Escaping scaling relationships for water dissociation at interfacial sites of zirconia-supported Rh and Pt clusters

Combining artificial intelligence and physics-based modeling to directly assess atomic site stabilities: from sub-nanometer clusters to extended surfaces

The performance of functional materials is dictated by chemical and structural properties of individual atomic sites. In catalysts, for example, the thermodynamic stability of constituting atomic sites is a key descriptor from which more complex properties, such as molecular adsorption energies and reaction rates, can be derived. In this study, we present a widely applicable machine learning (ML) approach to instantaneously compute the stability of individual atomic sites in structurally and electronically complex nano-materials. Conventionally, we determine such site stabilities using computationally intensive first-principles calculations. With our approach, we predict the stability of atomic sites in sub-nanometer metal clusters of 3-55 atoms with mean absolute errors in the range of 0.11-0.14 eV. To extract physical insights from the ML model, we introduce a genetic algorithm (GA) for feature selection. This algorithm distills the key structural and chemical properties governing the stability of atomic sites in size-selected nanoparticles, allowing for physical interpretability of the models and revealing structure-property relationships. The results of the GA are generally model and materials specific. In the limit of large nanoparticles, the GA identifies features consistent with physics-based models for metal-metal interactions. By combining the ML model with the physics-based model, we predict atomic site stabilities in real time for structures ranging from sub-nanometer metal clusters (3-55 atom) to larger nanoparticles (147 to 309 atoms) to extended surfaces using a physically interpretable framework. Finally, we present a proof of principle showcasing how our approach can determine stable and active nanocatalysts across a generic materials space of structure and composition.

Influence of a Cu-zirconia interface structure on CO2 adsorption and activation

CO₂ adsorption and activation on a catalyst are key elementary steps for CO₂ conversion to various valuable products. In the present computational study, we screened different Cu-ZrO₂ interface structures and analyzed the influence of the interface structure on CO₂ binding strength using density functional theory calculations. Our results demonstrate that a Cu nanorod favors one position on both tetragonal and monoclinic ZrO₂ surfaces, where the bottom Cu atoms are placed close to the lattice oxygens. In agreement with previous calculations, we find that CO₂ prefers a bent bidentate configuration at the Cu-ZrO₂ interface and the molecule is clearly activated being negatively charged. Straining of the Cu nanorod influences CO₂ adsorption energy but does not change the preferred nanorod position on zirconia. Altogether, our results highlight that CO₂ adsorption and activation depend sensitively on the chemical composition and atomic structure of the interface used in the calculations. This structure sensitivity may potentially impact further catalytic steps and the overall computed reactivity profile.

Theoretical Study of an almost Barrier-Free Water Dissociation on a Platinum (111) Surface Alloyed with Ruthenium and Molybdenum

A theoretical study based on density functional theory for H₂O dissociation on the metal surface of Pt(111) alloyed simultaneously with Ru and Mo was performed. The determination of the minimum energy path using the climbing image nudged elastic band (CI-NEB) method shows that the dissociation reaction of H₂O with this catalyst requires almost no energy cost. This dissociation reaction is not only kinetically favored but also almost thermodynamically neutral and somewhat exothermic. The electronic structure analysis showed that much more charge was released in Mo and was used to bind the adsorbed hydroxyl (OH_ad). Further analyses of the density of states (DOS) showed that the large number of orbitals that overlap when OH binds to Mo are responsible for the stabilization of the OH-surface bond. The stability of the OH_ad fragment on the surface is believed to be a descriptor for the dissociation of H₂O with an almost spontaneous process.

Reconstruction and catalytic activity of hybrid Pd(100)/(111) monolayer on γ-Al2O3(100) in CH4, H2O, and O2 dissociation

The importance of the "heterogeneity" of a Pd monolayer induced by interaction with a semi-ionic support in catalysis was evaluated. The geometry of the Pd monolayer was optimized on the (100) plane of γ-Al2O3 at fixed unit cell parameters defined by the oxide. Simulation of the deposition of a whole Pd monolayer in the flat Pd(100) form cut from the bulk led to the formation of a slightly distorted Pd(111) monolayer. The subsequent chemisorption or dissociation of CH4 or H2O on the Pd(111) layer resulted in a new hybrid Pd(100)/(111) structure containing alternating elements of (100) and (111) planes (the parallel bands of squares and triangles), which are similar for both CH4 and H2O reactions, and two isolated Pd mono-vacancies, respectively. The hybrid Pd(100)/(111) layer without chemisorbed species was found to be more stable than the initial distorted Pd(111) layer. The catalytic capabilities of these monolayer structures were investigated for the dissociation of methane and the water-gas shift reaction (WGSR) due to the lower predicted activation barriers for CH4, H2O, and O2 dissociation on the hybrid Pd(100)/(111) layer compared to that on the pure (bulk) Pd(100) surface. Moreover, the exothermic heats of these reactions were calculated to be moderate instead of endothermic heats on the Pd(100) or Pd(111) surfaces. The heats of H2O and NH3 adsorption on various monolayers were tested, revealing their dependence on Pd atomic charges. The relevance of the model of the heterogeneous Pd monolayer for explaining the maximum reaction rate experimentally observed at different Pd coverages was discussed. The transferability of the geometry and the extent of charge inhomogeneity of the hybrid monolayer without vacancies were also tested on the same γ-Al2O3(100) support for Pt, Rh, and Ag.

Ensembles of Metastable States Govern Heterogeneous Catalysis on Dynamic Interfaces

Heterogeneous catalysis is at the heart of the chemical industry. Being able to tune and design efficient catalysts for processes of interest is of the utmost importance, and for this, a molecular-level understanding of heterogeneous catalysts is the first step and indeed a prime focus of modern catalysis research. For a long time, the single most thermodynamically stable structure of the catalytic interface attained under the reaction conditions had been envisioned as the reactive phase. However, some catalytic interfaces continue to undergo structural dynamics in the steady state, triggered by high temperatures and pressures and binding and changing reagents. Among particularly dynamic interfaces are such widely used catalysts as crystalline and amorphous surfaced supporting (sub)nanometallic clusters. Recently, it became clear that this dynamic fluxionality causes the supported clusters to populate many distinct structural and stoichiometric states under catalytic conditions. Hence, the catalytic interface should be viewed as an evolving statistical ensemble of many structures (rather than one structure). Every member in the ensemble contributes to the properties of the catalyst differently, in proportion to its probability of being populated. This new notion flips the established paradigm and calls for a new theory, new modeling approaches, operando measurements, and updated design strategies. The statistical ensemble nature of surface-supported subnanocluster catalysts can be exemplified by oxide-supported and adsorbate-covered Pt, Pd, Cu, and CuPd clusters, which are catalytic toward oxidative and nonoxidative dehydrogenation. They have access to a variety of 3D and quasi-2D shapes. The compositions of their thermal ensembles are dependent on the cluster size, leading to size-specific catalytic activities and the famous "every atom counts" phenomenon. The support and adsorbates affect catalyst structures, and the state of the reacting species causes the ensemble to change in every reaction intermediate. The most stable member of the ensemble dominates the thermodynamic properties of the corresponding intermediate, whereas the kinetics can be determined by more active but less populated metastable catalyst states, and that suggests that many earlier studies might have overlooked the actual active sites. Both effects depend on the relative time scales of catalyst restructuring and reaction dynamics. The catalyst may routinely operate off-equilibrium. Ensemble phenomena lead to surprising exceptions from established rules of catalysis, such as scaling relations and Arrhenius behavior. Catalyst deactivation is also an ensemble property, and its extent of mitigation can be predicted through the new paradigm. These findings were enabled by advances in theory, such as global optimization and subsequent utilization of multiple local minima and pathways sampling as well as operando catalyst characterization. The fact that the per-site and per-species resolution is needed for the description and prediction of catalyst properties gives theory the central role in catalysis research, as most experiments provide ensemble-average information and cannot detect the crucial minority species that may be responsible for the catalytic activity.

First-principles insight into CO hindered agglomeration of Rh and Pt single atoms on m-ZrO2

Kinetic and thermodynamic stability of single-atom and nanocluster catalysts is addressed under reaction conditions within a DFT-parametrised multi-scale thermodynamic framework combining atomistic, non-equilibrium, and nanothermodynamics.