New AI Tool Predicts Lithium Metal Anode Failures from Just Two Early Cycles

Lithium metal batteries (LMBs) are a promising technology for next-generation energy storage, offering higher energy density than traditional lithium-ion batteries. However, challenges related to the anode’s behavior — specifically issues related to its kinetics and reversibility — have hindered their widespread adoption. Researchers have long struggled with understanding the underlying causes of battery failure, often relying on post-mortem analysis that only reveals outcomes but fails to capture the dynamic processes leading to failure.