 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,546 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 153,901 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.