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An improved two‐dimensional (2,4) finite‐difference time‐domain method for Lorentz dispersive media

Overview of attention for article published in International Journal of Numerical Modelling, May 2024
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Title
An improved two‐dimensional (2,4) finite‐difference time‐domain method for Lorentz dispersive media
Published in
International Journal of Numerical Modelling, May 2024
DOI 10.1002/jnm.3244
Authors

Theodoros T. Zygiridis, Stamatios A. Amanatiadis, Nikolaos V. Kantartzis

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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 14 May 2024.
All research outputs
#17,745,659
of 26,012,510 outputs
Outputs from International Journal of Numerical Modelling
#29
of 83 outputs
Outputs of similar age
#115,928
of 227,561 outputs
Outputs of similar age from International Journal of Numerical Modelling
#1
of 1 outputs
Altmetric has tracked 26,012,510 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 83 research outputs from this source. They receive a mean Attention Score of 1.7. This one has gotten more attention than average, scoring higher than 56% 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 227,561 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them