Modeling Magnetic Correlations in magnetite Nanoparticle Assemblies Using X-ray Magnetic Scattering Data

Magnetic nanoparticles are increasingly used in nanotechnologies and biomedical applications, such as drug targeting, MRI, and bio-separation. Magnetite (Fe3O4) nanoparticles stand to be effective in these roles due to the non-toxic nature of magnetite and its ease of manufacture. To be more effective in these applications, a greater understanding of the magnetic behavior of the individual magnetite nanoparticles is needed when a collection of them is used. This research seeks to discover the local magnetic ordering of ensembles of magnetite nanoparticles occurring at various stages of the magnetization process. To complete this study, we use resonant x-ray magnetic scattering, which provides information about the magnetic orders in the material. Here we discuss the modeling of the magnetic scattering data using a one-dimensional chain of nanoparticles with a mix of ferromagnetic, anti-ferromagnetic, and random order and the model's validation against empirical gaussian fits. The model utilizes twelve variable parameters and we used a Levenberg-Marquardt algorithm to find the best fit parameters. By fitting the model to the experimental data, we extracted information about the magnetic correlations in the nanoparticle assembly.