Separation and characterization of nanoparticles in complex food and environmental samples by field-flow fractionation
The thorough analysis of natural nanoparticles (NPs) and engineered NPs involves the sequence of detection, identification, quantification and, if possible, detailed characterization. In a complex or heterogeneous sample, each step of this sequence is an individual challenge, and, given suitable sample preparation, field-flow fractionation (FFF) is one of the most promising techniques to achieve relevant characterization. The objective of this review is to present the current status of FFF as an analytical separation technique for the study of NPs in complex food and environmental samples. FFF has been applied for separation of various types of NP (e.g., organic macromolecules, and carbonaceous or inorganic NPs) in different types of media (e.g., natural waters, soil extracts or food samples). FFF can be coupled to different types of detectors that offer additional information and specificity, and the determination of size-dependent properties typically inaccessible to other techniques. The separation conditions need to be carefully adapted to account for specific particle properties, so quantitative analysis of heterogeneous or complex samples is difficult as soon as matrix constituents in the samples require contradictory separation conditions. The potential of FFF analysis should always be evaluated bearing in mind the impact of the necessary sample preparation, the information that can be retrieved from the chosen detection systems and the influence of the chosen separation conditions on all types of NP in the sample. A holistic methodological approach is preferable to a technique-focused one.
| Main Authors: | , , , , |
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| Format: | article biblioteca |
| Language: | eng |
| Subjects: | Q02 - Traitement et conservation des produits alimentaires, U30 - Méthodes de recherche, 000 - Autres thèmes, |
| Online Access: | http://agritrop.cirad.fr/577115/ http://agritrop.cirad.fr/577115/1/ID577115.pdf |
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