Pushing the Frontier in Computational Catalysis with the Development of kinetic Monte Carlo Methods for Complex Surface Reactions

Solid catalysts are employed in more than 85% of industrial reactions, whose economic impact is estimated to 30-40% of global GDP.

Heterogeneous catalysts also play a central role in the production of high-value chemical compounds, such as fuels and additives, pharmaceuticals, and polymers (plastics).

Recently, these materials have attracted significant interest in the context of sustainability, CO2 utilisation, and green-chemistry, as they can facilitate transformations such as CO2 or biomass to useful chemicals at high efficiencies.

Thus, motivated, the project will develop advanced computational methodologies and an integrated kinetic Monte Carlo (KMC) framework for the simulation of complex reaction kinetics on solid surfaces, focusing in particular on photo(electro)catalysts which may undergo structural changes as the reaction progresses.

In this D.Phil. project, these methods will be extended aiming at (i) improving the robustness of the approximate acceleration algorithms by introducing mathematically rigorous ways to calculate error norms and improved strategies to down-scale kinetic constants, (ii) tackling the simulation of dynamic lattices, to take into account catalytic surface reconstruction explicitly in the modelling, (iii) introducing photo(electro)chemical events in the KMC framework making it possible to model chemistries relevant to sustainability, such as solar-powered CO2 conversion to valuable products.

The project includes mainly mathematical computational method development activities, and will deliver a general-purpose framework for the accurate simulation of photo(electro)chemical processes.

The host lab has previously developed computationally efficient approaches, algorithms and code, based on the KMC method, enabling the high-fidelity modelling of catalytic reactions in which several parallel and competing reaction pathways exist, and the participating surface species may exhibit alternative binding configurations and may be subject to lateral interactions that influence the reaction rates.

Additionally, the group has developed parallelisation approaches for simulating very large domains and approximate algorithms for tackling performance limitations due reaction timescale disparity.

In the context of this project, these existing approaches will be integrated and further advanced, to deliver the envisaged framework.

Additionally, methods and computational components related to the simulation of dynamic lattices and photo-excited events involving electronically excited states, will be a novel area of research and development that brings significant value to the project.

This project falls within the EPSRC "energy and decarbonisation", "physical sciences" and "research infrastructure" research areas.

Moreover, the planned activities align well with EPSRC's priorities in advanced materials, circular economy, and net zero. New industrial materials are often developed via trial and error rather than rational mechanistic considerations.

Yet, the economic benefits of materials modelling are already tangible with reported reductions in development time "from 10 to 1.5-years, saving millions of euros because of the understanding of the material and saving of experiments".

In this context, the envisioned simulation framework will facilitate the discovery of catalytic materials with far-reaching impact in fields ranging from CO2 recycling to sustainable chemicals manufacturing.