Catalysis and Chemical Engineering Global Conference

Modeling and simulation are key enablers in advancing the field of catalysis, providing powerful tools that allow scientists to visualize, analyze, and predict catalytic behavior. Through computational methods, it becomes possible to simulate chemical reactions atomistically, allowing for optimization of catalyst design for efficiency and improved reaction pathways. This session emphasizes the innovative role of modeling and simulation for the catalysis community, advancing chemistry for sustainable development and industrial applications.

Modeling Catalysts and Their Structures: At the molecular level, catalysts interact with reactants in specific structural modes. One of the most valuable resources for understanding these catalyst-reactant interactions, and how they affect reactions, is modeling. Scientists can simulate complex processes in a virtual environment, requiring only a few configurations to be tested in the lab. For example, using quantum mechanics and molecular dynamics simulations, scientists can predict catalyst performance under specific conditions. This targeted approach allows for more focused improvements in catalyst designs and functionalities.

Simulations of catalytic processes are particularly relevant to sustainable energy solutions. Modeling aids scientists in discovering new materials for hydrogen production, fuel cells, and carbon capture, enabling them to increase efficiency and reduce environmental impact. Designing catalysts to maximize energy conversion and storage, with insights into the basic mechanisms behind catalytic reactions, paves the way toward cleaner, more sustainable energy technologies.

Machine learning and artificial intelligence are increasingly being integrated into the modeling and simulation of catalysis. These technologies analyze large data volumes, identify patterns, and even predict catalyst behavior, accelerating discoveries in catalysis. Combining AI tools with traditional modeling methods speeds up the identification of optimal catalyst structures, reducing time and costs in developing new catalytic materials.