Abstract
The structural and magnetic properties of magnetic multi-core particles were determined by numerical inversion of small angle scattering and isothermal magnetisation data. The investigated particles consist of iron oxide nanoparticle cores (9 nm) embedded in poly(styrene) spheres (160 nm). A thorough physical characterisation of the particles included transmission electron microscopy, X-ray diffraction and asymmetrical flow field-flow fractionation. Their structure was ultimately disclosed by an indirect Fourier transform of static light scattering, small angle X-ray scattering and small angle neutron scattering data of the colloidal dispersion. The extracted pair distance distribution functions clearly indicated that the cores were mostly accumulated in the outer surface layers of the poly(styrene) spheres. To investigate the magnetic properties, the isothermal magnetisation curves of the multi-core particles (immobilised and dispersed in water) were analysed. The study stands out by applying the same numerical approach to extract the apparent moment distributions of the particles as for the indirect Fourier transform. It could be shown that the main peak of the apparent moment distributions correlated to the expected intrinsic moment distribution of the cores. Additional peaks were observed which signaled deviations of the isothermal magnetisation behavior from the non-interacting case, indicating weak dipolar interactions.
Highlights
Magnetisation behaviour M(H)[22,23,24]
The multi-core particles consisted of large poly(styrene) spheres with embedded superparamagnetic iron oxide nanoparticle cores
Analysis of the pair distance distribution function (PDDF) strongly indicated that the cores were mostly accumulated in the surface layers of the poly(styrene) spheres
Summary
Magnetisation behaviour M(H)[22,23,24]. Whilst this model offers an adequate description for single-core nanoparticle systems under consideration of polydispersity, recent work has suggested that so called multi-core particles[25,26,27] may be more suited to magnetic hyperthermia. The magnetisation curves of a magnetic nanoparticle ensemble were numerically inversed in order to extract the apparent moment distribution, using the classical Langevin function as model function. The working hypothesis was that in case of dipolar interactions the extracted apparent moment distribution exhibits characteristic distortions compared to the intrinsic moment distribution of the nanoparticle ensemble. The working hypothesis was that for example in case of dipolar interactions, the apparent moment distributions exhibit characteristic distortions This is an alternative approach compared to established model fits[28,29,30,32] where the influence of dipolar interactions is a priori included in the model functions
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