Abstract
In this study, regarding to the wide applications of spinel ferrites in various fields such as Li ion-batteries, photocatalysts, and optoelectronics, the structural and morphological properties of tin ferrite oxide (SnFe2O4) nanoparticles are investigated using X-ray diffraction (XRD) analysis and field emission scanning electron microscopy (FESEM). The sol–gel, solvothermal, and co-precipitation methods were used to synthesize the SnFe2O4 nanoparticles, and the effect of annealing temperatures at T = 350 °C, 450 °C, and 550 °C was investigated. The XRD results confirmed the formation of tin ferrite spinel phase at an annealing temperature of 350 °C with a preferred peak (311). Crystallite size (D) and strain (ε) of SnFe2O4 nanoparticles was determined in region 20–45 nm and 2–4 × 10–4, respectively, using the Scherer, Williamson–Hall, and Rietveld computational methods. The results showed that the crystallite size in the samples increased with increasing annealing temperature. This increase is attributed to the reduction of defects, imperfections and lattice strain, which leading to an increase in the lattice constants and unit cell volume in the nanocrystalline structure. The Rietveld method determine smaller crystal sizes compared to the Williamson–Hall and Scherer methods because it can correct for peak broadening by taking into account all instrumental factors. The FESEM images of the synthesized nanostructures of SnFe2O4 showed cubic and polyhedral grains with cluster growth and an average grain size of 50–80 nm. According to the crystal structure of tin ferrite spinel, the cubic morphology confirmed the formation of this structure. The average crystallite size and grains in the synthesized samples was determined using X-ray diffraction (XRD) and field emission scanning electron microscopy (FESEM) analysis, respectively. The formation conditions of the SnFe2O4 spinel phase and other phases in the synthesis process at different temperatures and dependence of structural parameters was studied by various structural models for the samples.
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