4.7 Review

Rational strategy for characterization of nanoscale particles by asymmetric- flow field flow fractionation: A tutorial

期刊

ANALYTICA CHIMICA ACTA
卷 809, 期 -, 页码 9-24

出版社

ELSEVIER
DOI: 10.1016/j.aca.2013.11.021

关键词

Field flow fractionation; Nanoparticle; Nanomaterial; Protocol; Optimization; Validation

向作者/读者索取更多资源

This tutorial proposes a comprehensive and rational measurement strategy that provides specific guidance for the application of asymmetric-flow field flow fractionation (A4F) to the size-dependent separation and characterization of nanoscale particles (NPs) dispersed in aqueous media. A range of fractionation conditions are considered, and challenging applications, including industrially relevant materials (e.g., metal NPs, asymmetric NPs), are utilized in order to validate and illustrate this approach. We demonstrate that optimization is material dependent and that polystyrene NPs, widely used as a reference standard for retention calibration in A4F, in fact represent a class of materials with unique selectivity, recovery and optimal conditions for fractionation; thus use of these standards to calibrate retention for other materials must be validated a posteriori. We discuss the use and relevance of different detection modalities that can potentially yield multi-dimensional and complementary information on NP systems. We illustrate the fractionation of atomically precise nanoclusters, which are the lower limit of the nanoscale regime. Conversely, we address the upper size limit for normal mode elution in A4F. The protocol for A4F fractionation, including the methods described in the present work is proposed as a standardized strategy to realize interlaboratory comparability and to facilitate the selection and validation of material-specific measurement parameters and conditions. It is intended for both novice and advanced users of this measurement technology. Published by Elsevier B.V.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据