Low frequency cyclical potentials for fine tuning insulator-based dielectrophoretic separations.

Area of Science:

• Biophysics
• Microfluidics
• Particle Separation Science

Background:

• Separating particles with similar characteristics, such as microorganisms, presents a significant challenge in various scientific fields.
• Existing methods often struggle to differentiate particles based on subtle variations in size or surface charge.

Purpose of the Study:

• To demonstrate the efficacy of cyclical low frequency signals with insulator-based dielectrophoresis (iDEP) for separating particles with similar properties.
• To develop an experimental method for estimating particle dielectrophoretic (DEP) mobilities to aid in signal design.

Main Methods:

• Custom signal designer program developed using Matlab® and COMSOL Multiphysics® to identify optimal low-frequency signals.
• Utilized iDEP devices to separate mixtures of 10 µm particles based on surface charge differences.
• Separated mixtures of 2 µm and 5 µm particles based on size differences using custom step signals.

Main Results:

• Successfully separated 10 µm particles with identical size, shape, and material but different zeta potentials using custom step and sawtooth left signals.
• Achieved separation of 2 µm and 5 µm particles with minimal zeta potential difference (10 mV) using a custom step signal.
• Developed and validated an experimental technique for estimating particle DEP mobilities, integrated into the signal design program.

Conclusions:

• The developed technique enables the design of signals for separating micron-sized particles with subtle differences in characteristics.
• This approach holds significant potential for applications in microbial screening and other fields requiring precise particle differentiation.