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 Li2ZrCl6 (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.