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Structural and magnetic properties of multi-core nanoparticles analysed using a generalised numerical inversion method
University of Cantabria, Santander, Spain .
University College London, London, United Kingdom .
Physikalisch-Technische Bundesanstalt, Berlin, Germany .
Bundesanstalt für Materialforschung Und-prüfung (BAM), Berlin, Germany ; AGH University of Science and Technology, Krakow, Poland .
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2017 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, 45990Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2017. Vol. 7, 45990
National Category
Natural Sciences
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URN: urn:nbn:se:ri:diva-29602DOI: 10.1038/srep45990Scopus ID: 2-s2.0-85017457020OAI: oai:DiVA.org:ri-29602DiVA: diva2:1095983
Available from: 2017-05-16 Created: 2017-05-16 Last updated: 2017-05-16Bibliographically approved

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