Autonomous Solid-State Synthesis of NASICON -Type Na-Ion Conductor

Na superionic conductors (NASICONs) are known for their stability and high ionic conductivity, making them ideal for next-generation all-solid-state batteries. While the compositional design space of NASICON is enormous, synthesis exploration is challenging as impurities or other more energetically preferred phases can form, requiring careful design and recipe optimization. The rise of autonomous laboratories, such as the A-Lab, presents an opportunity to tackle complex problems more effectively through intelligent high-throughput synthesis facilities. In this talk, we present a cost-guided autonomous solid-state synthesis (CASS) system implemented in the A-Lab to accelerate the discovery of optimal, synthesizable, and high-purity NASICON phases consistent with the project-specific design rules. CASS optimizes the synthesis while also minimizing the cost imposed by the design rule by utilizing a genetic algorithm, automated solid-state synthesis and characterization in the A-Lab, automated XRD analysis, and a compositional stability model in a feedback loop. Its effectiveness is demonstrated through the discovery of a new fast-conducting phosphosilicate NASICON. We discuss the strategies employed in the CASS to overcome the inherent limitations of each tool. Our work establishes a workflow for autonomous, integrated NASICON design and synthesis optimization, and thus offers insights for generalizable objective-driven solid-solution exploration.