Dynamics of rotating paramagnetic particles simulated by lattice Boltzmann and particle dynamics methods

Area of Science:

• Biochemical sensing
• Microfluidics
• Computational physics

Background:

• Novel biochemical sensors utilize rotating chains of microscale paramagnetic particles.
• Predicting particle dynamics is crucial for optimizing sensor design and performance.

Purpose of the Study:

• To compare Lattice Boltzmann (LB) and Particle Dynamics (PD) simulations for predicting the behavior of paramagnetic particle chains in sensors.
• To determine the necessary simulation fidelity for accurate prediction of macroscopic and microscopic properties.

Main Methods:

• Lattice Boltzmann (LB) simulations solving Navier-Stokes equations, including hydrodynamic interactions.
• Particle Dynamics (PD) simulations neglecting hydrodynamic interactions and fluid motion.
• Comparison of simulation results with each other and with experimental data.

Main Results:

• Macroscopic properties, such as particle aggregation, depend primarily on drag force, validating the simpler PD approach for these aspects.
• Good agreement was found between LB and PD simulations for aggregated particle numbers versus the Mason number.
• Significant differences were observed in drag force calculations between rotating cylinders and particle chains, highlighting distinct dynamics.

Conclusions:

• Particle Dynamics simulations provide reasonably accurate predictions for macroscopic properties of paramagnetic particle chains in sensors.
• Lattice Boltzmann simulations are essential for capturing microscopic details like individual particle force distributions.
• The choice of simulation method depends on the required level of detail for sensor design optimization.