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Mendeley readers
Attention Score in Context
| Title |
Atomic force microscopy analysis of nanoparticles in non-ideal conditions
|
|---|---|
| Published in |
Discover Nano, August 2011
|
| DOI | 10.1186/1556-276x-6-514 |
| Pubmed ID | |
| Authors |
Petr Klapetek, Miroslav Valtr, David Nečas, Ota Salyk, Petr Dzik |
| Abstract |
Nanoparticles are often measured using atomic force microscopy or other scanning probe microscopy methods. For isolated nanoparticles on flat substrates, this is a relatively easy task. However, in real situations, we often need to analyze nanoparticles on rough substrates or nanoparticles that are not isolated. In this article, we present a simple model for realistic simulations of nanoparticle deposition and we employ this model for modeling nanoparticles on rough substrates. Different modeling conditions (coverage, relaxation after deposition) and convolution with different tip shapes are used to obtain a wide spectrum of virtual AFM nanoparticle images similar to those known from practice. Statistical parameters of nanoparticles are then analyzed using different data processing algorithms in order to show their systematic errors and to estimate uncertainties for atomic force microscopy analysis of nanoparticles under non-ideal conditions. It is shown that the elimination of user influence on the data processing algorithm is a key step for obtaining accurate results while analyzing nanoparticles measured in non-ideal conditions. |
Mendeley readers
The data shown below were compiled from readership statistics for 193 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Russia | 2 | 1% |
| Germany | 1 | <1% |
| Austria | 1 | <1% |
| Italy | 1 | <1% |
| South Africa | 1 | <1% |
| Japan | 1 | <1% |
| Unknown | 186 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 46 | 24% |
| Researcher | 35 | 18% |
| Student > Bachelor | 20 | 10% |
| Student > Master | 19 | 10% |
| Professor > Associate Professor | 8 | 4% |
| Other | 25 | 13% |
| Unknown | 40 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Physics and Astronomy | 40 | 21% |
| Chemistry | 28 | 15% |
| Materials Science | 22 | 11% |
| Engineering | 18 | 9% |
| Agricultural and Biological Sciences | 11 | 6% |
| Other | 24 | 12% |
| Unknown | 50 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 25 August 2022.
All research outputs
#2,088,857
of 25,373,627 outputs
Outputs from Discover Nano
#23
of 1,146 outputs
Outputs of similar age
#9,971
of 135,479 outputs
Outputs of similar age from Discover Nano
#1
of 19 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,146 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done particularly well, scoring higher than 97% 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 135,479 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 92% of its contemporaries.
We're also able to compare this research output to 19 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 94% of its contemporaries.