| Title |
Modeling Mechanism and Growth Reactions for New Nanofabrication Processes by Atomic Layer Deposition
|
|---|---|
| Published in |
Advanced Materials, December 2015
|
| DOI | 10.1002/adma.201504043 |
| Pubmed ID | |
| Authors |
Simon D Elliott, Gangotri Dey, Yasheng Maimaiti, Hayrensa Ablat, Ekaterina A Filatova, Glen N Fomengia |
| Abstract |
Recent progress in the simulation of the chemistry of atomic layer deposition (ALD) is presented for technologically important materials such as alumina, silica, and copper metal. Self-limiting chemisorption of precursors onto substrates is studied using density functional theory so as to determine reaction pathways and aid process development. The main challenges for the future of ALD modeling are outlined. |
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 % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 2% |
| Ireland | 2 | 2% |
| Netherlands | 1 | <1% |
| Korea, Republic of | 1 | <1% |
| Finland | 1 | <1% |
| Sweden | 1 | <1% |
| Unknown | 112 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 37 | 31% |
| Researcher | 24 | 20% |
| Student > Master | 11 | 9% |
| Student > Doctoral Student | 9 | 8% |
| Student > Bachelor | 9 | 8% |
| Other | 15 | 13% |
| Unknown | 15 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Materials Science | 27 | 23% |
| Engineering | 26 | 22% |
| Chemistry | 23 | 19% |
| Physics and Astronomy | 13 | 11% |
| Chemical Engineering | 8 | 7% |
| Other | 3 | 3% |
| Unknown | 20 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 20 March 2019.
All research outputs
#15,403,045
of 24,417,958 outputs
Outputs from Advanced Materials
#11,495
of 16,282 outputs
Outputs of similar age
#213,474
of 398,680 outputs
Outputs of similar age from Advanced Materials
#178
of 226 outputs
Altmetric has tracked 24,417,958 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 16,282 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.1. This one is in the 27th percentile – i.e., 27% 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 398,680 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 226 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.