journal article·2014-03

The effects of aging time on the size, morphology, oriented attachment and magnetic behavior of hematite nanocrystals synthesized by forced hydrolysis of FeIII solutions

C. Luna, E.D. Barriga-Castro, R. Mendoza-Reséndez

Acta Materialia· Volume 66
Publisher page

Abstract

Abstract Three-dimensional (3-D) nanoarchitectures composed of self-organized hematite nanocrystals were successfully prepared by thermally induced hydrolysis of iron (III) solutions in the presence of urea and without additional stabilizers. The size, morphology and microstructure of these nanocrystal aggregates were investigated as a function of aging time using X-ray diffraction, transmission electron microscopy and selected area electron diffraction. The evolution of the microstructural parameters, including crystallite size, root mean square strain and lattice parameters, was analyzed by the Rietveld method using the MAUD software program and adopting the size–strain–shape Popa model. In addition, vibrating-sample magnetometry measurements were carried out to examine the magnetic behavior of the nanoarchitectures. These studies suggested that the formation mechanism of the observed nanoarchitectures consisted of several self-organization processes linked in hierarchical levels. The nanocrystals within these nanoarchitectures grew in size by Ostwald ripening and subsequent grain growth when they were aged at 98 °C in tightly capped tubes for an aging time that varied from 2 h up to 45 days. The crystal morphology evolved favoring a rhombohedral shape until intergrowth between the densely packed nanocrystals occurred. Consequently, the morphology of the nanoarchitectures, their effective magnetic anisotropy, the occurrence of the Morin transition and the exchange bias effect were also strongly dependent on the aging time.
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Research context

OpenAlex topics: Iron oxide chemistry and applications · Magnetic Properties and Synthesis of Ferrites · Minerals Flotation and Separation Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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