| Title |
Molecular dynamics simulation of persistent slip bands formation in nickel-base superalloys
|
|---|---|
| Published in |
Machine Intelligence Research, December 2016
|
| DOI | 10.1007/s11633-016-1035-x |
| Authors |
Jian-Feng Huang, Zhong-Lai Wang, Er-Fu Yang, Don McGlinchey, Yuan-Xin Luo, Yun Li, Yi Chen |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 1 | 50% |
| United Kingdom | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 31 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 16% |
| Student > Ph. D. Student | 4 | 13% |
| Student > Master | 4 | 13% |
| Professor | 3 | 10% |
| Student > Bachelor | 3 | 10% |
| Other | 4 | 13% |
| Unknown | 8 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 8 | 26% |
| Materials Science | 8 | 26% |
| Physics and Astronomy | 2 | 6% |
| Psychology | 1 | 3% |
| Computer Science | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 10 | 32% |
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 27 November 2018.
All research outputs
#19,944,091
of 25,373,627 outputs
Outputs from Machine Intelligence Research
#186
of 444 outputs
Outputs of similar age
#304,722
of 422,399 outputs
Outputs of similar age from Machine Intelligence Research
#8
of 14 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 444 research outputs from this source. They receive a mean Attention Score of 2.5. This one is in the 48th percentile – i.e., 48% 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 422,399 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.