Frequency-based nanoparticle sensing over large field ranges using the ferromagnetic resonances of a magnetic nanodisc

Abstract

Using finite element micromagnetic simulations, we study how resonant magnetisation dynamics in thin magnetic discs with perpendicular anisotropy are influenced by magnetostatic coupling to a magnetic nanoparticle. We identify resonant modes within the disc using direct magnetic eigenmode calculations and study how their frequencies and profiles are changed by the nanoparticle's stray magnetic field. We demonstrate that particles can generate shifts in the resonant frequency of the disc's fundamental mode which exceed resonance linewidths in recently studied spin torque oscillator devices. Importantly, it is shown that the simulated shifts can be maintained over large field ranges (here up to 1 T). This is because the resonant dynamics (the basis of nanoparticle detection here) respond directly to the nanoparticle stray field, i.e. detection does not rely on nanoparticle-induced changes to the magnetic ground state of the disk. A consequence of this is that in the case of small disc-particle separations, sensitivities to the particle are highly mode-and particle-positiondependent, with frequency shifts being maximised when the intense stray field localised directly beneath the particle can act on a large proportion of the disc's spins that are undergoing high amplitude precession.

Large scale finite-element simulation of micromagnetic thermal noise

“…By exciting the stationary system with a stochastic thermal noise field h th , and performing a node-wise Fourier transform, it is possible to numerically calculate the resonance frequencies as well as the corresponding eigenvectors [19]. Results of the oscillation amplitudes as well as the corresponding resonance frequencies using the proposed method are visualized in Fig The original resonance frequencies calculated from stochastic time-integration [19] are in perfect agreement with the ones calculated by Albert using an eigenmode based approach [6,20]. A comparison of the different methods is presented in Fig.…”

Using Jupyter for Reproducible Scientific Workflows

“…For each figure in the publication, one notebook can be provided (find examples in Refs. [6], [7]). Using Binder, the community can inspect and re-run all the calculations in the cloud and make the publication reproducible.…”

From Micromagnetic to In Silico Modeling of Magnetic Nanodisks for Hyperthermia Applications

“…[ 16–20 ] Furthermore, attention has been focused on possible uses in cell separation from blood samples for early cancer detection, [ 21 ] and in frequency‐based nanoparticle sensing, exploiting changes in the ferromagnetic resonance behavior. [ 22 ]…”

“…[16][17][18][19][20] Furthermore, attention has been focused on possible uses in cell separation from blood samples for early cancer detection, [21] and in frequency-based nanoparticle sensing, exploiting changes in the ferromagnetic resonance behavior. [22] Another potential application is magnetic hyperthermia for cancer cure, where disk-, ring-, cylinder-, sphere-, cube-, or flower-shaped nanostructures made of different magnetic materials have been explored as heating agents for the generation of strongly localized increments of temperature. [23][24][25][26][27][28][29][30][31][32] Under the action of ac magnetic fields (f ≅ 50-500 kHz) and for sufficiently large size, they can produce heat via magnetic hysteresis, showing values of specific loss power (SLP) higher than those of the clinically approved SPIONs.…”