Molecular dynamics modelling of interacting magnetic nanoparticles for investigating equilibrium and dynamic ensemble properties

Magnetic nanoparticles have the potential to be used in various biomedical applications, including magnetic drug targeting and hyperthermia for cancer treatment. In both cases, precise prediction of the local particle concentration is required to plan a successful therapy, which is a challenging task due to several complex flow phenomena. Computational macroscopic and microscopic models have been developed to support this process, but they have limitations in terms of interactions implementation, micromagnetic dynamics or computational costs. This study aims to develop a model that can represent micromagnetic dynamics and being employed to study equilibrium properties of particle ensembles in viscous media. Therefore, a kinetic Monte Carlo method in combination with Langevin equations is used. So, magnetization dynamics and mechanical motion can be simulated in combination very efficiently. The new model is validated with another model based on the stochastic Landau-Lifshitz-Gilbert equation. Various interaction potentials like Van der Waals, steric and electrostatic interactions are included to study their specific influence on structural properties. Also, methods to control the errors while integrating the equations of motion and using the Ewald method for calculating interaction quantities are implemented. As a validation we studied equilibrium and time dependent properties of non-interacting particle ensembles as well as errors made by the Ewald-method used for interaction quantities calculation. In all studies we found very good agreement of the simulation results with the theoretical predictions. The developed models can now be used for investigating equilibrium and dynamic properties of ferrofluids, or more general for biomedical research for magnetic drug targeting, hyperthermia, or imaging techniques. Furthermore, the new hybrid model can be also used for simulations in the range of milliseconds with reasonable computational effort.