Simulation-Guided Tracer Optimization for Magnetic Particle Spectroscopy: Interplay of Core, Shell and Anisotropy...

Detection of magnetic nanoparticles (MNP) relies on their nonlinear magnetic response, changing with the local environment in vivo. Employing an effective viscosity model within stochastic coupled Néel-Brownian simulations, we quantify how viscosity (0.8-50 000 mPa·s) affects signal intensity of single-frequency magnetic particle spectroscopy (MPS, 25 kHz) and frequency-mixing MPS (FM-MPS; f_H = 40.5 kHz, f_L = 0.063 kHz). We investigate single-core, non-interacting MNP with various core sizes (12-28 nm), hydrodynamic shell thicknesses (5-100 nm), and anisotropy (4-200 kJ m^{- 3}), using dominant readouts (MPS: third-harmonic; FM-MPS: f_H + 2f_L mixing-term). Increasing viscosity progressively suppresses Brownian rotation, with thicker shells affected at lower viscosities, and drives signals toward an immobilization plateau. Under the simulated conditions, MNP appear distinguishable in blood-associated viscosities using MPS, whereas distinguishability is pronounced in cellular/tissue-like viscosities with FM-MPS. Moderate anisotropy (∼20-40 kJ m^{- 3}) enhances signals by ∼10%, whereas higher anisotropies suppress relaxation, finally collapsing the signal. While large cores maximize the signal at fixed particle number, dosage-normalized conditions suggest favorable performance for intermediate cores (∼15-18 nm). These results propose a cohesive framework linking particle properties, excitation scheme, and physiological environment, thereby providing insight into MNP tracer optimization for biosensing, cell tracking, imaging, and in vivo diagnostics.