Mechanochemistry-Driven Optimization of Halide-Based Solid-State Electrolytes via Orthogonal Design of Experiments and Regression Modeling

The mechanochemical synthesis of halide-based solid-state electrolytes (SSEs) requires the fine-tuning of key parameters to optimize ionic conductivity, yet rigorous statistical analysis of the parametric effects remains lacking. In this work, we applied an orthogonal design of experiments on Li 2 ZrCl 6 (LZC) – a cost-effective halide-based SSE – to evaluate the impact of six parameters. The results reveal that ionic conductivity is most influenced by the ball-to-precursor mass ratio, the ball-mill step time, and the milling speed. Structural characterizations indicate a resistive intermediate spinel-LZC phase that inhibits performance. A multivariate linear regression model was employed to quantify the impacts of the parameters. Finally, a Gaussian process regression model predicted an optimized ionic conductivity and its corresponding set of synthesis conditions. The findings reported here establish a hierarchy of the importance of parameters for experimental optimization of current and future SSEs to enable consistent, high-quality production for next-generation all-solid-state Li-ion batteries.