What Challenges Exist in Integrating AI with Catalysis?
While promising, the integration of AI with catalysis faces several challenges:
Data Quality: High-quality and extensive datasets are required for effective AI training, which are often difficult to obtain. Model Interpretability: AI models, particularly deep learning, can act as "black boxes" making it difficult to interpret how decisions are made. Computational Resources: AI-driven simulations and optimizations demand significant computational power. Cross-Disciplinary Expertise: Requires expertise in both catalysis and AI, which can be challenging to find.
