Thermal Noise Magnetometry of magnetic nanoparticles: simulations and experiments

TL;DR

This paper develops a theoretical model and optimized sample holder design for Thermal Noise Magnetometry, enhancing the sensitivity and accuracy of magnetic nanoparticle characterization without external excitation.

Contribution

It introduces a new theoretical framework and an optimized sample geometry that significantly improve TNM measurement sensitivity and validation through experiments.

Findings

Optimized sample holder increases noise power by 3.5 times.

Theoretical predictions match experimental measurements.

Sample volume is reduced by more than half.

Abstract

Magnetic nanoparticles have proven to be valuable for biomedical applications. A prerequisite for the efficiency of these applications are precisely characterized particles. Thermal Noise Magnetrometry (TNM), unlike any other magnetic characterization method, allows to characterize the particles without the application of an external excitation. We present a theoretical framework to model the experiment in order to examine the magnetic noise power properties of particle ensembles in TNM and optimize the geometry of the nanoparticle sample. An optimized sample geometry is calculated to maximize the noise power measured by the detector. The theoretical framework and the newly designed sample holder are validated by measuring a sensitivity profile in the setup. The optimized sample holder increases the noise power with a factor of 3.5 compared to the regular sample holder, while its volume is decreased by more than half. Moreover, the experimental profiles are consistent with the simulated counterparts, confirming the relevance of the theoretical framework. These results contribute to the further establishment of TNM as magnetic nanoparticle characterization method.