Combinatorial Synthesis and Automated Analytics for Material Exploration of Solid Electrolytes

Abstract

The development of solid electrolytes with high ionic conductivity is crucial for advancing all-solid-state batteries. However, conventional materials discovery approaches are hindered by experimental inefficiencies and analytical bottlenecks. Here, we present a high-throughput experimental platform integrating composition-gradient thin-film synthesis, automated structural and electrochemical characterization, and machine-learning pipelines for exploring pseudo-ternary systems. Composition-gradient thin films on 4-inch Si wafers were fabricated by co-sputtering of three targets. Synchrotron X-ray diffraction (SXRD) at SPring-8 BL28XU, equipped with automated sample exchange and XY-stage positioning, allows rapid structural mapping. Non-negative matrix factorization (NMF) first extracts latent phase information as basis patterns with corresponding phase fractions. These basis patterns are subsequently clustered using DBSCAN with dynamic time warping (DTW) distance metrics, which effectively groups solid solutions exhibiting continuous peak shifts into single clusters. Electrochemical impedance spectroscopy was performed using an automated XY-stage with a Z-axis contact probe system. EIS analysis employs Bayesian-navigated equivalent-circuit model (ECM) fitting to ensure consistent and automated extraction of bulk and grain-boundary conductivities. To validate the platform, we investigated the CeF 3 –LaF 3 –SrF 2 pseudo-ternary system for fluoride-ion conductors. SXRD analysis revealed distinct formation regions for tysonite and fluorite structures. The ionic conductivity mapping revealed that Ce-rich tysonite exhibited bulk conductivities exceeding 10 –4 S cm –1 , with values decreasing sharply in the two-phase region and reaching approximately 10 –8 S cm –1 for the fluorite phase. This integrated approach establishes a framework for accelerated discovery and optimization of solid electrolytes. Acknowledgements: This study was conducted using a grant from the project (JPNP21006) commissioned by the New Energy and Industrial Technology Development Organization (NEDO).