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Real‐time dielectrophoretic signaling and image quantification methods for evaluating electrokinetic properties of nanoparticles
Real‐time image signaling and quantification methods are described that allow easy‐to‐use, fast extraction of the electrical properties of nanoparticles. Positive dielectrophoretic (pDEP) collection rate analysis enables the dielectric properties of very small samples of nanoparticles to be accurate...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5034756/ https://www.ncbi.nlm.nih.gov/pubmed/25872874 http://dx.doi.org/10.1002/elps.201400500 |
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author | Bakewell, David J. Bailey, Joe Holmes, David |
author_facet | Bakewell, David J. Bailey, Joe Holmes, David |
author_sort | Bakewell, David J. |
collection | PubMed |
description | Real‐time image signaling and quantification methods are described that allow easy‐to‐use, fast extraction of the electrical properties of nanoparticles. Positive dielectrophoretic (pDEP) collection rate analysis enables the dielectric properties of very small samples of nanoparticles to be accurately quantified. Advancing earlier work involving dual‐cycle pulsed pDEP 1 collection experiments, we report the development of a statistical image quantification method that significantly advances the evaluation of nanoparticle dielectric properties. Compared with traditional methods that require information about the geometry of the electrode array to be entered for semiautomated quantification 2, the new statistical approach described does not require a priori knowledge of device geometry. The efficacy of the statistical method is experimentally demonstrated using 200 nm diameter latex nanospheres, suspended in low conductivity medium, that are attracted by pDEP onto planar castellated electrode arrays with 5‐micron‐sized features. The method is shown to yield estimates for the nanoparticle conductivity and surface conductance, [Formula: see text] mS/m and [Formula: see text] nS, that concur closely with those obtained using traditional geometric methods previously reported 1. Consequently, the statistical method is accurate, fast, robust, supervisor‐free, and useful for determining nanoparticle electrokinetic parameters. |
format | Online Article Text |
id | pubmed-5034756 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-50347562016-10-03 Real‐time dielectrophoretic signaling and image quantification methods for evaluating electrokinetic properties of nanoparticles Bakewell, David J. Bailey, Joe Holmes, David Electrophoresis Part II: Advances in Fabrication and Instrumentation Real‐time image signaling and quantification methods are described that allow easy‐to‐use, fast extraction of the electrical properties of nanoparticles. Positive dielectrophoretic (pDEP) collection rate analysis enables the dielectric properties of very small samples of nanoparticles to be accurately quantified. Advancing earlier work involving dual‐cycle pulsed pDEP 1 collection experiments, we report the development of a statistical image quantification method that significantly advances the evaluation of nanoparticle dielectric properties. Compared with traditional methods that require information about the geometry of the electrode array to be entered for semiautomated quantification 2, the new statistical approach described does not require a priori knowledge of device geometry. The efficacy of the statistical method is experimentally demonstrated using 200 nm diameter latex nanospheres, suspended in low conductivity medium, that are attracted by pDEP onto planar castellated electrode arrays with 5‐micron‐sized features. The method is shown to yield estimates for the nanoparticle conductivity and surface conductance, [Formula: see text] mS/m and [Formula: see text] nS, that concur closely with those obtained using traditional geometric methods previously reported 1. Consequently, the statistical method is accurate, fast, robust, supervisor‐free, and useful for determining nanoparticle electrokinetic parameters. John Wiley and Sons Inc. 2015-07-06 2015-07 /pmc/articles/PMC5034756/ /pubmed/25872874 http://dx.doi.org/10.1002/elps.201400500 Text en © 2015 The Authors. ELECTROPHORESIS Published by WILEY‐VCH Verlag GmbH & Co. KGaA This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Part II: Advances in Fabrication and Instrumentation Bakewell, David J. Bailey, Joe Holmes, David Real‐time dielectrophoretic signaling and image quantification methods for evaluating electrokinetic properties of nanoparticles |
title | Real‐time dielectrophoretic signaling and image quantification methods for evaluating electrokinetic properties of nanoparticles |
title_full | Real‐time dielectrophoretic signaling and image quantification methods for evaluating electrokinetic properties of nanoparticles |
title_fullStr | Real‐time dielectrophoretic signaling and image quantification methods for evaluating electrokinetic properties of nanoparticles |
title_full_unstemmed | Real‐time dielectrophoretic signaling and image quantification methods for evaluating electrokinetic properties of nanoparticles |
title_short | Real‐time dielectrophoretic signaling and image quantification methods for evaluating electrokinetic properties of nanoparticles |
title_sort | real‐time dielectrophoretic signaling and image quantification methods for evaluating electrokinetic properties of nanoparticles |
topic | Part II: Advances in Fabrication and Instrumentation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5034756/ https://www.ncbi.nlm.nih.gov/pubmed/25872874 http://dx.doi.org/10.1002/elps.201400500 |
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