Local Fluxionality of Surface-Deposited Cluster Catalysts: The Case of Pt7 on Al2O3

Simulating Structural Dynamics of Metal Catalysts under Operative Conditions

Structural reconstructions of metal catalysts have been recognized as common phenomena during catalytic reactions, which play a key role in their activities in heterogeneous catalysis. Precisely identifying the structures under the operative conditions becomes a prerequisite to establish a reliable structure-activity relationship and further rationalize the design of metal catalysts. However, real-time capture of the structural variations of catalysts at the atomic level with high-temporal resolution is a grand challenge for present in situ characterizations. During the past decade, significant progress has been made in theory to couple the structures with the reaction conditions to reproduce the experimental observations and predict the adsorbate-induced changes of catalysts in composition, morphology, size, etc. Modeling the dynamic correlation between the structure and activity of the metal catalysts brings us advanced knowledge of heterogeneous catalysis and becomes indispensable for accurate evaluation of the performance of metal catalysts.

Comparison of methods for the NMR measurement of motionally averaged dipolar couplings

Motionally averaged dipolar couplings are an important tool for understanding the complex dynamics of catalysts, polymers, and biomolecules. While there is a plethora of solid-state NMR pulse sequences available for their measurement, in can be difficult to gauge the methods' strengths and weaknesses. In particular, there has not been a comprehensive comparison of their performance in natural abundance samples, where 1H homonuclear dipolar couplings are important and the use of large MAS rotors may be required for sensitivity reasons. In this work, we directly compared some of the more common methods for measuring C-H dipolar couplings in natural abundance samples using L-alanine (L-Ala) and the N-formyl-L-methionyl-L-leucyl-L-phenylalanine (fMLF) tripeptide as model systems. We evaluated their performance in terms of accuracy, resolution, sensitivity, and ease of implementation. We found that, despite the presence of 1H homonuclear dipolar interactions, all methods, with the exception of REDOR, were able to yield the reasonable dipolar coupling strengths for both mobile and static moieties. Of these methods, PDLF provides the most convenient workflow and precision at the expense of low sensitivity. In low-sensitivity cases, MAS-PISEMA and DIPSHIFT appear to be the better options.

Single-Atom based Metal-Organic Framework Photocatalysts for Solar-Fuel Generation

The growing demand for fossil fuels and subsequent CO2 emissions prompted a search for alternate sources of energy and a reduction in CO2. Photocatalysis driven by solar light has been found as a potential research area to tackle both these problems. In this direction, SAC@MOF (Single-atom loaded MOFs) photocatalysis is an emerging field and a promising technology. The unique properties of single-atom catalysts (SACs), such as high catalytic activity and selectivity, are leveraged in these systems. Photocatalysis, focusing on the utilization of Metal-Organic Frameworks (MOFs) as platforms for creating single-atom catalysts (SACs) characterized by metal single-atoms (SAs) as their active sites, are noted for their unparalleled atomic efficiency, precisely defined active sites, and superior photocatalytic performance. The synergy between MOFs and SAs in photocatalytic systems is meticulously examined, highlighting how they collectively enhance photocatalytic efficiency. This review examines SAC@MOF development and applications in environmental and energy sectors, focusing on synthesis and stabilization methods for SACs on MOFs and also characterization techniques vital for understanding these catalysts. The potential of SAC@MOF in CO2 Photoreduction and Photocatalytic H2 evolution is highlighted, emphasizing its role in green energy technologies and advances in materials science and Photocatalysis.

Comprehensive Density Functional and Kinetic Monte Carlo Study of CO2 Hydrogenation on a Well-Defined Ni/CeO2 Model Catalyst: Role of Eley-Rideal Reactions

A detailed multiscale study of the mechanism of CO2 hydrogenation on a well-defined Ni/CeO2 model catalyst is reported that couples periodic density functional theory (DFT) calculations with kinetic Monte Carlo (kMC) simulations. The study includes an analysis of the role of Eley-Rideal elementary steps for the water formation step, which are usually neglected on the overall picture of the mechanism, catalytic activity, and selectivity. The DFT calculations for the chosen model consisting of a Ni4 cluster supported on CeO2 (111) show large enough adsorption energies along with low energy barriers that suggest this catalyst to be a good option for high selective CO2 methanation. The kMC simulations results show a synergic effect between the two 3-fold hollow sites of the supported Ni4 cluster with some elementary reactions dominant in one site, while other reactions prefer the another, nearly equivalent site. This effect is even more evident for the simulations explicitly including Eley-Rideal steps. The kMC simulations reveal that CO is formed via the dissociative pathway of the reverse water-gas shift reaction, while methane is formed via a CO2 → CO → HCO → CH → CH2 → CH3 → CH4 mechanism. Overall, our results show the importance of including the Eley-Rideal reactions and point to small Ni clusters supported on the CeO2 (111) surface as potential good catalysts for high selective CO2 methanation under mild conditions, while very active and selective toward CO formation at higher temperatures.

A possibility to infer frustrations of supported catalytic clusters from macro-scale observations

Recent experimental and theoretical studies suggest that dynamic active centres of supported heterogeneous catalysts may, under certain conditions, be frustrated. Such out-of-equilibrium materials are expected to possess unique catalytic properties and also higher level of functionality. The latter is associated with the navigation through the free energy landscapes with energetically close local minima. The lack of common approaches to the study of out-of-equilibrium materials motivates the search for specific ones. This paper suggests a way to infer some valuable information from the interplay between the intensity of reagent supply and regularities of product formation.

Iterative multiscale and multi-physics computations for operando catalyst nanostructure elucidation and kinetic modeling

Modern heterogeneous catalysis has benefitted immensely from computational predictions of catalyst structure and its evolution under reaction conditions, first-principles mechanistic investigations, and detailed kinetic modeling, which are rungs on a multiscale workflow. Establishing connections across these rungs and integration with experiments have been challenging. Here, operando catalyst structure prediction techniques using density functional theory simulations and ab initio thermodynamics calculations, molecular dynamics, and machine learning techniques are presented. Surface structure characterization by computational spectroscopic and machine learning techniques is then discussed. Hierarchical approaches in kinetic parameter estimation involving semi-empirical, data-driven, and first-principles calculations and detailed kinetic modeling via mean-field microkinetic modeling and kinetic Monte Carlo simulations are discussed along with methods and the need for uncertainty quantification. With these as the background, this article proposes a bottom-up hierarchical and closed loop modeling framework incorporating consistency checks and iterative refinements at each level and across levels.

Single-atom catalysis enabled by high-energy metastable structures

Owing to limited degrees of freedom, the active sites of stable single-atom catalyst (SAC) often have one structure that is energetically much lower than other local-minimum structures. Thus, the SAC adopts one lowest-energy structure (LES) with an overwhelmingly larger proportion than any other high-energy metastable structure (HEMS), and the LES is commonly assumed to be solely responsible for the catalytic performance of an SAC. Herein, we demonstrate with SACs anchored on CeO2 that the HEMS of an SAC, even though its proportion remains several orders of magnitude lower than the LES throughout the catalytic reaction, can dictate catalysis with extraordinary activity arising from its unique coordination environment and oxidation state. Thus, we unravel the key role of HEMS-enabled catalysis in single-atom catalysis, which shakes the common assumption in the studies of SACs and urges new developments in both experiment and theory to identify and exploit catalysis via HEMSs.

1H chemical shift anisotropy: a high sensitivity solid-state NMR dynamics probe for surface studies?

Dynamics play significant roles in chemistry and biochemistry-molecular motions impact both large- and small-scale chemical reactions in addition to biochemical processes. In many systems, including heterogeneous catalysts, the characterization of dynamics remains a challenge. The most common approaches involve the solid-state NMR measurement of anisotropic interactions, in particular ²H quadrupolar coupling and ¹H-X dipolar coupling, which generally require isotope enrichment. Due to the high sensitivity of ¹H NMR, ¹H chemical shift anisotropy (CSA) is a particularly enticing, and underexplored, dynamics probe. We carried out ¹H CSA and ¹H-¹³C dipolar coupling measurements in a series of model supported complexes to understand how ¹H CSA can be leveraged to gain dynamic information for heterogeneous catalysts. Mathematical descriptions are given for the dynamic averaging of the CSA tensor, and its dependence on orientation and asymmetry. The variability of the orientation of the tensor in the molecular frame, in addition to its magnitude and asymmetry, negatively impacts attempts to extract quantitative dynamic information. Nevertheless, ¹H CSA measurements can reveal useful qualitative insights into the motions of a particularly dilute site, such as from a surface species.

Exploring the Potential Energy Surface of Pt6 Sub-Nano Clusters Deposited over Graphene

Catalytic systems based on sub-nanoclusters deposited over different supports are promising for very relevant chemical transformations such as many electrocatalytic processes as the ORR. These systems have been demonstrated to be very fluxional, as they are able to change shape and interconvert between each other either alone or in the presence of adsorbates. In addition, an accurate representation of their catalytic activity requires the consideration of ensemble effects and not a single structure alone. In this sense, a reliable theoretical methodology should assure an accurate and extensive exploration of the potential energy surface to include all the relevant structures and with correct relative energies. In this context, we applied DFT in conjunction with global optimization techniques to obtain and analyze the characteristics of the many local minima of Pt₆ sub-nanoclusters over a carbon-based support (graphene)-a system with electrocatalytic relevance. We also analyzed the magnetism and the charge transfer between the clusters and the support and paid special attention to the dependence of dispersion effects on the ensemble characteristics. We found that the ensembles computed with and without dispersion corrections are qualitatively similar, especially for the lowest-in-energy clusters, which we attribute to a (mainly) covalent binding to the surface. However, there are some significant variations in the relative stability of some clusters, which would significantly affect their population in the ensemble composition.

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.

Theoretical Perspective on Operando Spectroscopy of Fluxional Nanocatalysts

Improvements in operando spectroscopy have enabled the catalysis community to investigate the dynamic nature of catalysts under operating conditions with increasing detail. Still, the highly dynamic nature of some catalysts, such as fluxional supported subnano clusters, presents a formidable challenge even for the most state-of-the-art techniques. The reason is that such fluxional catalytic interfaces contain a variety of thermally accessible states. Operando spectroscopies used in catalysis generally fall into two categories: ensemble-based techniques, which provide spectra containing the signals of the entire ensemble of states of the catalyst and are not necessarily dominated by the most active species, and localized techniques, which provide atomistic-level information about the dynamics of active sites in a very small area, which might not include the most active species. Combining many different kinds of techniques can provide detailed insight; however, we propose that effective utilization of specific computational techniques and approaches within the fluxionality paradigm can fill the gap and enable atomistic characterization of the most relevant catalytic sites.

Addressing Dynamics at Catalytic Heterogeneous Interfaces with DFT-MD: Anomalous Temperature Distributions from Commonly Used Thermostats

Density functional theory-based molecular dynamics (DFT-MD) has been widely used for studying the chemistry of heterogeneous interfacial systems under operational conditions. We report frequently overlooked errors in thermostated or constant-temperature DFT-MD simulations applied to study (electro)catalytic chemistry. Our results demonstrate that commonly used thermostats such as Nosé-Hoover, Berendsen, and simple velocity-rescaling methods fail to provide a reliable temperature description for systems considered. Instead, nonconstant temperatures and large temperature gradients within the different parts of the system are observed. The errors are not a "feature" of any particular code but are present in several ab initio molecular dynamics implementations. This uneven temperature distribution, due to inadequate thermostatting, is well-known in the classical MD community, where it is ascribed to the failure in kinetic energy equipartition among different degrees of freedom in heterogeneous systems (Harvey et al. J. Comput. Chem. 1998, 726-740) and termed the flying ice cube effect. We provide tantamount evidence that interfacial systems are susceptible to substantial flying ice cube effects and demonstrate that the traditional Nosé-Hoover and Berendsen thermostats should be applied with care when simulating, for example, catalytic properties or structures of solvated interfaces and supported clusters. We conclude that the flying ice cube effect in these systems can be conveniently avoided using Langevin dynamics.

Dynamics of Heterogeneous Catalytic Processes at Operando Conditions

The rational design of high-performance catalysts is hindered by the lack of knowledge of the structures of active sites and the reaction pathways under reaction conditions, which can be ideally addressed by an in situ/operando characterization. Besides the experimental insights, a theoretical investigation that simulates reaction conditions-so-called operando modeling-is necessary for a plausible understanding of a working catalyst system at the atomic scale. However, there is still a huge gap between the current widely used computational model and the concept of operando modeling, which should be achieved through multiscale computational modeling. This Perspective describes various modeling approaches and machine learning techniques that step toward operando modeling, followed by selected experimental examples that present an operando understanding in the thermo- and electrocatalytic processes. At last, the remaining challenges in this area are outlined.

Active Site Fluxional Restructuring as a New Paradigm in Triggering Reaction Activity for Nanocluster Catalysis

The rationale of the catalytic activity observed in experiments is a crucial task in fundamental catalysis studies. Efficient catalyst design relies on an accurate understanding of the origin of the activity at the atomic level. Theoretical studies have been widely developed to reach such a fundamental atomic scale understanding of catalytic activity. Current theories ascribe the catalytic activity to the geometric and electronic structure of the active site, in which the geometrical and electronic structure effects are derived from the equilibrium geometry of active sites characterizing the static property of the catalyst; however catalysts, especially in the form of nanoclusters, may present fluxional and dynamic structure under reaction conditions, and the effect of this fluxional behavior is not yet widely recognized. Therefore, this Account will focus on the fluxionality of the active sites, which is driven by thermal fluctuations under finite temperature.Under reaction conditions, nanocluster catalysts can readily restructure, either being promoted to another metastable isomer (named as plastic fluxionality) or presenting ample deformations around their equilibrium geometry (named as elastic fluxionality). This Account summarizes our recent studies on the fluxionality of the nanoclusters and how plastic and elastic fluxionalities play roles in highly efficient reaction pathways. Our results show that the low energy metastable isomers formed by plastic fluxionality can manifest high reactivity despite their minor occurrence probability in the mixture of catalyst isomers. In the end, the highly active metastable isomer may dominate the total observed reactivity. In addition, the isomerization between the global minimum structure and the highly active metastable isomer can be a central step in catalytic transformations in order to circumvent some difficult reaction steps and may govern the overall mechanism. In addition, the thermal fluctuation driven elastic fluxionality is also found to play a key role, complementary to plastic fluxionality. The elastic fluxionality creates substantial structural deformations of the active site, and these deformed geometries enable low activation energies and high catalytic activity, which cannot be found from the static equilibrium geometry of the catalyst. A dedicated global activity search algorithm is proposed to search for the optimal reaction pathway on fluxional nanoclusters. In summary, our studies demonstrate that thermal-driven fluxionality provides a different paradigm for understanding the high activity of nanoclusters under reaction conditions beyond the static description of geometric and electronic structure. We first summarize our previous results and then provide a perspective for further studies on how to investigate and take the advantage of the fluxional geometry of nanoclusters. We will defend in this Account that the static picture for the active site is not complete and might miss critical reaction pathways that are highly efficient and only open after thermally induced restructuring of the active site.

Dynamics and Site Isolation: Keys to High Propane Dehydrogenation Performance of Silica-Supported PtGa Nanoparticles

Nonoxidative dehydrogenation of light alkanes has seen a renewed interest in recent years. While PtGa systems appear among the most efficient catalyst for this reaction and are now implemented in production plants, the origin of the high catalytic performance in terms of activity, selectivity, and stability in PtGa-based catalysts is largely unknown. Here we use molecular modeling at the DFT level on three different models: (i) periodic surfaces, (ii) clusters using static calculations, and (iii) realistic size silica-supported nanoparticles (1 nm) using molecular dynamics and metadynamics. The combination of the models with experimental data (XAS, TEM) allowed the refinement of the structure of silica-supported PtGa nanoparticles synthesized via surface organometallic chemistry and provided a structure-activity relationship at the molecular level. Using this approach, the key interaction between Pt and Ga was evidenced and analyzed: the presence of Ga increases (i) the interaction between the oxide surface and the nanoparticles, which reduces sintering, (ii) the Pt site isolation, and (iii) the mobility of surface atoms which promotes the high activity, selectivity, and stability of this catalyst. Considering the complete system for modeling that includes the silica support as well as the dynamics of the PtGa nanoparticle is essential to understand the catalytic performances.

Observing the three-dimensional dynamics of supported metal complexes

The dynamics of heterogeneous catalysts are linked to their activity and selectivity but are poorly understood. NMR enables for the determination of high-resolution dynamic structures for such sites and the mapping of accessible conformations.

Adsorption-Induced Liquid-to-Solid Phase Transition of Cu Clusters in Catalytic Dissociation of CO2

Sub-nanometer metal clusters widely existing in catalysts have a large ensemble of metastable isomers that can interconvert during catalytic reactions, exhibiting complex dynamical catalytic effects. In this work, we systematically investigate the temperature dependent structural dynamics of the Cu₁₃ cluster in CO₂ dissociation using ab initio molecular dynamics and the free energy calculation method. We find an abnormal entropic effect due to adsorption-induced liquid-to-solid phase transition of the cluster during the course of the elementary dissociation step at transition temperatures. In the dissociation product, the formation of a rigid Cu₃O unit decreases the dynamical fluidity of the cluster and increases the melting temperature, causing a decrease in the entropy of the dissociation product. Our work demonstrates the nontrivial effects of surface adsorption on phase transition behaviors of dynamic clusters and offers a new perspective to dynamic catalysis.

Reagent-Triggered Isomerization of Fluxional Cluster Catalyst via Dynamic Coupling

Metallic cluster catalysts have many thermodynamically accessible isomers with diverse active sites and low reaction barriers, and lately a strong hypothesis emerged that the many catalyst states collectively drive the catalysis. However, it remained a hypothesis that catalyst isomerization is actually kinetically feasible under the current reaction conditions. Using high-temperature dynamics simulations and sampling, a range of orientations, and vibrational energy distributions, we probe how thermal effects and molecular events affect cluster catalyst dynamics. We show that even such a delicate affair as the dissociation or scattering of a methane molecule on the heavy and thus slow Pt₁₃ cluster triggers substantial isomerization of the catalyst, far beyond thermal at 700 K. A kinetic coupling between the methane activity and cluster catalyst dynamics is observed. In return, the thermal dynamics of the cluster affects the methane reaction and scattering probabilities. Hence, molecular events at the surfaces of fluxional cluster catalysts should facilitate the population of an ensemble of catalyst states under the current reaction conditions, with implications for available active sites, reaction mechanisms, and apparent rates.

CO2 Hydrogenation to Formate and Formic Acid by Bimetallic Palladium-Copper Hydride Clusters

Mass spectrometric analysis of the anionic products of interaction between bimetallic palladium-copper tetrahydride anions, PdCuH₄^-, and carbon dioxide, CO₂, in a reaction cell shows an efficient generation of the PdCuCO₂H₄^- intermediate and formate/formic acid complexes. Multiple structures of PdCuH₄^- and PdCuCO₂H₄^- are identified by a synergy between anion photoelectron spectroscopy and quantum chemical calculations. The higher energy PdCuH₄^- isomer is shown to drive the catalytic hydrogenation of CO₂, emphasizing the importance of accounting for higher energy isomers for cluster catalytic activity. This study represents the first example of CO₂ hydrogenation by bimetallic hydride clusters.

Efficient Global Structure Optimization with a Machine-Learned Surrogate Model

We propose a scheme for global optimization with first-principles energy expressions of atomistic structure. While unfolding its search, the method actively learns a surrogate model of the potential energy landscape on which it performs a number of local relaxations (exploitation) and further structural searches (exploration). Assuming Gaussian processes, deploying two separate kernel widths to better capture rough features of the energy landscape while retaining a good resolution of local minima, an acquisition function is used to decide on which of the resulting structures is the more promising and should be treated at the first-principles level. The method is demonstrated to outperform by 2 orders of magnitude a well established first-principles based evolutionary algorithm in finding surface reconstructions. Finally, global optimization with first-principles energy expressions is utilized to identify initial stages of the edge oxidation and oxygen intercalation of graphene sheets on the Ir(111) surface.

Dynamic vs static behaviour of a supported nanoparticle with reaction-induced catalytic sites in a lattice model

Modern literature shows a rapidly growing interest to the supported nanocatalysts with dynamic behaviour under reaction conditions. This new frontier of heterogeneous catalysis is recognized as one of the most challenging and worthy of consideration from all possible angles. In this context, a previously suggested lattice model is used to get an insight, by means of kinetic Monte Carlo, into the influence of the mobility of reaction-induced catalytic sites of a two-dimensional supported nanoparticle on the system behaviour. The results speak in favour of feasibility of dynamic nanocatalysts with self-organized structures capable of robust functioning. This approach, from the macroscopic end, is believed to be a useful complement to ever developing experimental and first principle approaches.

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.

Pt8 cluster on alumina under a pressure of hydrogen: Support-dependent reconstruction from first-principles global optimization

Alumina supported Pt nanoclusters under a hydrogen environment play a crucial role in many heterogeneous catalysis applications. We conducted grand canonical genetic algorithm simulations for supported Pt₈ clusters in a hydrogen gas environment to study the intracluster, cluster-support, and cluster-adsorbate interactions. Two alumina surfaces, α-Al₂O₃(0001) and γ-Al₂O₃(100), and two conditions, T = 600 °C, p_H2 = 0.1 bar and T = 25 °C, p_H2 = 1.0 bar, were considered corresponding to low and high hydrogen chemical potential μ_H, respectively. The low free energy ensemble of Pt₈ is decorated by a medium (2-12 H), respectively, high (20-30 H), number of hydrogen atoms under equilibrium at low μ_H, respectively, high μ_H, and undergoes different morphological transformations on the two surfaces. On α-Al₂O₃(0001), Pt₈ is mostly 3D but very fluxional in structure at low μ_H and converts to open one-layer 2D structures with minimal fluxionality at high μ_H, whereas on γ-Al₂O₃(100), the exact opposite occurs: Pt₈ clusters present one-layer 2D shapes at low μ_H and switch to compact 3D shapes under high μ_H, during which the Pt₈ cluster preserves moderate fluxionality. Further analysis reveals a similar Pt-Pt bond length increase when switching from low μ_H to high μ_H on both surfaces although morphological transformations are different. Electronic structure analysis shows the existence of bonding interactions between Pt and Lewis acidic Al³⁺ sites along with the Pt-O interaction, which implies the necessity to include Al neighbors to discuss the electronic structure of small Pt clusters.

Dynamics of Subnanometer Pt Clusters Can Break the Scaling Relationships in Catalysis

Scaling relationships in catalysis impose fundamental limitations on the catalyst maximal performance; therefore, there is a continuous hunt for ways of circumventing them. We show that, at the subnano-scale, scaling relationships can be broken through catalyst dynamics. Oxygen reduction reaction (ORR), which can be catalyzed by Pt nanoparticles, is used as our study case. Subnanometer gas-phase and graphene-deposited Pt _n cluster catalysts are shown to exhibit poor correlation between binding energies of the intermediates, O, OH, and OOH, involved in the scaling relationships for ORR. The effect is due to the highly fluxional behavior of subnanometer clusters, which easily adapt their structures to the bound adsorbates and varying coverage and in some cases even reshape the structure upon changing environment. This fluxional behavior is also commonplace for clusters and contrasts them to extended surfaces, suggesting that breaking scaling relationships is likely a rule more than an exception in nanocluster catalysis.

Combined Automated Reaction Pathway Searches and Sparse Modeling Analysis for Catalytic Properties of Lowest Energy Twins of Cu13

In nanocatalysis, growing attention has recently been given to investigation of energetically low-lying structural isomers of atomic clusters, because some isomers can demonstrate better catalytic activity than the most stable structures. In this study, we present a comparative investigation of catalytic activity for NO dissociation of a pair of the energetically degenerated isomers of Cu₁₃ cluster having C₂ and C _s symmetries. It is shown that although these isomers have similar structural, electronic, and optical properties, they can possess very different catalytic activities. The effect of isomerization between cluster isomers is considered using state-of-the-art automated reaction pathway search techniques such as an artificial force induced reaction (AFIR) method as a part of a global reaction route mapping (GRRM) strategy. This method allows effectively to locate a large number of possible reaction pathways and transition states (TSs). In total, 12 TSs for NO dissociation were obtained for Cu₁₃, of C₂, C _s, as well as I _h isomers. Sparse modeling analysis shows that LUMO is strongly negatively correlated with total energy of TSs. For most TSs, LUMO has the antibonding character of NO, consisting of the interaction between π* of NO and SOMO of Cu₁₃. Therefore, an increase in the strength of interaction between NO molecule and Cu₁₃ cluster causes the rise in energy of the LUMO, resulting in lowering of the TS energy for NO dissociation. The combination of the automated reaction pathway search technique and sparse modeling represents a powerful tool for analysis and prediction of the physicochemical properties of atomic clusters, especially in the regime of structural fluxionality, where traditional methods based on random geometry search analyses are difficult.

Dynamic Phase Diagram of Catalytic Surface of Hexagonal Boron Nitride under Conditions of Oxidative Dehydrogenation of Propane

Partially oxidized surfaces of hexagonal boron nitride (hBN) and several metal borides are unexpectedly excellent catalysts for oxidative dehydrogenation of alkanes to olefins, but the nature of the active site(s) on these B-containing interfaces remains elusive. We characterize the surface of the partially oxidized B-rich hBN surface under reaction conditions from first principles. The interface has thermal access to multiple different stoichiometries and multiple structures of each stoichiometry. The size of the thermal ensemble is composition-dependent. The phase diagram of the interface constructed on the basis of the statistical ensembles of many accessible states is very different from the one based on global minima. Phase boundaries shift and blur, and phases consist of several stoichiometries and structures. The BO layer transiently exposes the reactive -B═O motifs in the metastable states. The fluxionality and structural diversity emerging under reaction conditions must be taken into account in theoretically descriptions of the catalytic interface.