What are the Future Directions in Model Validation?
Future directions in model validation for catalysis include:
Integration with Machine Learning: Combining traditional modeling approaches with machine learning techniques to improve model accuracy and predictive capabilities. Enhanced Data Sharing: Developing platforms for sharing experimental and computational data to facilitate model validation and benchmarking. Advanced Computational Methods: Leveraging advancements in computational power and algorithms to develop more accurate and scalable models. Holistic Approaches: Integrating environmental, economic, and social factors into model validation to support sustainable catalyst development.
