Electrolytes for Lithium-Ion Batteries
Using machine learning as a high-throughput screening tool, this project accelerates the discovery-to-validation cycle for solid-state electrolytes (SSEs) by identifying structurally suitable candidates from existing materials databases, then progressing the most promising through experimental synthesis and electrochemical validation. By bridging database mining, ML-assisted screening, and lab validation, the project reduces technical risk and development time — positioning Australia to rapidly advance toward pilot-scale SSE development and domestic battery manufacturing.
