Assessment of submicron particle zeta potential in simple electrokinetic microdevices

Abstract

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.

Simultaneous Determination of Linear and Nonlinear Electrophoretic Mobilities of Cells and Microparticles

“…With the purpose of characterizing the microparticles and cells, the parameters μ EO and μ EP (1) were estimated first following standard procedures, as reported elsewhere. , In addition to these attributes, which are key for the design of DC-iEK experiments, the novel recently defined parameter referred to as E EEC , (i.e., the electric field at which EP (3) , EOF drag, and EP (1) are balanced, resulting in v P = 0) was also measured. , This attribute allows extrapolating the expected applied voltages required to achieve the trapping of a particle or microorganism across different microfluidic DC-iEK devices. This applied voltage value is commonly referred as the “trapping voltage”, which is a system-dependent parameter, while E EEC is a system-independent parameter .…”

On the use of correction factors for the mathematical modeling of insulator based dielectrophoretic devices

“…Dielectrophoresis was first reported in 1951 by Dr. Herbert Pohl employing a rudimentary electrode‐based system . Since then, there have been numerous developments in DEP that have produced two main types of systems: electrode‐based DEP and insulator‐based DEP (iDEP) . This contribution is focused on the latter, with emphasis on the advancements in mathematical modeling of device performance.…”

“…Many research groups have dedicated significant efforts to the modeling of iDEP‐based microfluidic devices; a large majority of reports on DEP include modeling efforts . Mathematical modeling of any type of EK system is not a simple task, as several phenomena can arise in these devices, including particle size distribution, particle‐particle interactions , temperature gradients , electro thermal flows , and Joule heating effects .…”

A velocity program using the Kanade–Lucas–Tomasi feature‐tracking algorithm with demonstration for pressure and electroosmosis conditions

“…[24,25]. The zeta potential is the potential directly in contact with the bulk fluid [26]. This work demonstrates the accuracy and reliability when implementing a simple KLT feature‐tracking algorithm in the μPTV MATLAB program, which can be adopted into further microfluidic studies.…”

“…The μPTV MATLAB program is developed using computer vision toolboxes available in MATLAB and takes inspiration from the need to quantify the EOF velocity and the zeta potential during a study of EOF by Bosma et al [24,25]. The zeta potential is the potential directly in contact with the bulk fluid [26]. This work demonstrates the accuracy and reliability when implementing a simple KLT feature-tracking algorithm in the μPTV MATLAB program, which can be adopted into further microfluidic studies.…”