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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Accelerated Atomistic Modeling of Solid-State Battery Materials With Machine Learning
|
|---|---|
| Published in |
Frontiers in Energy Research, June 2021
|
| DOI | 10.3389/fenrg.2021.695902 |
| Authors |
Haoyue Guo, Qian Wang, Annika Stuke, Alexander Urban, Nongnuch Artrith |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 10% |
| United States | 1 | 10% |
| Netherlands | 1 | 10% |
| United Kingdom | 1 | 10% |
| Unknown | 6 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 70% |
| Scientists | 3 | 30% |
Mendeley readers
The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 100 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 19 | 19% |
| Student > Ph. D. Student | 14 | 14% |
| Student > Doctoral Student | 8 | 8% |
| Student > Bachelor | 6 | 6% |
| Student > Master | 5 | 5% |
| Other | 6 | 6% |
| Unknown | 42 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Materials Science | 16 | 16% |
| Chemistry | 11 | 11% |
| Engineering | 7 | 7% |
| Energy | 7 | 7% |
| Chemical Engineering | 3 | 3% |
| Other | 9 | 9% |
| Unknown | 47 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 08 June 2021.
All research outputs
#7,364,822
of 26,435,181 outputs
Outputs from Frontiers in Energy Research
#244
of 4,893 outputs
Outputs of similar age
#147,589
of 465,100 outputs
Outputs of similar age from Frontiers in Energy Research
#14
of 224 outputs
Altmetric has tracked 26,435,181 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 4,893 research outputs from this source. They receive a mean Attention Score of 1.6. This one has done particularly well, scoring higher than 95% 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 465,100 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 68% of its contemporaries.
We're also able to compare this research output to 224 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 93% of its contemporaries.