July 22, 2025

Explainable artificial intelligence for materials discovery: application to catalysts for the HER and ORR

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This approach finds optimal catalysts for hydrogen production using explainable AI, highlighting insights into material properties.

MAIN FINDING: Incorporating explainable artificial intelligence improves the design of catalysts for hydrogen production.
KEY EVIDENCE: The study utilized counterfactual explanations to reveal relationships between material features and performance.
APPROACH: Density functional theory calculations validated the discovered materials against design targets.
SIGNIFICANCE: This method offers a new pathway for material design, emphasizing explainability while maintaining high accuracy.

Vassilev-Galindo et al. (2025) studied this question.

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