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

A. Yadav, Ronald Calhoun, Patrick Phelan, A. K. Vuppu, Antonio Garcia, Mark Hayes

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Novel biochemical sensors consisting of rotating chains of microscale paramagnetic particles have been proposed that would enable convenient, sensitive analyte detection. Predicting the dynamics of these particles is required to optimise their design. The results of lattice Boltzmann (LB) and particle dynamics (PD) simulations are reported, where the LB approach provides a verified solution of the complete Navier-Stokes equations, including the hydrodynamic interactions among the particles. On the other hand, the simpler PD approach neglects hydrodynamic interactions, and does not compute the fluid motion. It is shown that macroscopic properties, like the number of aggregated particles, depend only on the drag force and not on the total hydrodynamic force, making PD simulations yield reasonably accurate predictions. Relatively good agreement between the LB and PD simulations, and qualitative agreement with experimental data, are found for the number of aggregated particles as a function of the Mason number. The drag force on a rotating cylinder is significantly different from that on particle chains calculated from both simulations, demonstrating the different dynamics between the two cases. For microscopic quantities like the detailed force distributions on each particle, the complete Navier-Stokes solution, here represented by the LB simulation, is required.

Original languageEnglish (US)
Pages (from-to)145-150
Number of pages6
JournalIEE Proceedings: Nanobiotechnology
Volume153
Issue number6
DOIs
StatePublished - 2006

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Materials Science (miscellaneous)
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Dynamics of rotating paramagnetic particles simulated by lattice Boltzmann and particle dynamics methods'. Together they form a unique fingerprint.

Cite this