Correlating Oxygen Reduction Reaction Activity and Structural Rearrangements in MgO-Supported Platinum Nanoparticles

Sampling Real-Time Atomic Dynamics in Metal Nanoparticles by Combining Experiments, Simulations, and Machine Learning

Even at low temperatures, metal nanoparticles (NPs) possess atomic dynamics that are key for their properties but challenging to elucidate. Recent experimental advances allow obtaining atomic-resolution snapshots of the NPs in realistic regimes, but data acquisition limitations hinder the experimental reconstruction of the atomic dynamics present within them. Molecular simulations have the advantage that these allow directly tracking the motion of atoms over time. However, these typically start from ideal/perfect NP structures and, suffering from sampling limits, provide results that are often dependent on the initial/putative structure and remain purely indicative. Here, by combining state-of-the-art experimental and computational approaches, how it is possible to tackle the limitations of both approaches and resolve the atomistic dynamics present in metal NPs in realistic conditions is demonstrated. Annular dark-field scanning transmission electron microscopy enables the acquisition of ten high-resolution images of an Au NP at intervals of 0.6 s. These are used to reconstruct atomistic 3D models of the real NP used to run ten independent molecular dynamics simulations. Machine learning analyses of the simulation trajectories allow resolving the real-time atomic dynamics present within the NP. This provides a robust combined experimental/computational approach to characterize the structural dynamics of metal NPs in realistic conditions.

Dynamics of chemical reactions on single nanocatalysts with heterogeneous active sites

Modern chemical science and industries critically depend on the application of various catalytic methods. However, the underlying molecular mechanisms of these processes still remain not fully understood. Recent experimental advances that produced highly-efficient nanoparticle catalysts allowed researchers to obtain more quantitative descriptions, opening the way to clarify the microscopic picture of catalysis. Stimulated by these developments, we present a minimal theoretical model that investigates the effect of heterogeneity in catalytic processes at the single-particle level. Using a discrete-state stochastic framework that accounts for the most relevant chemical transitions, we explicitly evaluated the dynamics of chemical reactions on single heterogeneous nanocatalysts with different types of active sites. It is found that the degree of stochastic noise in nanoparticle catalytic systems depends on several factors that include the heterogeneity of catalytic efficiencies of active sites and distinctions between chemical mechanisms on different active sites. The proposed theoretical approach provides a single-molecule view of heterogeneous catalysis and also suggests possible quantitative routes to clarify some important molecular details of nanocatalysts.

Pt38 as a promising ethanol catalyst: a first principles study

This first-principles study predicts Pt₃₈ nanoparticles as a catalyst for ethanol reactions. Starting from the adsorption properties, we shed light on the effectiveness of Pt-based nanoclusters as ethanol catalysts. First, the ethanol adsorption on Pt₃₈ shows that the most stable site positions the molecule with the oxygen anchored on top of an edge, whereas CH₃ is oriented towards the facet and the molecule remains in trans-symmetry. The ethanol-oxygen adsorbed on top of a facet Pt-atom offers the least stable configuration and the longer Pt-O distance (2.318 Å), while the shorter Pt-O distance (2.237 Å) is found when ethanol is on top of an edge site and the molecule is vertically oriented with Gauche symmetry. A shorter Pt-O distance correlates with higher radial breathing of the nanoparticle after ethanol adsorption. Atomic charge redistribution is calculated on all the considered systems and cases. In any event, we show that the Pt-anchor receives a charge, whilst oxygen-ethanol donates electrons. Orbital analysis shows that Pt-anchors and ethanol-oxygen atoms primarily exchange p-charge. Energy barriers associated with the ethanol bond cleavage show that the C-C bond break is slightly more favourable on Pt₃₈ than on an extended Pt(111). In addition, we find that the cleavage of the hydroxyl O-H ethanol bond shows a higher energy barrier while the removal of an H-atom from the CH₃ group is easier. These three facts indicate that the Pt₃₈ nanoparticle enhances ethanol catalysis and hence is a good candidate for ethanol-based fuel cells.

Born to be different: the formation process of Cu nanoparticles tunes the size trend of the activity for CO2 to CH4 conversion

We investigate the impact of the formation process of Cu nanoparticles on the distribution of adsorption sites and hence on their activity. Using molecular dynamics, we model formation pathways characteristic of physical synthesis routes as the annealing of a liquid droplet, the growth proceeding via the addition of single atoms, and the coalescence of individual nanoparticles. Each formation process leads to different and characteristic size-dependent distributions of their adsorption sites, catalogued and monitored on-the-fly by means of a suitable geometrical descriptor. Annealed or coalesced nanoparticles present a rather homogeneous distribution in the kind and relative abundance of non-equivalent adsorption sites. Atom-by-atom grown nanoparticles, instead, exhibit a more marked occurrence of adsorption sites corresponding to adatoms and small islands on (111) and (100) facets. Regardless of the formation process, highly coordinated sites are more likely in larger nanoparticles, while the abundance of low-coordination sites depends on the formation process and on the nanoparticle size. Furthermore, we show how each characteristic distribution of adsorption sites reflects in different size trends for the Cu-nanoparticle activity, taking as an example the electro-reduction of CO₂ into CH₄. To this end, we employ a multi-scale method and observe that the faceted but highly defected structures obtained during the atom-by-atom growth become more and more active with increasing size, with a mild dependence on the original seed. In contrast, the activity of Cu-nanoparticles obtained by annealing decreases with their size, while coalesced nanoparticles' activity shows a non-monotonic behaviour.

A kinetic Monte Carlo-blueprint for oxygen reduction on oxide-supported PtNi nanoalloys

To elucidate the effect of the architecture of supported bimetallic nanocatalysts, we developed a new lattice kinetic Monte Carlo based on the classifying and counting adsorption sites with respect to their generalized coordination number. We employed this tool to estimate the activity of MgO-supported PtNi nanoalloys for oxygen reduction. We demonstrated that the presence of Ni atoms in contact with the substrate massively enhances their activity with at least a 7-order of magnitude increase in the turnover of water production with respect to the case where only Pt lay at the interface. We further discussed how the nanoalloy shape affects the activity showing that truncated octahedra are 10² more active than cuboctahedra of similar size. We explained our results in terms of their distinct distribution and occurrence of the most active sites for oxygen reduction leading to the stabilization of different chemical species during the reaction dynamics. Our results suggest that engineering multifaceted and long edge PtNi-nanoalloys with a certain chemical ordering at the support interface would improve their catalytic performance for the oxygen reduction reaction.

Correlating Oxygen Reduction Reaction Activity and Structural Rearrangements in MgO-Supported Platinum Nanoparticles

We develop a multi‐scale approach towards the design of metallic nanoparticles with applications as catalysts in electrochemical reactions. The here discussed method exploits the relationship between nanoparticle architecture and electrochemical activity and is applied to study the catalytic properties of MgO(100)‐supported Pt nanosystems undergoing solid‐solid and solid‐liquid transitions. We observe that a major increment in the activity is associated to the reconstruction of the interface layers, supporting the need for a full geometrical characterisation of such structures also when in‐operando.