CBET-EPSRC: Bespoke Porous Catalyst Design via Integrated Stochastic Modelling of Reaction and Transport in Synergy with Experiments

About This Grant

Heterogeneous catalysts accelerate chemical reactions in more than 70% of all chemical manufacturing processes. In these materials, the active sites (single atoms or nanoparticles) lie within the porous network of a solid support, which may be crystalline, e.g. a zeolite, or amorphous, e.g. an activated carbon. For these materials to function properly, gas or liquid reactants must transfer through the pore openings, diffuse along the porous networks, and adsorb on the active sites where reactions occur. The products of the reaction must diffuse in the other direction from the active sites, through the pores, and to the outside of the material. Optimal performance requires a balance between reactants and products transport, which depends on the molecular properties of the fluids and the structural properties of the catalyst. This project will develop a fully integrated–multiscale kinetic modelling framework for industrial applications that accounts for the relevant reactive and transport phenomena. This project brings together investigators from the University of Oklahoma, the University of Oxford, and the University of Manchester, who will achieve the following aims: 1) Bridge the knowledge gap between local pore-scale phenomena (electronic/molecular) and global/bulk phenomena (performance) in porous catalysts. The kinetic Monte Carlo (kMC) method will be the backbone of the envisioned integrated framework, which will link reactive kMC and diffusive kMC approaches. The outcome of this aim will be a stochastic, multiscale modelling framework for high-fidelity simulations that will rationalize trends and inform materials design. 2) Obtain fundamental insight into the relation between porous catalyst structure and performance for important future industrial processes. The use-case will be represented by biomass-related transformations, and specifically the conversion of fructose to hydroxymethylfurfural (HMF), in which selectivity challenges are prominent, with humins obtained as the undesired by-products. The kMC framework of aim 1 will be parameterized with density functional theory (DFT) (reactive component) and molecular dynamics (MD) (transport component), towards predictive simulations. The outcome of this aim will be guidance for the development of superior catalysts. 3) Experimentally validate the framework and the predictions of the models of aims 1 and 2 via a variety of approaches encompassing catalyst synthesis, physicochemical properties modification, characterization, diffusion measurements and kinetic studies. The outcome of this aim will be the step-by-step improvement of the computational/theoretical methods developed throughout this project. The successful completion of the project will deliver much anticipated know-how for the design of advanced materials and chemical processes with unprecedented accuracy and spatial resolution. In the long run, the fundamental insights obtained via MD and DFT calculations, once validated against nuclear magnetic resonance (NMR) experiments, will help identify the rate-limiting steps affecting the performance of several chemical processes of industrial and societal relevance. This collaborative U.S.- U.K. project is supported by the U.S. National Science Foundation (NSF) and the Engineering and Physical Sciences Research Council (EPSRC) of United Kingdom Research and Innovation (UKRI), where NSF funds the U.S. investigator and EPSRC funds the partners in the U.K. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.