In catalysis, nanoparticles enable chemical transformations and their structural and chemical fingerprints control activity. To develop understanding of such fingerprints, methods studying catalysts at realistic conditions have proven instrumental. Normally, these methods either probe the catalyst bed with low spatial resolution, thereby averaging out single particle characteristics, or probe an extremely small fraction only, thereby effectively ignoring most of the catalyst. Here, we bridge the gap between these two extremes by introducing highly multiplexed single particle plasmonic nanoimaging of model catalyst beds comprising 1000 nanoparticles, which are integrated in a nanoreactor platform that enables online mass spectroscopy activity measurements. Using the example of CO oxidation over Cu, we reveal how highly local spatial variations in catalyst state dynamics are responsible for contradicting information about catalyst active phase found in the literature, and identify that both surface and bulk oxidation state of a Cu nanoparticle catalyst dynamically mediate its activity.

The steadily increasing consumption of natural gas imposes a need to facilitate the handling and distribution of the fuel, which presently is compressed or condensed. Alternatively, reduced volatility and increased tractability are achieved by converting the chemical energy of the main component, methane, into liquid methanol. Previous studies have explored direct methane-to-methanol conversion, but suitable catalysts have not yet been identified. Here, the complete reaction cycle for methane-to-methanol conversion over the Cu-SSZ-13 system is studied using density functional theory. The first step in the reaction cycle is the migration of Cu species along the zeolite framework forming the Cu pair, which is necessary for the adsorption of O2. Methane conversion occurs over the CuOOCu and CuOCu sites, consecutively, after which the system is returned to its initial structure with two separate Cu ions. A density functional theory-based kinetic model shows high activity when water is included in the reaction mechanism, for example, even at very low partial pressures of water, the kinetic model results in a turnover frequency of ∼1 at 450 K. The apparent activation energy from the kinetic model (∼1.1 eV) is close to recent measurements. However, experimental studies always observe very small amounts of methanol compared to formation of more energetically preferred products, for example, CO2. This low selectivity to methanol is not described by the current reaction mechanism as it does not consider formation of other species; however, the results suggest that selectivity, rather than inherent kinetic limitations, is an important target for improving methanol yields from humid systems. Moreover, a closed reaction cycle for the partial oxidation of methane has long been sought, and in achieving this over the Cu-SSZ-13, this study contributes one more step toward identifying a suitable catalyst for direct methane-to-methanol conversion.

In plasmon-mediated photocatalysis it is of critical importance to differentiate light-induced catalytic reaction rate enhancement channels, which include near-field effects, direct hot carrier injection, and photothermal catalyst heating. In particular, the discrimination of photothermal and hot electron channels is experimentally challenging, and their role is under keen debate. Here we demonstrate using the example of CO oxidation over nanofabricated neat Pd and Au 50 Pd 50 alloy catalysts, how photothermal rate enhancement differs by up to 3 orders of magnitude for the same photon flux, and how this effect is controlled solely by the position of catalyst operation along the light-off curve measured in the dark. This highlights that small fluctuations in reactor temperature or temperature gradients across a sample may dramatically impact global and local photothermal rate enhancement, respectively, and thus control both the balance between different rate enhancement mechanisms and the way strategies to efficiently distinguish between them should be devised.

This paper uses a network of ideal flow reactors and a detailed population balance model to study the evolution of the size and shape distributions of pigmentary titanium dioxide, formed under industrial synthesis conditions. The industrial reactor has multiple reactant injections, a tubular working zone in which the exothermic reaction is completed, and a cooling zone. A network of continuously stirred tank reactors is used to model variation in composition around the feeds and plug flow reactors with prescribed temperature gradients are used to describe the working and cooling zones. The quality of the industrial product depends on its morphology, and this is influenced by factors including temperature and throughput. In this paper, a multivariate particle model is accommodated using a stochastic method and the particle morphology is characterized in terms of the distributions of primary and aggregate particle diameters, number of primary particles per particle and neck radii of connected primary particles. Increasing temperature or residence time is shown to produce larger particles. Qualitative similarities are highlighted between such findings and previous studies. The throughput studies are also in qualitative agreement with empirical industrial experience. There is scope for extending and improv

This work presents a hybrid particle-number and particle model to improve efficiency in solving population balance equations for type spaces spanning spherical and aggregate particles. The particle-number model tracks simpler, spherical particles cheaply by storing only the number of particles with a given one-dimensional internal coordinate, while the particle model allows resolution of the detailed aggregate structure that occurs due to collision and coagulation between particles by storing distinct computational entries for each particle. This approach is exact if primary particles are defined by their monomer count and the particle-number model increments in single monomers. A stochastic method is used to solve the population balance equations for the combined type space. The hybrid method works well for large ensembles (> 2 12 particles) with a detailed particle model, where per