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Explainable AI in Electrocatalysis and Photocatalysis: From Catalyst Design to Mechanistic Insights
Jiarui Zhang1, Jianqiao Liu1,2, Di Wu1
1College of Information Science and Technology, Dalian Maritime University, Linghai Road 1, Ganjingzi District, Dalian 116026, Liaoning, P. R. China.
ACS Applied Materials & Interfaces
|June 26, 2026
Summary
Explainable artificial intelligence (XAI) enhances catalytic science by combining predictive accuracy with physical interpretability. This approach overcomes the limitations of traditional AI, enabling transparent catalyst design and deeper mechanistic understanding.
Area of Science:
- Catalytic science
- Materials informatics
- Artificial intelligence (AI)
Background:
- Conventional AI in catalysis lacks mechanistic interpretability due to its "black-box" nature.
- This limits the transfer of learned knowledge to new catalytic systems.
- Explainable AI (XAI) offers a solution by bridging predictive accuracy with physical interpretability.
Purpose of the Study:
- To provide a comprehensive review of XAI in catalytic science.
- To highlight how XAI enables transparent catalyst design and mechanistic insights.
- To trace the evolution of AI in catalysis towards interpretable models.
Main Methods:
- Review of traditional and deep-learning-based XAI approaches.
- Analysis of how electronic, geometric, and reactive descriptors are interpreted.
- Summary of XAI applications in various catalytic reactions.
Main Results:
- XAI elucidates structure-activity relationships in catalysis.
- XAI facilitates catalyst screening and provides mechanistic insights in electrocatalysis (e.g., hydrogen evolution, CO2 reduction).
- XAI frameworks are applied to photocatalysis for CO2 conversion and pollution remediation.
Conclusions:
- XAI transforms catalyst development from empirical modeling to a transparent, knowledge-driven paradigm.
- It establishes a clear link between catalyst design and mechanistic understanding.
- XAI alleviates the "black-box" limitations of conventional AI in catalysis.
Keywords:
catalytic informaticselectrocatalysisenvironmental applicationsexplainable artificial intelligencephotocatalysisMore Related Videos
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