Beyond trial and error: A framework for AI-driven solid-electrolyte discovery

Researchers proposed a closed-loop framework linking materials databases, simulations, automated experiments, and literature extraction to find solid electrolytes. The system evaluates chemical stability, mechanical strength, and manufacturing requirements alongside ion speed. This approach shifts research away from isolated trial and error toward an interconnected testing pipeline.

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