A simulation framework for particle magnetization dynamics of large ensembles of single domain particles: Numerical treatment of Brown/N\'{e}el dynamics and parameter identification problems in magnetic particle imaging

TL;DR

This paper introduces a unified simulation framework for modeling the magnetization dynamics of large ensembles of single domain magnetic nanoparticles, addressing Brownian and Néel mechanisms, and applies it to parameter identification in magnetic particle imaging.

Contribution

It develops a novel computational framework for simulating particle magnetization dynamics and solving parameter identification problems in magnetic particle imaging.

Findings

Framework accurately models Brownian and Néel dynamics.

Numerical results align well with experimental data.

Enables effective parameter estimation in MPI applications.

Abstract

Magnetic nanoparticles and their magnetization dynamics play an important role in many applications. We focus on magnetization dynamics in large ensembles of single domain nanoparticles being characterized by either Brownian or N\'{e}el rotation mechanisms. Simulations of the respective behavior are obtained by solving advection-diffusion equations on the sphere, for which a unified computational framework is developed and investigated. This builds the basis for solving two parameter identification problems, which are formulated in the context of the chosen application, magnetic particle imaging. The functionality of the computational framework is illustrated by numerical results in the parameter identification problems either compared quantitatively or qualitatively to measured data.