| Title |
Designing hierarchical nanoporous membranes for highly efficient gas adsorption and storage
|
|---|---|
| Published in |
Science Advances, October 2020
|
| DOI | 10.1126/sciadv.abb0694 |
| Pubmed ID | |
| Authors |
Haiyan Mao, Jing Tang, Jun Chen, Jiayu Wan, Kaipeng Hou, Yucan Peng, David M Halat, Liangang Xiao, Rufan Zhang, Xudong Lv, Ankun Yang, Yi Cui, Jeffrey A Reimer |
X Demographics
The data shown below were collected from the profiles of 23 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 13% |
| India | 2 | 9% |
| United Kingdom | 1 | 4% |
| Canada | 1 | 4% |
| Paraguay | 1 | 4% |
| Spain | 1 | 4% |
| Kenya | 1 | 4% |
| Japan | 1 | 4% |
| Belize | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 11 | 48% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 16 | 70% |
| Scientists | 5 | 22% |
| Science communicators (journalists, bloggers, editors) | 2 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 67 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 22% |
| Researcher | 6 | 9% |
| Student > Doctoral Student | 4 | 6% |
| Student > Master | 3 | 4% |
| Student > Bachelor | 2 | 3% |
| Other | 6 | 9% |
| Unknown | 31 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Materials Science | 10 | 15% |
| Chemical Engineering | 9 | 13% |
| Chemistry | 6 | 9% |
| Energy | 2 | 3% |
| Environmental Science | 2 | 3% |
| Other | 4 | 6% |
| Unknown | 34 | 51% |
Attention Score in Context
This research output has an Altmetric Attention Score of 115. 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 15 August 2022.
All research outputs
#363,701
of 25,387,668 outputs
Outputs from Science Advances
#2,749
of 12,215 outputs
Outputs of similar age
#10,868
of 434,919 outputs
Outputs of similar age from Science Advances
#121
of 553 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,215 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 120.3. This one has done well, scoring higher than 77% 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 434,919 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 553 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.