Structural Study of Nano-Sized Gahnite (ZnAl2O4): From the Average to the Local Scale.
Giorgia ConfalonieriNicola RotirotiAndrea BernasconiMonica DapiaggiPublished in: Nanomaterials (Basel, Switzerland) (2020)
Spinel gahnite (ZnAl2O4) has been obtained through a hydrothermal synthesis method with a grain size of about 2 nm. The sample was calcined for a few hours at two different temperatures (800 and 900 °C) in order to obtain larger grain sizes to be analyzed by means of powder diffraction with the Rietveld method, and by means of total scattering with the Pair Distribution Function (PDF) method. The idea is to compare the average to the local structure, as a function of increasing grain size. The total scattering data were collected at the European Synchrotron Radiation Facility (ESRF), Grenoble. The samples have been also characterised by means of high resolution Transmission Electron Microscopy (TEM), showing an increasing grain size up to about 9 nm. The average structure presented variations in the inversion degree and an increase in grain size. TEM observations demonstrated that the small crystals are well crystallised: the high resolution images neatly showed the atomic planes, even in the smallest particles. However, the average structure did not properly fit the PDF data in the local region, owing to a slightly different coordination among the octahedra. A new structural model is proposed for the local region of the PDF, that helped our understanding of the differences between a real nanostructured sample and that of a microcrystalline one. The oxygen disorder, due to the inversion grade of the spinel, is demonstrates to be at the basis of the local deviation. No signals of interstitial Zn atoms were detected.
Keyphrases
- high resolution
- electron microscopy
- electronic health record
- photodynamic therapy
- mass spectrometry
- big data
- deep learning
- computed tomography
- convolutional neural network
- magnetic resonance imaging
- heavy metals
- radiation therapy
- high speed
- machine learning
- artificial intelligence
- long term care
- anaerobic digestion
- ionic liquid
- sewage sludge
- liquid chromatography
- crystal structure