Our recent work titled "Applying Stochastic Langevin Function with Coupled Brownian-Néel Relaxations to Study the Dynamic Magnetizations of Nanoparticle Tracers in Magnetic Particle Imaging" was published in the Journal of Physics D: Applied Physics.
Most theoretical studies in magnetic particle imaging (MPI) rely on the static Langevin function to describe the magnetization responses of superparamagnetic iron oxide nanoparticle (SPION) tracers. However, under a rapidly oscillating excitation field (typically tens of kHz), the magnetic relaxation time of SPION tracers becomes significant, making the static Langevin function inadequate for accurately modeling their magnetic signals in MPI.
In this work, we apply a stochastic Langevin function with coupled Brownian-Néel relaxation models to investigate the dynamic magnetization responses of SPION tracers in MPI. We model the time-domain magnetization response (M-t curve), dynamic magnetization-field hysteresis loops (M-H curve), and point spread functions (PSF) for different SPION tracer designs with varying physical and magnetic properties.

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