RESUMO
Ceramics with nominal chemical composition CaCu3Ti4O12 (CCTO), CaCu3Ti3.96Al0.04O11.96F0.04 (CCTOAF), and Ca0.98Mg0.08Cu2.94Ti3.96Al0.04O11.96F0.04 (CCTOMAF) were prepared by the solid-state reactions technique. Using SEM, EDX, XPS, EPR, NMR, and complex impedance spectroscopy, the microstructure, elements distribution, chemical composition of grains and grain boundaries, and the dielectric response of ceramics were investigated. In the ССТÐ, CCTOAF, and CCTOMAF series, the average grain size increases, the degree of copper segregation at the grain boundaries is inversely related to grain size, and the dielectric loss decreases from 0.071 to 0.047 and 0.030, respectively, while dielectric permittivity ε' at 1 kHz is 5.6 × 104, 7.1 × 104, and 4.3 × 104, respectively. Additives of Al, Mg, F and milled particles (ZrO2, Al2O3, and SiO2) can either partially introduce into the perovskite structure or form low-melting eutectics at the grain boundaries, causing abnormal grain growth. The presence of copper ions in various oxidation states, as well as evidence of exchange spin interactions between them, was confirmed in all samples.
RESUMO
Using X-ray powder diffractions, Mössbauer spectroscopy, and magnetic measurements, the effect of complex dopants (Co2+ + Ti4+) and (Bi3+ + Ti4+) on the fine structure and magnetic properties of M-type barium hexaferrite prepared by hydroxide and carbonate precipitations has been studied. The distribution of cations over five nonequivalent positions of barium hexaferrite with magnetoplumbite structure is discussed. It has been shown that doped barium hexaferrite can be used for high-coercitivity data storage media.
RESUMO
Influence of the vacancy concentration on the Li conductivity of the (Li(1-x)Na(x))(0.2)La(0.6)TiO(3) and (Li(1-x)Na(x)(0.5)La(0.5)TiO(3) perovskite series, with 0 < or = x < 1, has been investigated by neutron diffraction (ND), impedance spectroscopy (IS), nuclear magnetic resonance (NMR), and Monte Carlo simulations. In both series, Li(+) ions occupy unit cell faces, but Na(+) ions are located at A sites of the perovskite. From this fact, the amount of vacant A sites that participate in Li conductivity is given by the expression n(v) = [Li] + square, where square is the nominal vacancy concentration. Substitution of Li by Na decreases the amount of vacancies, reducing drastically the Li conductivity when n(v) approaches the percolation threshold of the perovskite conduction network. In disordered (Li(1-x)Na(x))(0.5)La(0.5)TiO(3) perovskites, the percolation threshold is 0.31; however, in ordered (Li(1-x)Na(x))(0.2)La(0.6)TiO(3) perovskites, this parameter changes to 0.26. Near the percolation threshold, the amount of mobile Li species deduced by (7)Li NMR spectroscopy is lower than that derived from structural formulas but higher than deduced from dc conductivity measurements. Conductivity values have been explained by Monte Carlo simulations, which assume a random walk for Li ions in the conduction network of the perovskite. In these simulations, distribution of vacancies conforms to structural models deduced from ND experiments.
