Dissipative particle dynamics for modeling micro-objects in microfluidics: application to dielectrophoresis

Area of Science:

• Computational physics
• Microfluidics engineering
• Biophysics

Background:

• Microfluidic devices enable precise manipulation of micro-objects.
• Simulating micro-object behavior in low Reynolds number flows is challenging.
• Accurate modeling is crucial for designing effective microfluidic systems.

Purpose of the Study:

• To develop and validate a Dissipative Particle Dynamics (DPD) model for micro-object trajectories in microfluidics.
• To simulate micro-object deflection under external forces, specifically dielectrophoresis.
• To compare simulation results with experimental data from a fabricated microfluidic device.

Main Methods:

• Utilized an in-house Fortran code for DPD simulations of Stokes flow (Re=0.01).
• Developed a mapping algorithm to scale external forces between physical and DPD domains.
• Fabricated a microfluidic device and conducted experiments with red blood cells under dielectrophoretic forces.

Main Results:

• DPD parameters were adjusted to accurately replicate Stokes flow.
• Simulated trajectories of red blood cells under dielectrophoretic force showed good agreement with analytical predictions.
• Experimental results from the microfluidic device validated the simulation model.

Conclusions:

• DPD is a viable technique for simulating micro-object dynamics in microfluidic devices.
• The developed mapping algorithm effectively bridges DPD simulations and real-world forces.
• The study demonstrates good correlation between numerical predictions and experimental outcomes in microfluidic systems.