| Title |
Field flow fractionation techniques to explore the “nano-world”
|
|---|---|
| Published in |
Analytical & Bioanalytical Chemistry, January 2017
|
| DOI | 10.1007/s00216-017-0180-6 |
| Pubmed ID | |
| Authors |
Catia Contado |
| Abstract |
Field flow fractionation (FFF) techniques are used to successfully characterize several nanomaterials by sizing nano-entities and producing information about the aggregation/agglomeration state of nanoparticles. By coupling FFF techniques to specific detectors, researchers can determine particle-size distributions (PSDs), expressed as mass-based or number-based PSDs. This review considers FFF applications in the food, biomedical, and environmental sectors, mostly drawn from the past 4 y. It thus underlines the prominent role of asymmetrical flow FFF within the FFF family. By concisely comparing FFF techniques with other techniques suitable for sizing nano-objects, the advantages and the disadvantages of these instruments become clear. A consideration of select recent publications illustrates the state of the art of some lesser-known FFF techniques and innovative instrumental set-ups. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 135 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | <1% |
| South Africa | 1 | <1% |
| Unknown | 133 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 34 | 25% |
| Researcher | 23 | 17% |
| Student > Master | 15 | 11% |
| Student > Bachelor | 11 | 8% |
| Student > Doctoral Student | 8 | 6% |
| Other | 15 | 11% |
| Unknown | 29 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 31 | 23% |
| Biochemistry, Genetics and Molecular Biology | 11 | 8% |
| Engineering | 10 | 7% |
| Chemical Engineering | 7 | 5% |
| Agricultural and Biological Sciences | 6 | 4% |
| Other | 21 | 16% |
| Unknown | 49 | 36% |
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 22 March 2017.
All research outputs
#22,764,772
of 25,377,790 outputs
Outputs from Analytical & Bioanalytical Chemistry
#7,543
of 9,619 outputs
Outputs of similar age
#363,431
of 422,539 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#106
of 150 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,619 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 1st percentile – i.e., 1% 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 422,539 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 150 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.