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In this study, we demonstrate the use of cyclical low frequency signals with insulator-based dielectrophoresis (iDEP) devices for the separation of particles of similar characteristics and an experimental method for estimating particle DEP mobilities. A custom signal designer program was created using Matlab® and COMSOL Multiphysics® for the identification of specific low frequency signals aimed at separating particle mixtures by exploiting slight differences in surface charge (particle zeta potential) or particle size. For the separation by surface charge, a mixture of two types of 10 μm particles was analyzed and effectively separated employing both a custom step signal and a sawtooth left signal. Notably, these particles had the same shape, size, and surface functionalization as well as were made from the same substrate material. For the separation by size, a sample containing 2 μm and 5 μm particles was successfully separated using a custom step signal; these particles had the same shape, surface functionalization, were made from the same substrate materials, and had only a small difference in zeta potential (10 mV). Additionally, an experimental technique was developed to estimate the dielectrophoretic mobility of each particle type; this information was then utilized by the signal designer program. The technique developed in this study is readily applicable for designing signals capable of separating micron-sized particles of similar characteristics, such as microorganisms, where slight differences in cell size and the shape of surface charge could be effectively exploited. These findings open the possibility for applications in microbial screening using iDEP devices.

The application of nanoparticle in medicine is promising for the treatment of a wide variety of diseases. However, the slow progress in the field has resulted in relatively few therapies being translated into the clinic. Anisotropic synthetic protein nanoparticles (ASPNPs) show potential as a next-generation drug-delivery technology, due to their biocompatibility, biodegradability, and functionality. Even though ASPNPs have the potential to be used in a variety of applications, such as in the treatment of glioblastoma, there is currently no high-throughput technology for the processing of these particles. Insulator-based electrokinetics employ microfluidics devices that rely on electrokinetic principles to manipulate micro- and nanoparticles. These miniaturized devices can selectively trap and enrich nanoparticles based on their material characteristics, and subsequently release them, which allows for particle sorting and processing. In this study, we use insulator-based electrokinetic (EK) microdevices to characterize ASPNPs. We found that anisotropy strongly influences electrokinetic particle behavior by comparing compositionally identical anisotropic and non-anisotropic SPNPs. Additionally, we were able to estimate the empirical electrokinetic equilibrium parameter (eE EEC) for all SPNPs. This particle-dependent parameter can allow for the design of various separation and purification processes. These results show how promising the insulator-based EK microdevices are for the analysis and purification of clinically relevant SPNPs.

The present communication illustrates the use of simple electrokinetic devices for the assessment of the zeta potential of submicron polystyrene particles. A combination of manual and automatic particle tracking was employed. This approach allows for characterizing particles in the same conditions and devices in which they can be separated, e.g. dielectrophoretic separations; making the resulting data readily applicable.