(Invited) Bridging Data Gaps in Li/Na Metal-Oxide Chemistry through Computational and Automated Synthesis Workflows
This work combines large-scale computational exploration with accelerated experimental synthesis to uncover underexplored regions of Li/Na-containing metal oxide chemistries relevant to electrochemical energy storage and develops solid-state and wet-chemical synthesis platforms supported by automation, robotics, and AI-guided decision-making.