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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Deep Learning for Photonic Design and Analysis: Principles and Applications
|
|---|---|
| Published in |
Frontiers in Materials, January 2022
|
| DOI | 10.3389/fmats.2021.791296 |
| Authors |
Bing Duan, Bei Wu, Jin-hui Chen, Huanyang Chen, Da-Quan Yang |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Colombia | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 23% |
| Student > Ph. D. Student | 3 | 14% |
| Student > Master | 2 | 9% |
| Professor | 1 | 5% |
| Unspecified | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 9 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 7 | 32% |
| Physics and Astronomy | 3 | 14% |
| Mathematics | 1 | 5% |
| Materials Science | 1 | 5% |
| Unspecified | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 9 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 16 January 2024.
All research outputs
#2,824,673
of 25,187,238 outputs
Outputs from Frontiers in Materials
#40
of 3,007 outputs
Outputs of similar age
#67,294
of 517,032 outputs
Outputs of similar age from Frontiers in Materials
#3
of 204 outputs
Altmetric has tracked 25,187,238 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,007 research outputs from this source. They receive a mean Attention Score of 1.6. 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 517,032 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 204 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 99% of its contemporaries.