Dynamics of gold clusters on ceria during CO oxidation

Transferable, Living Data Sets for Predicting Global Minimum Energy Nanocluster Geometries

Modeling of nanocluster geometries is essential for studying the dependence of catalytic activity on the available active sites. In heterogeneous catalysis, the interfacial interaction of the support with the metal can result in modification of the structural and electronic properties of the clusters. To tackle the study of a diverse array of cluster shapes, data-driven methodologies are essential to circumvent prohibitive computational costs. At their core, these methods require large data sets in order to achieve the necessary accuracy to drive structural exploration. Given the similarity in binding character of the transition metals, cluster shapes encountered for various systems show a large amount of overlap. This overlap has been utilized to construct a living data set which may be carried over across multiple studies. Iterative refinement of this data set provides a low-cost pathway for initialization of cluster studies. It is shown that utilization of transferable structural information can reduce model construction costs by more than 90%. The benefits of this approach are particularly notable for alloy systems, which possess significantly larger configurational spaces compared to the pure-phase counterparts.

Descriptor for C2N-Supported Single-Cluster Catalysts in Bifunctional Oxygen Evolution and Reduction Reactions

Developing highly active cluster catalysts for the bifunctional oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) is significant for future renewable energy technology. Here, we employ first-principles calculations combined with a genetic algorithm to explore the activity trends of transition metal clusters supported on C2N. Our results indicate that the supported clusters, as bifunctional catalysts for the OER and the ORR, may outperform single-atom catalysts. In particular, the C2N-supported Ag6 cluster exhibits outstanding bifunctional activity with low overpotentials. Mechanistic analysis indicates that the activity of the cluster is related to the number of atoms in the active site as well as the interaction between the intermediate and the cluster. Accordingly, we identify a descriptor that links the intrinsic properties of the clusters with the activity of both the OER and the ORR. This work provides guidelines and strategies for the rational design of highly efficient bifunctional cluster catalysts.

The Promoting Role of Ni on In2O3 for CO2 Hydrogenation to Methanol

Ni-promoted indium oxide (In2O3) is a promising catalyst for the selective hydrogenation of CO2 to CH3OH, but the nature of the active Ni sites remains unknown. By employing density functional theory and microkinetic modeling, we elucidate the promoting role of Ni in In2O3-catalyzed CO2 hydrogenation. Three representative models have been investigated: (i) a single Ni atom doped in the In2O3(111) surface, (ii) a Ni atom adsorbed on In2O3(111), and (iii) a small cluster of eight Ni atoms adsorbed on In2O3(111). Genetic algorithms (GAs) are used to identify the optimum structure of the Ni8 clusters on the In2O3 surface. Compared to the pristine In2O3(111) surface, the Ni8-cluster model offers a lower overall barrier to oxygen vacancy formation, whereas, on both single-atom models, higher overall barriers are found. Microkinetic simulations reveal that only the supported Ni8 cluster can lead to high methanol selectivity, whereas single Ni atoms either doped in or adsorbed on the In2O3 surface mainly catalyze CO formation. Hydride species obtained by facile H2 dissociation on the Ni8 cluster are involved in the hydrogenation of adsorbed CO2 to formate intermediates and methanol. At higher temperatures, the decreasing hydride coverage shifts the selectivity to CO. On the Ni8-cluster model, the formation of methane is inhibited by high barriers associated with either direct or H-assisted CO activation. A comparison with a smaller Ni6 cluster also obtained with GAs exhibits similar barriers for key rate-limiting steps for the formation of CO, CH4, and CH3OH. Further microkinetic simulations show that this model also has appreciable selectivity to methanol at low temperatures. The formation of CO over single Ni atoms either doped in or adsorbed on the In2O3 surface takes place via a redox pathway involving the formation of oxygen vacancies and direct CO2 dissociation.

Ensemble representation of catalytic interfaces: soloists, orchestras, and everything in-between

Catalytic systems are complex and dynamic, exploring vast chemical spaces on multiple timescales. In this perspective, we discuss the dynamic behavior of fluxional, heterogeneous thermal and electrocatalysts and the ensembles of many isomers which govern their behavior. We develop a new paradigm in catalysis theory in which highly fluxional systems, namely sub-nano clusters, isomerize on a much shorter timescale than that of the catalyzed reaction, so macroscopic properties arise from the thermal ensemble of isomers, not just the ground state. Accurate chemical predictions can only be reached through a many-structure picture of the catalyst, and we explain the breakdown of conventional methods such as linear scaling relations and size-selected prevention of sintering. We capitalize on the forward-looking discussion of the means of controlling the size of these dynamic ensembles. This control, such that the most effective or selective isomers can dominate the system, is essential for the fluxional catalyst to be practicable, and their targeted synthesis to be possible. It will also provide a fundamental lever of catalyst design. Finally, we discuss computational tools and experimental methods for probing ensembles and the role of specific isomers. We hope that catalyst optimization using chemically informed descriptors of ensemble nature and size will become a new norm in the field of catalysis and have broad impacts in sustainable energy, efficient chemical production, and more.

Real-time dynamics and structures of supported subnanometer catalysts via multiscale simulations

Understanding the performance of subnanometer catalysts and how catalyst treatment and exposure to spectroscopic probe molecules change the structure requires accurate structure determination under working conditions. Experiments lack simultaneous temporal and spatial resolution and could alter the structure, and similar challenges hinder first-principles calculations from answering these questions. Here, we introduce a multiscale modeling framework to follow the evolution of subnanometer clusters at experimentally relevant time scales. We demonstrate its feasibility on Pd adsorbed on CeO2(111) at various catalyst loadings, temperatures, and exposures to CO. We show that sintering occurs in seconds even at room temperature and is mainly driven by free energy reduction. It leads to a kinetically (far from equilibrium) frozen ensemble of quasi-two-dimensional structures that CO chemisorption and infrared experiments probe. CO adsorption makes structures flatter and smaller. High temperatures drive very rapid sintering toward larger, stable/metastable equilibrium structures, where CO induces secondary structure changes only.

Toward an Atomic-Level Understanding of Ceria-Based Catalysts: When Experiment and Theory Go Hand in Hand

ConspectusBecause ceria (CeO₂) is a key ingredient in the formulation of many catalysts, its catalytic roles have received a great amount of attention from experiment and theory. Its primary function is to enhance the oxidation activity of catalysts, which is largely governed by the low activation barrier for creating lattice O vacancies. Such an important characteristic of ceria has been exploited in CO oxidation, methane partial oxidation, volatile organic compound oxidation, and the water-gas shift (WGS) reaction and in the context of automotive applications. A great challenge of such heterogeneously catalyzed processes remains the unambiguous identification of active sites.In oxidation reactions, closing the catalytic cycle requires ceria reoxidation by gas-phase oxygen, which includes oxygen adsorption and activation. While the general mechanistic framework of such processes is accepted, only very recently has an atomic-level understanding of oxygen activation on ceria powders been achieved by combined experimental and theoretical studies using in situ multiwavelength Raman spectroscopy and DFT.Recent studies have revealed that the adsorption and activation of gas-phase oxygen on ceria is strongly facet-dependent and involves different superoxide/peroxide species, which can now be unambiguously assigned to ceria surface sites using the combined Raman and DFT approach. Our results demonstrate that, as a result of oxygen dissociation, vacant ceria lattice sites are healed, highlighting the close relationship of surface processes with lattice oxygen dynamics, which is also of technical relevance in the context of oxygen storage-release applications.A recent DFT interpretation of Raman spectra of polycrystalline ceria enables us to take account of all (sub)surface and bulk vibrational features observed in the experimental spectra and has revealed new findings of great relevance for a mechanistic understanding of ceria-based catalysts. These include the identification of surface oxygen (Ce-O) modes and the quantification of subsurface oxygen defects. Combining these theoretical insights with operando Raman experiments now allows the (sub)surface oxygen dynamics of ceria and noble metal/ceria catalysts to be monitored under the reaction conditions.Applying these findings to Au/ceria catalysts provides univocal evidence for ceria support participation in heterogeneous catalysis. For room-temperature CO oxidation, operando Raman monitoring the (sub)surface defect dynamics clearly demonstrates the dependence of catalytic activity on the ceria reduction state. Extending the combined experimental/DFT approach to operando IR spectroscopy allows the elucidation of the nature of the active gold as (pseudo)single Au⁺ sites and enables us to develop a detailed mechanistic picture of the catalytic cycle. Temperature-dependent studies highlight the importance of facet-dependent defect formation energies and adsorbate stabilities (e.g., carbonates). While the latter aspects are also evidenced to play a role in the WGS reaction, the facet-dependent catalytic performance shows a correlation with the extent of gold agglomeration. Our findings are fully consistent with a redox mechanism, thus adding a new perspective to the ongoing discussion of the WGS reaction.As outlined above for ceria-based catalysts, closely combining state-of-the-art in situ/operando spectroscopy and theory constitutes a powerful approach to rational catalyst design by providing essential mechanistic information based on an atomic-level understanding of reactions.