Harnessing explainable AI to adaptively design catalysts for lithium-sulfur batteries.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 40486974.
- Also identified by DOI 10.1016/j.patter.2025.101256 and PMC identifier 12142603.
- Licence recorded as CC BY-NC.
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Abstract
The exploration of efficient catalysts for sluggish sulfur redox reactions is pivotal for advancing lithium-sulfur batteries but remains inefficient through trial-and-error approaches. In a recent <i>Joule</i> study, Zhou, Li, and colleagues proposed an explainable-AI-based approach to intelligently design catalysts adaptive to diverse local chemical environments in batteries, achieving exceptional catalytic and battery performance.