Temperature dependence of ferromagnetic behavior in ceria nanoparticles with cubic morphology
Source abstract
Abstract
Cerium IV oxide (CeO 2 ) is a semiconductor material composed of a rare-earth metal that has been extensively studied due to present ferromagnetic behavior at room temperature and the possibility of being used in the production of information systems devices. The origin of this ferromagnetism is still far from clear up to now and there are scarce works about their temperature dependence. In this work, we report a systematic study of the temperature dependence of the magnetic properties of ceria nanoparticles with cubic morphology using magnetization measurements and electron paramagnetic resonance (EPR) spectroscopy. The material was characterized by X-Ray Diffraction (XRD), Transmission Electron Microscopy (TEM) and X-Ray excited Photoelectron Spectroscopy (XPS) techniques. A bimodal size distribution of CeO 2 (100) NPs with an average size of 28.5 nm and 11 nm was obtained. XPS data for Ce 3d indicated that the relative surface amounts of Ce 4+ and Ce 3+ species were 74.10 % and 25.90 %, while for O 1 s the relative surface proportion found was 71.48 % for species oxygenated located in the crystalline lattice of the nanomaterial and 28.51 % of adsorbed hydroxyl oxygen (Ce – OH). The zero-field-cooled/field-cooled (ZFC/FC) curves of χ(T) and the M(H) curves as a function at different temperatures indicated ferromagnetic and paramagnetic behavior. The temperature dependence of the broad line in EPR spectra showed a magnetic transition at approximately 50 K, which can be attributed to the condensation of surface oxygen and the extinction of oxygen vacancies. This result reinforces the relationship between oxygen vacancies and ferromagnetic behavior in CeO 2 nanoparticles.
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Research context
OpenAlex topics: Catalytic Processes in Materials Science · ZnO doping and properties · Magnetic and transport properties of perovskites and related materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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