Abstract

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, σp=25.8 mS/m and KS=1.29 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.

Highlights

  • The electrical properties of nanoparticles play a key role in determining their dispersive behavior in aqueous solution

  • Advancing earlier work involving dual-cycle pulsed Positive dielectrophoretic (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

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Summary

Introduction

The electrical properties of nanoparticles play a key role in determining their dispersive behavior in aqueous solution. Charge screening and mutual nanoparticle repulsion, for example, are influenced by co- and counterions associated with the electrical double layer. Nanoparticle electrical properties are in turn dependent on their intended application, for instance, biological labeling influences nanoparticle surface charge as well as other properties [3]. An important electrokinetic laboratory technique for nanoparticle electrical DEP is a powerful technique that has become popular in recent years due to the convenience with which it can be integrated into lab-on-chip platforms [6,7,8]

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