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Mixing heterogeneous Li-ion conductive materials is one of potential ways toenhance the Li-ion conductivity more than that of the parent materials.However, the development of the mixtures had not exhibited significant progressbecause it is a formidable task to cover the vast possible composition of theparent materials using traditional ways. Here, we introduce a fashion based onmachine learning to optimize the composition ratio of ternaryLi3PO4-Li3BO3-Li2SO4 mixture for its Li-ion conductivity. According to ourresults, the optimum composition of the ternary mixture system is 25:14:61(Li3PO4: Li3BO3: Li2SO4 in mol%), whose Li-ion conductivity is measured as 4.9x 10E-4 S/cm at 300 {\deg}C. Our X-ray structure analysis indicates that Li-ionconductivity in the mixing systems is enhanced by virtue of the coexistence oftwo or more phases. Although the mechanism enhancing Li-ion conductivity is notsimple, our results demonstrate the effectiveness of machine learning for thedevelopment of materials.

Optimization of heterogeneous ternary Li3PO4-Li3BO3-Li2SO4 mixture for Li-ion conductivity by machine learning