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Analytical approaches for the characterization and quantification of nanoparticles in food and beverages

Overview of attention for article published in Analytical & Bioanalytical Chemistry, October 2016
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  • Good Attention Score compared to outputs of the same age and source (71st percentile)

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112 Mendeley
Title
Analytical approaches for the characterization and quantification of nanoparticles in food and beverages
Published in
Analytical & Bioanalytical Chemistry, October 2016
DOI 10.1007/s00216-016-9946-5
Pubmed ID
Authors

Monica Mattarozzi, Michele Suman, Claudia Cascio, Davide Calestani, Stefan Weigel, Anna Undas, Ruud Peters

Abstract

Estimating consumer exposure to nanomaterials (NMs) in food products and predicting their toxicological properties are necessary steps in the assessment of the risks of this technology. To this end, analytical methods have to be available to detect, characterize and quantify NMs in food and materials related to food, e.g. food packaging and biological samples following metabolization of food. The challenge for the analytical sciences is that the characterization of NMs requires chemical as well as physical information. This article offers a comprehensive analysis of methods available for the detection and characterization of NMs in food and related products. Special attention was paid to the crucial role of sample preparation methods since these have been partially neglected in the scientific literature so far. The currently available instrumental methods are grouped as fractionation, counting and ensemble methods, and their advantages and limitations are discussed. We conclude that much progress has been made over the last 5 years but that many challenges still exist. Future perspectives and priority research needs are pointed out. Graphical Abstract Two possible analytical strategies for the sizing and quantification of Nanoparticles: Asymmetric Flow Field-Flow Fractionation with multiple detectors (allows the determination of true size and mass-based particle size distribution); Single Particle Inductively Coupled Plasma Mass Spectrometry (allows the determination of a spherical equivalent diameter of the particle and a number-based particle size distribution).

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 112 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 22%
Researcher 16 14%
Student > Bachelor 11 10%
Professor 9 8%
Student > Master 9 8%
Other 21 19%
Unknown 21 19%
Readers by discipline Count As %
Chemistry 27 24%
Agricultural and Biological Sciences 16 14%
Environmental Science 10 9%
Materials Science 5 4%
Unspecified 5 4%
Other 16 14%
Unknown 33 29%
Attention Score in Context

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 05 January 2017.
All research outputs
#16,737,737
of 25,394,764 outputs
Outputs from Analytical & Bioanalytical Chemistry
#5,272
of 9,624 outputs
Outputs of similar age
#204,628
of 329,342 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#51
of 195 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,624 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 41st percentile – i.e., 41% 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 329,342 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 195 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.