What Are the Challenges in Applying Data Analytics to Catalysis?
Despite its potential, applying data analytics in catalysis comes with challenges:
Data quality and consistency: Ensuring that data from different sources is accurate, complete, and comparable. Data integration: Combining datasets from various experiments and simulations can be complex. Interpretability: Making the results of data analytics understandable and actionable for experimental chemists. Computational resources: High-performance computing infrastructure is often required to process and analyze large datasets.
Addressing these challenges is essential for the successful implementation of data analytics in catalysis.
