Influence of Cation Vacancies on Li Conductivity of La1/2Li1/2-2xSrxTiO3 Perovskites (0 < x ≤ 0.25): The Role of Nominal and Effective Vacancies

The Li1/2-2xSrxLa1/2TiO3 series (0 <= x <= 0.25) is investigated with X-ray diffraction, nuclear magnetic resonance, and impedance spectroscopy techniques. The substitution of two Li+ by one Sr2+ in Li1/2La1/2TiO3 perovskite generates cation vacancies that, when ordered in alternating planes along the c-axis, confer a two-dimensional character to Li mobility. In previous works, it was shown that Li+ ions partially occupy the center of the six faces of the cubic perovskite, resulting in the associated A-sites to participate like a vacancy in the definition of the percolation vacancy threshold. The results obtained in the Li(1/2-2x)SrxLa(1/2)TiO(3) series are compared with those obtained in the Li3xLa2/3-xTiO3 series, and other Sr-doped solid solutions (Li1/2-xSr2xLa1/2-xTiO3 and LixSrxLa2/3-xTiO3), to highlight the importance of the effective vacancies with respect to the nominal ones in conductivity. The analysis of four series, belonging to the ternary SrTiO3-La2/3TiO3-Li2TiO3 phase diagram, permits a better understanding of the ionic conduction mechanism in perovskites. The results show that the vacancy percolation model is more adequate to explain Li conductivity than the conventional hopping probability model. In the analyzed series, Li conductivity is maximum when a small amount of Sr is incorporated into the pseudo-cubic La1/2Li1/2TiO3 end member, while it decreases as the amount of strontium increases.

Automated summary

The Li1/2-2xSrxLa1/2TiO3 series was studied using X-ray diffraction, nuclear magnetic resonance and impedance spectroscopy techniques. The substitution of Sr2+ for two Li+ in Li1/2La1/2TiO3 generates cation vacancies that give a two-dimensional character to Li mobility. The results show that effective vacancies play a significant role in conductivity, and the vacancy percolation model is more suitable for explaining Li conductivity than the conventional hopping probability model.