In this episode of The Chemistry Show, we move from experimental structural methods to the rapidly expanding world of computational modeling and data-driven materials design. The focus shifts from observing structure to predicting and engineering it.

We explore how techniques such as Density Functional Theory (DFT) and molecular dynamics (MD) simulations provide atomic-scale insight into catalytic mechanisms, surface energetics, and reaction pathways.

Ultimately, this episode demonstrates how modern materials science combines high-level computation with experimental validation to accelerate innovation in renewable energy technologies.

Powered by AI (Google NotebookLM), this episode is based on lecture material from the Structural Methods in Inorganic Chemistry course taught by Prof. Pedro Camargo at the University of Helsinki, and reflects how the field has evolved from structure determination to predictive catalyst design.