A method for assessing nanomaterial dispersion quality based on principal component analysis of particle size distribution data

Seemingly contradictory findings between studies are a major issue in nanoecotoxicological research and have been explained as a result of the lack of comparability between assay methods, with dispersion of nanomaterials being identified as a key factor. Here we show the use of a multivariate method...

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Bibliographic Details
Published in:Particuology 2015-10, Vol.22 (5), p.30-38
Main Authors: Tantra, R., Oksel, C., Robinson, K.N., Sikora, A., Wang, X.Z., Wilkins, T.A.
Format: Article
Language:English
Subjects:
Dispersion
Nanomaterial characterization
Nanotoxicology
Particle size distribution
Principal component analysis
主成分分析
分布数据
分散
实验室数据
数据挖掘工具
粒度
纳米材料
质量评价方法
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Summary:Seemingly contradictory findings between studies are a major issue in nanoecotoxicological research and have been explained as a result of the lack of comparability between assay methods, with dispersion of nanomaterials being identified as a key factor. Here we show the use of a multivariate method, principal component analysis （PCA）, as a tool in protocol development and categorization of dispersion quality. Results show the significance of particle concentration within a protocol, and its effect on repeatability. Our results suggest that future studies should involve the use of PCA as a powerful data exploration tool to facilitate method development, comparability and integration of data across different laboratories.
ISSN:1674-2001
2210-4291
DOI:10.1016/j.partic.2014.10.004