Optimize before you Synthesize - Enhancing the Ionic Conductivity of Li7SiPS8 using Bayesian Optimization

Tetragonal Li 7 SiPS 8 is a superionic solid electrolyte, yet its Li ion conductivity suffers from the presence of an amorphous side phase. Attempts to optimize the ionic conductivity, however, are incremental and hence time-consuming, because the relationship between synthesis conditions and electrolyte performance is largely unknown. In this work, we employ Bayesian Optimization (BO) as an efficient design-of-experiment approach to increase the ionic conductivity of the Li 7 SiPS 8 system. Our data-driven workflow reproducibly yields Li 7 SiPS 8 with ionic conductivities exceeding 7mScm −1 at room temperature, an increase by up to 350 % compared to previously reported routes. Simultaneously, the optimized solid-state synthesis lowered the synthesis temperature by 100K (20 %) and shortened the reaction time by 76 h (76 %), delivering a more energy-efficient and, hence, sustainable process. To probe the origin of the increased conductivity, we examined six representative samples by quantitative Rietveld refinements, synchrotron X-ray powder diffraction, pair distribution function analysis, solid-state and pulsed-field-gradient NMR, electron microscopy, and Raman spectroscopy. We demonstrate that BO can help navigate the complex synthesis parameter space, thereby accelerating the development of high-performance sulfide electrolytes for next-generation batteries.