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Magnetic Particle Imaging (MPI) uses ferrofluids based on superparamagnetic iron-oxide nanoparticles (SPIONs) as
a tracer, whose induced voltage in the receive coils is the measured signal. Image reconstruction is often done with
the system matrix approach, which needs the signal of a test sample at each position for which the concentration
should be reconstructed. In a scanner with a three dimensional reconstruction volume, this measurement becomes
very time consuming. Functional parameters such as the temperature might also be reconstructed with a system
matrix approach but would require additional system matrices to be measured. Simulation models for the ferrofluid’s
magnetic behavior might be a solution to this problem, if they are sufficiently fast and precise. Here, we compare
the prediction quality and computational cost of the commonly used Debye model with the new Refined Debye
model on a viscosity measurement.