A method for assessing nanomaterial dispersion quality based on principal component analysis of particle size distribution data |
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| Institution: | 1. National Physical Laboratory, Hampton Road, Teddington, Middlesex TW11 0LW, UK;2. Institute of Particle Science and Engineering, School of Chemical and Process Engineering, University of Leeds, Leeds LS2 9JT, UK;1. Faculty of Engineering, Tel Aviv University, 69978 Ramat Aviv, Israel;2. Department of Mechanical Engineering, Boston University, 110 Cummington St., Boston, MA 02215, USA;3. Department of Mechanical, Aerospace and Nuclear Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA;1. Leidos Corporation, Raleigh, NC, USA;2. Geophysical Fluid Dynamics Institute and Earth, Ocean and Atmospheric Science, Florida State University, Tallahassee, FL, USA;3. University of West Florida, Pensacola, FL, USA;4. Earth, Ocean and Atmospheric Science, Florida State University, Tallahassee, FL, USA;5. Colorado Center for Astrodynamics Research, University of Colorado, Boulder, CO, USA;1. Chair of Analytical Chemistry, Faculty of Chemistry, Warsaw University of Technology, Noakowskiego St. 3, 00-664 Warsaw, Poland;2. Chair of Medical Biotechnology, Faculty of Chemistry, Warsaw University of Technology, Noakowskiego St. 3, 00-664 Warsaw, Poland;3. Institute of Inorganic Chemistry, University of Vienna, Waehringer Str. 42, A-1090, Vienna, Austria;4. Vernadsky Institute of Geochemistry and Analytical Chemistry, Kosygin St. 19, 119991 Moscow, Russian Federation |
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| Abstract: | 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. |
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| Keywords: | Nanomaterial characterization Principal component analysis Nanotoxicology Dispersion Particle size distribution |
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