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Tuning the structure and habit of iron oxide mesocrystalsElectronic supplementary information (ESI) available: Morphological characterization of the nanocubes, further GISAXS analysis and indexed patterns, AFM images, additional SEM images, mesocrystal surface reconstruction using SEM images, and magnetic characterization. See DOI: 10.1039/c6nr03776c
Erscheinungsjahr
2016-08
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
A precise control over the meso- and microstructure of ordered and aligned nanoparticle assemblies,
i.e.
, mesocrystals, is essential in the quest for exploiting the collective material properties for potential applications. In this work, we produced evaporation-induced self-assembled mesocrystals with different mesostructures and crystal habits based on iron oxide nanocubes by varying the nanocube size and shape and by applying magnetic fields. A full 3D characterization of the mesocrystals was performed using image analysis, high-resolution scanning electron microscopy and Grazing Incidence Small Angle X-ray Scattering (GISAXS). This enabled the structural determination of
e.g.
multi-domain mesocrystals with complex crystal habits and the quantification of interparticle distances with sub-nm precision. Mesocrystals of small nanocubes (
l
= 8.6-12.6 nm) are isostructural with a body centred tetragonal (
bct
) lattice whereas assemblies of the largest nanocubes in this study (
l
= 13.6 nm) additionally form a simple cubic (
sc
) lattice. The mesocrystal habit can be tuned from a square, hexagonal to star-like and pillar shapes depending on the particle size and shape and the strength of the applied magnetic field. Finally, we outline a qualitative phase diagram of the evaporation-induced self-assembled superparamagnetic iron oxide nanocube mesocrystals based on nanocube edge length and magnetic field strength.
A precise control over the meso- and microstructure of ordered and aligned nanoparticle assemblies,
i.e.
, mesocrystals, is essential in the quest for exploiting the collective material properties for potential applications.
Sprache
–
Identifikatoren
ISSN: 2040-3364
eISSN: 2040-3372
DOI: 10.1039/c6nr03776c
Titel-ID: cdi_rsc_primary_c6nr03776c
Format
–
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