What Challenges Exist in Implementing AI-Driven Tools in Catalysis?
Despite their potential, implementing AI-driven tools in catalysis faces several challenges: - Data Quality: The accuracy of AI models depends on the quality and comprehensiveness of the data they are trained on. - Complexity of Catalytic Systems: Catalytic reactions are often complex, involving numerous variables that can be difficult to model accurately. - Integration: Integrating AI tools into existing research workflows can be challenging and may require significant changes in how data is collected and analyzed. - Interpretability: Understanding how AI models arrive at their predictions can be difficult, which may hinder their acceptance among researchers.
