Mauro Bracconi’s research is centered on the analysis and modeling of catalytic processes across different scales. His work aims to describe how chemical reactions and reactor conditions interact, enabling more accurate prediction and optimization of complex reaction systems.

Within CORC, he is involved in the project “Physically-informed digital twins for carbon capture and sequestration into advanced materials via methane pyrolysis” working together with Matteo Maestri.

The project focuses on developing modeling frameworks that combine first-principles approaches with data-driven methods to create physically-informed digital twins. These models are designed to retain the accuracy of detailed simulations while enabling faster and more efficient predictions of system behavior.

In this context, Bracconi contributes to the development of multiscale models and their integration into predictive tools that can be used for reactor design and process optimization. This includes describing catalytic reaction mechanisms and translating them into models that can be applied under realistic operating conditions.