What are the Challenges in Applying AI to Catalysis?
Despite its potential, the application of AI in catalysis faces several challenges: 1. Data Quality and Availability: High-quality, well-curated datasets are essential for training accurate AI models. However, such datasets are often scarce in catalysis research. 2. Interpretability: AI models, particularly deep learning algorithms, can sometimes act as “black boxes,” making it difficult to understand the rationale behind their predictions. 3. Integration with Experimental Work: Bridging the gap between computational predictions and experimental validation remains a significant challenge. Effective integration requires close collaboration between computational scientists and experimentalists.
