More than 70% of chemical manufacturing relies on porous solid catalysts, but engineers lack a way to predict how their microscopic pore structures affect overall performance. This project builds a computer model that simulates every step—from molecules diffusing through nanoscale pores to chemical reactions at active sites—so that catalyst design no longer depends on trial and error. Current models treat the catalyst as a uniform blob, ignoring the complex interplay between transport and reaction inside its pores. The team will link two simulation methods: one that tracks individual molecules moving through the pore network, and another that models reactions at catalytic sites. They will test the framework against experiments for a specific case—converting fructose into hydroxymethylfurfural, a bio-based chemical, while suppressing unwanted byproducts. If successful, the model will let industry design catalysts with tailored pore structures for specific reactions, reducing waste and energy use. The work is fundamental science, but it directly targets a practical bottleneck in sustainable chemical manufacturing—turning plant biomass into useful products rather than burning it.
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Heterogeneous catalysts encompass porous solid materials that accelerate chemical reactions and are employed 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 support, which may be crystalline, e.g. a zeolite, or amorphous, e.g. an activated carbon. Thus, engagement with the catalytic functionality of such porous catalysts involves the transport of gas/liquid reactants around solid pellets (global transfer), transfer through the pore openings and diffusion along the porous networks (local transfer), adsorption and catalytic conversion on active sites, and finally desorption and transport back to the bulk. Due to the multiscale nature and the complex interplay of these phenomena, a fundamental understanding of structure-performance relationships remains elusive. From an industrial context, what is lacking but essential is an accurate and fully integrated-multiscale kinetic modelling framework that would account for the relevant reactive and transport phenomena within the spatial resolution of the catalyst's porous network structure. Such a framework will guide the development of superior porous catalysts for given applications, and the identification of optimal conditions for reducing the environmental impact of industrial operations. The proposed international collaborative project will address this challenge, underpinned by experimental investigation and close collaboration with industry (Johnson Matthey). The pertinent aims, methods and outcomes are: 1) To bridge the 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 [MS and co-workers, Zacros graph-theoretical kMC framework; J. Chem. Phys., 139: 224706 (2013); Comp. Phys. Comm., 270: 108148 (2022)] and diffusive kMC approaches [MS, AS and co-workers, J. Chem. Theory Comput., 15: 6907-6922 (2019)]. The outcome of this aim will be a stochastic, multiscale modelling framework for high-fidelity simulations that will rationalise trends and inform materials design. 2) To obtain fundamental insight into the relation between porous catalyst structure and performance for important future industrial processes. As use-cases, we will focus on biomass-related transformations, and specifically on 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 parameterised with density functional theory (DFT) (reactive component) and molecular dynamics (MD) (transport component), towards predictive simulations, which will deliver guidance in the development of superior catalysts. 3) To experimentally validate the framework and the predictions of the models of aims 1, 2. Experimental approaches encompassing catalyst synthesis, physicochemical properties modification, characterisation, diffusion measurements and kinetic studies, will enable the validation of different components of the models and the testing of the theoretical predictions. These activities will deliver know-how for the design of materials and chemical processes with unprecedented accuracy and spatial resolution. The MD and DFT results, once validated against nuclear magnetic resonance (NMR) experiments, will help identify the rate-limiting steps affecting the performance of industrial processes (e.g., selective adsorption vs. diffusion controlled by pore structure). This CBET-EPSRC Agreement proposal builds on an Expression of Interest submitted to EPSRC in March 2023, which was approved in September 2023. Industrial discussions have shaped the project.
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