Tetragonal Li₇SiPS₈ is a superionic solid electrolyte, yet its Li ion conductivity suffers from the presence of an amorphous sidephase. Attempts to optimize the ionic conductivity, however, are incremental and hence time-consuming, because the relationshipbetween 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 Li₇SiPS₈ system. Our data-drivenworkflow reproducibly yields Li₇SiPS₈ with ionic conductivities exceeding 7 mS cm^−1 at room temperature, an increase byup to 350% compared to previously reported routes. Simultaneously, the optimized solid-state synthesis lowered the synthesistemperature by 100 K (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 quantitativeRietveld 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 synthesisparameter space, thereby accelerating the development of high-performance sulfide electrolytes for next-generation batteries
Balzat et al. (Thu,) studied this question.