Optimize Before You Synthesize—Enhancing the Ionic Conductivity of Li ₇ SiPS ₈ Using Bayesian Optimization

Abstract

ABSTRACT Tetragonal 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 system. Our data‐driven workflow reproducibly yields with ionic conductivities exceeding 7 mS  at room temperature, an increase by up to compared to previously reported routes. Simultaneously, the optimized solid‐state synthesis lowered the synthesis temperature by 100 K () and shortened the reaction time by 76 h (), 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.