AI Article Synopsis

  • Scientists use coacervate-based methods to help collect and analyze different substances in the environment.
  • One method called cloud point extraction (CPE) helps separate certain chemicals when the temperature rises.
  • The article suggests that CPE could help improve how we find tiny particles in samples and keep them stable for testing.*

Article Abstract

Coacervate-based techniques are intensively used in environmental analytical chemistry to enrich and extract different kinds of analytes. Most methods focus on the total content or the speciation of inorganic and organic substances. Size fractionation is less commonly addressed. Within coacervate-based techniques, cloud point extraction (CPE) is characterized by a phase separation of non-ionic surfactants dispersed in an aqueous solution when the respective cloud point temperature is exceeded. In this context, the feature article raises the following question: May CPE in future studies serve as a key tool (i) to enrich and extract nanoparticles (NPs) from complex environmental matrices prior to analyses and (ii) to preserve the colloidal status of unstable environmental samples? With respect to engineered NPs, a significant gap between environmental concentrations and size- and element-specific analytical capabilities is still visible. CPE may support efforts to overcome this "concentration gap" via the analyte enrichment. In addition, most environmental colloidal systems are known to be unstable, dynamic, and sensitive to changes of the environmental conditions during sampling and sample preparation. This delivers a so far unsolved "sample preparation dilemma" in the analytical process. The authors are of the opinion that CPE-based methods have the potential to preserve the colloidal status of these instable samples. Focusing on NPs, this feature article aims to support the discussion on the creation of a convention called the "CPE extractable fraction" by connecting current knowledge on CPE mechanisms and on available applications, via the uncertainties visible and modeling approaches available, with potential future benefits from CPE protocols.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5061829PMC
http://dx.doi.org/10.1007/s00216-016-9873-5DOI Listing

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