Mixing
heterogeneous Li-ion conductive materials is one potential
way to enhance Li-ion conductivity more than that of the parent materials.
However, the huge number of possible compositions of parent materials
impedes the development of an optimal mixture by using conventional
methods. In this study, we employed machine learning to optimize the
composition ratio of ternary Li3PO4–Li3BO3–Li2SO4 for Li-ion
conductivity. We found the optimum composition of the ternary mixture
system to be 25:14:61 (Li3PO4:Li3BO3:Li2SO4 in mol %), whose Li-ion
conductivity is measured as 4.9 × 10–4 S/cm
at 300 °C. Our X-ray structure analysis suggested that Li-ion
conductivity of the mixed systems tends to be enhanced by the coexistence
of two or more phases. Although the mechanism enhancing Li-ion conductivity
is not simple, our results demonstrate the effectiveness of machine
learning for the development of materials.