Exploring the origins of crystallisation kinetics in hierarchical materials using in situ X-ray diffraction and pair distribution function analysis.

The discovery of novel catalytic materials is predicated on understanding contemporary synthetic processes. With this fundamental knowledge in place it becomes possible to modify the final material with subtle changes to the synthesis process. In this vein, hierarchical materials, formed by the addition of a mesoporogen within the hydrothermal synthesis, have attracted a significant amount of attention due to their catalytic benefits over analogous microporous species. In this work we monitor the hydrothermal synthesis in situ of a hierarchical and a microporous aluminophosphate, for the first time, combining total scattering and pairwise distribution function data. In doing so we observe the local formation of the species, and the longer range crystallisation processes concurrently.

A machine learning approach to graph-theoretical cluster expansions of the energy of adsorbate layers.

The accurate description of the energy of adsorbate layers is crucial for the understanding of chemistry at interfaces. For heterogeneous catalysis, not only the interaction of the adsorbate with the surface but also the adsorbate-adsorbate lateral interactions significantly affect the activation energies of reactions. Modeling the interactions of the adsorbates with the catalyst surface and with each other can be efficiently achieved in the cluster expansion Hamiltonian formalism, which has recently been implemented in a graph-theoretical kinetic Monte Carlo (kMC) scheme to describe multi-dentate species. Automating the development of the cluster expansion Hamiltonians for catalytic systems is challenging and requires the mapping of adsorbate configurations for extended adsorbates onto a graphical lattice. The current work adopts machine learning methods to reach this goal. Clusters are automatically detected based on formalized, but intuitive chemical concepts. The corresponding energy coefficients for the cluster expansion are calculated by an inversion scheme. The potential of this method is demonstrated for the example of ethylene adsorption on Pd(111), for which we propose several expansions, depending on the graphical lattice. It turns out that for this system, the best description is obtained as a combination of single molecule patterns and a few coupling terms accounting for lateral interactions.

Metal-Support Interactions in Heterogeneous Catalysis: DFT Calculations on the Interaction of Copper Nanoparticles with Magnesium Oxide.

Oxide supports play an important role in enhancing the catalytic properties of transition metal nanoparticles in heterogeneous catalysis. How extensively interactions between the oxide support and the nanoparticles impact the electronic structure as well as the surface properties of the nanoparticles is hence of high interest. In this study, the influence of a magnesium oxide support on the properties of copper nanoparticles with different size, shape, and adsorption sites is investigated using density functional theory (DFT) calculations. By proposing simple models to reduce the cost of the calculations while maintaining the accuracy of the results, we show using the nonreducible oxide support MgO as an example that there is no significant influence of the MgO support on the electronic structure of the copper nanoparticles, with the exception of adsorption directly at the Cu-MgO interface. We also propose a simplified methodology that allows us to reduce the cost of the calculations, while the accuracy of the results is maintained. We demonstrate in addition that the Cu nanowire model corresponds well to the nanoparticle model, which reduces the computational cost even further.

Direct Observation of Ni Nanoparticle Growth in Carbon-Supported Nickel under Carbon Dioxide Hydrogenation Atmosphere.

Understanding nanoparticle growth is crucial to increase the lifetime of supported metal catalysts. In this study, we employ in situ gas-phase transmission electron microscopy to visualize the movement and growth of ensembles of tens of nickel nanoparticles supported on carbon for CO2 hydrogenation at atmospheric pressure (H2:CO2 = 4:1) and relevant temperature (450 °C) in real time. We observe two modes of particle movement with an order of magnitude difference in velocity: fast, intermittent movement (vmax = 0.7 nm s-1) and slow, gradual movement (vaverage = 0.05 nm s-1). We visualize the two distinct particle growth mechanisms: diffusion and coalescence, and Ostwald ripening. The diffusion and coalescence mechanism dominates at small interparticle distances, whereas Ostwald ripening is driven by differences in particle size. Strikingly, we demonstrate an interplay between the two mechanisms, where first coalescence takes place, followed by fast Ostwald ripening due to the increased difference in particle size. Our direct visualization of the complex nanoparticle growth mechanisms highlights the relevance of studying nanoparticle growth in supported nanoparticle ensembles under reaction conditions and contributes to the fundamental understanding of the stability in supported metal catalysts.

An Insight into the Role of Reactant Structure Effect in Pd/C Catalysed Aldehyde Hydrogenation.

The different activity of a 1% Pd/carbon catalyst towards aromatic and aliphatic aldehydes hydrogenation has been explored by 13C NMR relaxation. The ratio between T1 relaxation times of adsorbed (ads) and free diffusing (bulk) molecules (T1ads/T1bulk) can be used as an indicator of the relative strength of interaction between the reactant and the catalytic surface, where the lower the T1ads/T1bulk, the higher the adsorption strength. It can be seen that 1% Pd/carbon showed a reverse catalytic behaviour towards benzaldehyde and octanal hydrogenation, which can be explained by analysing the T1 relaxation times related to each substrate in the presence of the catalyst. Comparing and correlating the different T1ads/T1bulk values, we were able to prove that the different catalytic results mainly depend on the contrasting adsorption behaviour of substrates on the catalyst. Moreover, the role of the solvent has been disclosed, as NMR results revealed that the adsorption of the reactants was strongly affected by the choice of solvent, which is revealed to be critical in modulating catalytic activity. As a consequence, T1ads/T1bulk measurements can provide a guide to the selection of appropriate reaction conditions for improving catalytic activity.

Competition between reverse water gas shift reaction and methanol synthesis from CO2: influence of copper particle size.

Converting CO2 into value-added chemicals and fuels, such as methanol, is a promising approach to limit the environmental impact of human activities. Conventional methanol synthesis catalysts have shown limited efficiency and poor stability in a CO2/H2 mixture. To design improved catalysts, crucial for the effective utilization of CO2, an in-depth understanding of the active sites and reaction mechanism is desired. The catalytic performance of a series of carbon-supported Cu catalysts, with Cu particle sizes in the range of 5 to 20 nm, was evaluated under industrially relevant temperature and pressure, i.e. 260 °C and 40 bar(g). The CO2 hydrogenation reaction exhibited clear particle size effects up to 13 nm particles, with small nanoparticles having the lower activity, but higher methanol selectivity. MeOH and CO formation showed a different size-dependence. The TOFCO increased from 1.9 × 10-3 s-1 to 9.4 × 10-3 s-1 with Cu size increasing from 5 nm to 20 nm, while the TOFMeOH was size-independent (8.4 × 10-4 s-1 on average). The apparent activation energies for MeOH and CO formation were size-independent with values of 63 ± 7 kJ mol-1 and 118 ± 6 kJ mol-1, respectively. Hence the size dependence was ascribed to a decrease in the fraction of active sites suitable for CO formation with decreasing particle size. Theoretical models and DFT calculations showed that the origin of the particle size effect is most likely related to the differences in formate coverage for different Cu facets whose abundancy depends on particle size. Hence, the CO2 hydrogenation reaction is intrinsically sensitive to the Cu particle size.

Combined spectroscopic and computational study for optimising catalyst design in hydrocarbon transformations.

Molecular interactions of hydrocarbons within the confined pores of heterogeneous catalysts can influence reaction pathways, which play a crucial role in determining the overall efficacy of catalytic transformations. We probe the interactions of n-butane with a solid-acid zeolite, mordenite, combining inelastic neutron scattering with DFT calculations. This reveals that the solid-acid sites within mordenite induce a conformer change, which could be key in designing optimised catalysts, for hydrocarbon transformations.

Thiol Functionalised Supports for Controlled Metal Nanoparticle Formation for Improved C-C Coupling.

The myriad applications of metal nanoparticle systems have individual demands on their size, shape and electronic states, demanding novel synthetic methods to optimise these properties. Herein we report our method of exploiting strong thiol-Pd binding as a precursor for forming small, uniform Pd nanoparticles on activation. We validate our approach with a range of characterisation techniques and contrast our design strategy with an analogous wetness impregnation method, showing the drastic improvements for catalytic C-C coupling. The presence of the thiol groups offers greater control over nanoparticle formation, particularly temperature resolution on activation, potentially allowing more targeted nanoparticle formation procedures.