Study about the nanoparticle agglomeration in a magnetic nanofluid by the Langevin dynamics simulation model using an effective Verlet-type algorithm

Abstract

This paper presents a modelling study about the nanoparticle agglomeration in magnetic nanofluids. The colloidal magnetic nanoparticles size distribution is subjected to simultaneous translation and rotation movements under the action of conservative and dissipative forces, with their respective moments. In order to obtain the numerical solution of the coupled equations of motion, we use a Langevin dynamics stochastic method based on an effective Verlet-type algorithm. The presented model is based on an easy-to-implement integrator. We apply a number of analytical techniques to assess the performance of the method. The model has been tested on a magnetite nanoparticle-based nanofluid. Finally, the paper presents a number of structures obtained in various physical conditions, discussing the retrieved results of modelling and simulation. In weak external magnetic field, the nanoparticles form arrangements like linear chains or dense globes and rings, with magnetic moments rotating in both directions (both clockwise and counterclockwise). These arrangements, in vortex and toroidal states, are reported in actual scientific literature and open new perspectives for understanding the behaviour of nanofluids, with applications in engineering and medicine. Chains are predominant in high external magnetic, with local magnetic moments mainly orientated mainly along the direction of the applied field.