Toshiya Saito

Synthesis, structure, and conduction mechanism of the lithium superionic conductor Li10+δGe1+δP2−δS12

A solid solution of the lithium superionic conductor Li10+δGe1+δP2−δS12 (0 ≤ δ ≤ 0.35) was synthesized and its structure and ionic conductivity were examined. The highest ionic conductivity value of 1.42 × 10−2 S cm−1 was obtained at 300 K with a sintered pellet of the sample having the highest solid solution lithium content of δ = 0.35. The Arrhenius conductivity curves obtained for this material exhibited a gradual change in slope over the temperature range of 193–373 K and the activation energy for ionic conduction decreased from 26 kJ mol−1 below 373 K to 7 kJ mol−1 above 573 K, which is typical of highly ionic conducting solids. The crystal structures of the solid solutions were determined using neutron diffraction, and conduction pathways were visualized through analysis by applying the maximum entropy method. The lithium distribution was found to disperse significantly throughout a one-dimensional conduction pathway as the temperature was increased from 4.8 K to 750 K. In addition, two-dimensional distribution of lithium along the ab plane became apparent at high temperatures, suggesting that the conduction mechanism changes from one-dimensional to three-dimensional with increasing temperature.

Ideal design of textured LiCoO2 sintered electrode for Li-ion secondary battery

To improve the energy density and practical realization of the all-solid-state Li-ion secondary battery, the principal requirement is a high electric conductivity in the densely sintered positive electrode. To accomplish this task, we focused on the anisotropic Li-ion and electron conductivities of the LiCoO2. As a result of our work, the ideal design of the texturing, perpendicular alignment of the c-plane and horizontal but random orientation of the c-axis on the electrode, was proposed. The battery performance of the ideal textured cell fabricated using a rotating strong magnetic field has a significantly higher performance than a randomly oriented cell.

Bayesian-Driven First-Principles Calculations for Accelerating Exploration of Fast Ion Conductors for Rechargeable Battery Application

Safe and robust batteries are urgently requested today for power sources of electric vehicles. Thus, a growing interest has been noted for fabricating those with solid electrolytes. Materials search by density functional theory (DFT) methods offers great promise for finding new solid electrolytes but the evaluation is known to be computationally expensive, particularly on ion migration property. In this work, we proposed a Bayesian-optimization-driven DFT-based approach to efficiently screen for compounds with low ion migration energies (

Dielectric Modification of 5V‐Class Cathodes for High‐Voltage All‐Solid‐State Lithium Batteries

{{\boldsymbol{E}}}_{{\boldsymbol{b}}}{\boldsymbol{)}}

Arrangement of La and vacancies in La2/3TiO3 predicted by first-principles density functional calculation with cluster expansion and Monte Carlo simulation

Eb). We demonstrated this on 318 tavorite-type Li- and Na-containing compounds. We found that the scheme only requires ~30% of the total DFT-

Anisotropy in activation energy of textured LiCoO2 for the initial stage of sintering

{{\boldsymbol{E}}}_{{\boldsymbol{b}}}