Transition Metal Carbides as Supports for Catalytic Metal Particles: Recent Progress and Opportunities.

Transition metal carbides (TMCs) constitute excellent alternatives to traditional oxide-based supports for small metal particles, leading to strong metal-support interactions, which drastically modify the catalytic properties of the supported metal atoms. Moreover, they possess extremely high melting points and good resistance to carbon deposition and sulfur poisoning, and the catalytic activities of some TMCs per se have been shown to be similar to those of Pt-group metals for a considerable number of reactions. Therefore, the use of TMCs as supports can give rise to bifunctional catalysts with multiple active sites. However, at present, only TiC and MoxC have been tested experimentally as supports for metal particles, and it is largely unclear which combinations may best catalyze which chemical reactions. In this Perspective, we review the most significant works on the use of TMCs as supports for catalytic applications, assess the current status of the field, and identify key advances being made and challenges, with an eye to the future.

Ten-electron count rule for the binding of adsorbates on single-atom alloy catalysts.

Single-atom alloys have recently emerged as highly active and selective alloy catalysts. Unlike pure metals, single-atom alloys escape the well-established conceptual framework developed nearly three decades ago for predicting catalytic performance. Although this offers the opportunity to explore so far unattainable chemistries, this leaves us without a simple guide for the design of single-atom alloys able to catalyse targeted reactions. Here, based on thousands of density functional theory calculations, we reveal a 10-electron count rule for the binding of adsorbates on the dopant atoms, usually the active sites, of single-atom alloy surfaces. A simple molecular orbital approach rationalizes this rule and the nature of the adsorbate-dopant interaction. In addition, our intuitive model can accelerate the rational design of single-atom alloy catalysts. Indeed, we illustrate how the unique insights provided by the electron count rule help identify the most promising dopant for an industrially relevant hydrogenation reaction, thereby reducing the number of potential materials by more than one order of magnitude.

Elucidating the Reactivity of Oxygenates on Single-Atom Alloy Catalysts.

Doping isolated transition metal atoms into the surface of coinage-metal hosts to form single-atom alloys (SAAs) can significantly improve the catalytic activity and selectivity of their monometallic counterparts. These atomically dispersed dopant metals on the SAA surface act as highly active sites for various bond coupling and activation reactions. In this study, we investigate the catalytic properties of SAAs with different bimetallic combinations [Ni-, Pd-, Pt-, and Rh-doped Cu(111), Ag(111), and Au(111)] for chemistries involving oxygenates relevant to biomass reforming. Density functional theory is employed to calculate and compare the formation energies of species such as methoxy (CH3O), methanol (CH3OH), and hydroxymethyl (CH2OH), thereby understanding the stability of these adsorbates on SAAs. Activation energies and reaction energies of C-O coupling, C-H activation, and O-H activation on these oxygenates are then computed. Analysis of the data in terms of thermochemical linear scaling and BroÌ·nsted-Evans-Polanyi relationship shows that some SAAs have the potential to combine weak binding with low activation energies, thereby exhibiting enhanced catalytic behavior over their monometallic counterparts for key elementary steps of oxygenate conversion. This work contributes to the discovery and development of SAA catalysts toward greener technologies, having potential applications in the transition from fossil to renewable fuels and chemicals.

Investigating Spillover Energy as a Descriptor for Single-Atom Alloy Catalyst Design.

The identification of thermodynamic descriptors of catalytic performance is essential for the rational design of heterogeneous catalysts. Here, we investigate how spillover energy, a descriptor quantifying whether intermediates are more stable at the dopant or host metal sites, can be used to design single-atom alloys (SAAs) for formic acid dehydrogenation. Using theoretical calculations, we identify NiCu as a SAA with favorable spillover energy and demonstrate that formate intermediates produced after the initial O-H activation are more stable at Ni sites where rate-determining C-H activation occurs. Surface science experiments demonstrated that NiCu(111) SAAs are more reactive than Cu(111) while they still follow the formate reaction pathway. However, reactor studies of silica-supported NiCu SAA nanoparticles showed only a modest improvement over Cu resulting from surface coverage effects. Overall, this study demonstrates the potential of engineering SAAs using spillover energy as a design parameter and highlights the importance of adsorbate-adsorbate interactions under steady-state operation.

Speeding up the Detection of Adsorbate Lateral Interactions in Graph-Theoretical Kinetic Monte Carlo Simulations.

Kinetic Monte Carlo (KMC) has become an indispensable tool in heterogeneous catalyst discovery, but realistic simulations remain computationally demanding on account of the need to capture complex and long-range lateral interactions between adsorbates. The Zacros software package (https://zacros.org) adopts a graph-theoretical cluster expansion (CE) framework that allows such interactions to be computed with a high degree of generality and fidelity. This involves solving a series of subgraph isomorphism problems in order to identify relevant interaction patterns in the lattice. In an effort to reduce the computational burden, we have adapted two well-known subgraph isomorphism algorithms, namely, VF2 and RI, for use in KMC simulations and implemented them in Zacros. To benchmark their performance, we simulate a previously established model of catalytic NO oxidation, treating the O* lateral interactions with a series of progressively larger CEs. For CEs with long-range interactions, VF2 and RI are found to provide impressive speedups relative to simpler algorithms. RI performs best, giving speedups reaching more than 150× when combined with OpenMP parallelization. We also simulate a recently developed methane cracking model, showing that RI offers significant improvements in performance at high surface coverages.

Stochastic Cellular Automata Modeling of CO2 Hydrate Growth and Morphology.

Carbon dioxide (CO2) hydrates are important in a diverse range of applications and technologies in the environmental and energy fields. The development of such technologies relies on fundamental understanding, which necessitates not only experimental but also computational studies of the growth behavior of CO2 hydrates and the factors affecting their crystal morphology. As experimental observations show that the morphology of CO2 hydrate particles differs depending on growth conditions, a detailed understanding of the relation between the hydrate structure and growth conditions would be helpful. To this end, this work adopts a modeling approach based on hybrid probabilistic cellular automata to investigate variations in CO2 hydrate crystal morphology during hydrate growth from stagnant liquid water presaturated with CO2. The model, which uses free energy density profiles as inputs, correlates the variations in growth morphology to the system subcooling ΔT, i.e., the temperature deficiency from the triple CO2-hydrate-water equilibrium temperature under a given pressure, and properties of the growing hydrate-water interface, such as surface tension and curvature. The model predicts that when ΔT is large, parabolic needle-like or dendrite crystals emerge from planar fronts that deform and lose stability. In agreement with chemical diffusion-limited growth, the position of such planar fronts versus time follows a power law. In contrast, the tips of the emerging parabolic crystals steadily grow in proportion to time. The modeling framework is computationally fast and produces complex growth morphology phenomena under diffusion-controlled growth from simple, easy-to-implement rules, opening the way for employing it in multiscale modeling of gas hydrates.

Microscopic insights on clathrate hydrate growth from non-equilibrium molecular dynamics simulations.

Clathrate hydrates form and grow at interfaces. Understanding the relevant molecular processes is crucial for developing hydrate-based technologies. Many computational studies focus on hydrate growth within the aqueous phase using the 'direct coexistence method', which is limited in its ability to investigate hydrate film growth at hydrocarbon-water interfaces. To overcome this shortcoming, a new simulation setup is presented here, which allows us to study the growth of a methane hydrate nucleus in a system where oil-water, hydrate-water, and hydrate-oil interfaces are all simultaneously present, thereby mimicking experimental setups. Using this setup, hydrate growth is studied here under the influence of two additives, a polyvinylcaprolactam oligomer and sodium dodecyl sulfate, at varying concentrations. Our results confirm that hydrate films grow along the oil-water interface, in general agreement with visual experimental observations; growth, albeit slower, also occurs at the hydrate-water interface, the interface most often interrogated via simulations. The results obtained demonstrate that the additives present within curved interfaces control the solubility of methane in the aqueous phase, which correlates with hydrate growth rate. Building on our simulation insights, we suggest that by combining data for the potential of mean force profile for methane transport across the oil-water interface and for the average free energy required to perturb a flat interface, it is possible to predict the performance of additives used to control hydrate growth. These insights could be helpful to achieve optimal methane storage in hydrates, one of many applications which are attracting significant fundamental and applied interests.

Stability and reactivity of metal nanoclusters supported on transition metal carbides.

Small particles of transition metals (TM) supported on transition metal carbides (TMC) - TMn@TMC - provide a plethora of design opportunities for catalytic applications due to their highly exposed active centres, efficient atom utilisation and the physicochemical properties of the TMC support. To date, however, only a very small subset of TMn@TMC catalysts have been tested experimentally and it is unclear which combinations may best catalyse which chemical reactions. Herein, we develop a high-throughput screening approach to catalyst design for supported nanoclusters based on density functional theory, and apply it to elucidate the stability and catalytic performance of all possible combinations between 7 monometallic nanoclusters (Rh, Pd, Pt, Au, Co, Ni and Cu) and 11 stable support surfaces of TMCs with 1 : 1 stoichiometry (TiC, ZrC, HfC, VC, NbC, TaC, MoC and WC) towards CH4 and CO2 conversion technologies. We analyse the generated database to unravel trends or simple descriptors in their resistance towards metal aggregate formation and sintering, oxidation, stability in the presence of adsorbate species, and study their adsorptive and catalytic properties, to facilitate the discovery of novel materials in the future. We identify 8 TMn@TMC combinations as promising catalysts, all of them being new for experimental validation, thus expanding the chemical space for efficient conversion of CH4 and CO2.

Assessing the Impact of Adlayer Description Fidelity on Theoretical Predictions of Coking on Ni(111) at Steam Reforming Conditions.

Methane steam reforming is an important industrial process for hydrogen production, employing Ni as a low-cost, highly active catalyst, which, however, suffers from coking due to methane cracking. Coking is the accumulation of a stable poison over time, occurring at high temperatures; thus, to a first approximation, it can be treated as a thermodynamic problem. In this work, we developed an Ab initio kinetic Monte Carlo (KMC) model for methane cracking on Ni(111) at steam reforming conditions. The model captures C-H activation kinetics in detail, while graphene sheet formation is described at the level of thermodynamics, to obtain insights into the "terminal (poisoned) state" of graphene/coke within reasonable computational times. We used cluster expansions (CEs) of progressively higher fidelity to systematically assess the influence of effective cluster interactions between adsorbed or covalently bonded C and CH species on the "terminal state" morphology. Moreover, we compared the predictions of KMC models incorporating these CEs into mean-field microkinetic models in a consistent manner. The models show that the "terminal state" changes significantly with the level of fidelity of the CEs. Furthermore, high-fidelity simulations predict C-CH island/rings that are largely disconnected at low temperatures but completely encapsulate the Ni(111) surface at high temperatures.

Exact distributed kinetic Monte Carlo simulations for on-lattice chemical kinetics: lessons learnt from medium- and large-scale benchmarks.

Kinetic Monte Carlo (KMC) simulations have been instrumental in multiscale catalysis studies, enabling the elucidation of the complex dynamics of heterogeneous catalysts and the prediction of macroscopic performance metrics, such as activity and selectivity. However, the accessible length- and time-scales have been a limiting factor in such simulations. For instance, handling lattices containing millions of sites with 'traditional' sequential KMC implementations is prohibitive owing to large memory requirements and long simulation times. We have recently established an approach for exact, distributed, lattice-based simulations of catalytic kinetics which couples the Time-Warp algorithm with the Graph-Theoretical KMC framework, enabling the handling of complex adsorbate lateral interactions and reaction events within large lattices. In this work, we develop a lattice-based variant of the Brusselator system, a prototype chemical oscillator pioneered by Prigogine and Lefever in the late 60s, to benchmark and demonstrate our approach. This system can form spiral wave patterns, which would be computationally intractable with sequential KMC, while our distributed KMC approach can simulate such patterns 15 and 36 times faster with 625 and 1600 processors, respectively. The medium- and large-scale benchmarks thus conducted, demonstrate the robustness of the approach, and reveal computational bottlenecks that could be targeted in further development efforts. This article is part of a discussion meeting issue 'Supercomputing simulations of advanced materials'.

Large-scale benchmarks of the time-warp/graph-theoretical kinetic Monte Carlo approach for distributed on-lattice simulations of catalytic kinetics.

Motivated by the need to perform large-scale kinetic Monte Carlo (KMC) simulations, in the context of unravelling complex phenomena such as catalyst reconstruction and pattern formation, we extend the work of Ravipati et al. [S. Ravipati, G. D. Savva, I.-A. Christidi, R. Guichard, J. Nielsen, R. Réocreux and M. Stamatakis, Comput. Phys. Commun., 2022, 270, 108148] in benchmarking the performance of a distributed-computing, on-lattice KMC approach. The latter, implemented in our software package Zacros, combines the graph-theoretical KMC framework with the Time-Warp algorithm for parallel discrete event simulations, and entails dividing the lattice into subdomains, each assigned to a processor. The cornerstone of the Time-Warp algorithm is the state queue, to which snapshots of the simulation state are saved regularly, enabling historical KMC information to be corrected when conflicts occur at subdomain boundaries. Focusing on three model systems, we highlight the key Time-Warp parameters that can be tuned to optimise performance. The frequency of state saving, controlled by the state saving interval, δsnap, is shown to have the largest effect on performance, which favours balancing the overhead of re-simulating KMC history with that of writing state snapshots to memory. Also important is the global virtual time (GVT) computation interval, ΔτGVT, which has little direct effect on the progress of the simulation but controls how often the state queue memory can be freed up. We also find that pre-allocating memory for the state queue data structure favours performance. These findings will guide users in maximising the efficiency of Zacros or other distributed KMC software, which is a vital step towards realising accurate, meso-scale simulations of heterogeneous catalysis.

Wetting Properties of Clathrate Hydrates in the Presence of Polycyclic Aromatic Compounds: Evidence of Ion-Specific Effects.

Polycyclic aromatic hydrocarbons (PAHs) have attracted remarkable multidisciplinary attention due to their intriguing π-π stacking configurations, showing enormous opportunity for their use in a variety of advanced applications. To secure progress, detailed knowledge on PAHs' interfacial properties is required. Employing molecular dynamics, we probe the wetting properties of brine droplets (KCl, NaCl, and CaCl2) on sII methane-ethane hydrate surfaces immersed in various oil solvents. Our simulations show synergistic effects due to the presence of PAHs compounded by ion-specific effects. Our analysis reveals phenomenological correlations between the wetting properties and a combination of the binding free-energy difference and entropy changes upon oil solvation for PAHs at oil/brine and oil/hydrate interfaces. The detailed thermodynamic analysis conducted upon the interactions between PAHs and various interfaces identifies molecular-level mechanisms responsible for wettability alterations, which could be applicable for advancing applications in optics, microfluidics, biotechnology, medicine, as well as hydrate management.

Stick or Spill? Scaling Relationships for the Binding Energies of Adsorbates on Single-Atom Alloy Catalysts.

Single-atom alloy catalysts combine catalytically active metal atoms, present as dopants, with the selectivity of coinage metal hosts. Determining whether adsorbates stick at the dopant or spill over onto the host is key to understanding catalytic mechanisms on these materials. Despite a growing body of work, simple descriptors for the prediction of spillover energies (SOEs), i.e., the relative stability of an adsorbate on the dopant versus the host site, are not yet available. Using Density Functional Theory (DFT) calculations on a large set of adsorbates, we identify the dopant charge and the SOE of carbon as suitable descriptors. Combining them into a linear surrogate model, we can reproduce DFT-computed SOEs within 0.06 eV mean absolute error. More importantly, our work provides an intuitive theoretical framework, based on the concepts of electrostatic interactions and covalency, that explains SOE trends and can guide the rational design of future single-atom alloy catalysts.

Observation and Characterization of Dicarbonyls on a RhCu Single-Atom Alloy.

Dicarbonyl species are ubiquitous on Rh/oxide catalysts and are known to form on Rh+ centers. However, dicarbonyl species have never been directly observed on single-atom alloys (SAAs) where the active site is metallic. Herein, using surface science and theoretical modeling, we provide evidence of dicarbonyl species at isolated Rh sites on a RhCu(100) SAA. This approach not only enables us to directly visualize dicarbonyl species at Rh sites but also demonstrates that the transition between the mono- and dicarbonyl configuration can be achieved by changing surface temperature and CO pressure. Density functional theory calculations further support the mono- and dicarbonyl assignments and provide evidence that these species should be stable on other SAA combinations. Together, these results provide a picture of the structure and energetics of both the mono- and dicarbonyl configurations on the RhCu(100) SAA surface and should aid with IR assignments on SAA nanoparticle catalysts.

Quantum Tunnelling Driven H2 Formation on Graphene.

It is commonly believed that it is unfavorable for adsorbed H atoms on carbonaceous surfaces to form H2 without the help of incident H atoms. Using ring-polymer instanton theory to describe multidimensional tunnelling effects, combined with ab initio electronic structure calculations, we find that these quantum-mechanical simulations reveal a qualitatively different picture. Recombination of adsorbed H atoms, which was believed to be irrelevant at low temperature due to high barriers, is enabled by deep tunnelling, with reaction rates enhanced by tens of orders of magnitude. Furthermore, we identify a new path for H recombination that proceeds via multidimensional tunnelling but would have been predicted to be unfeasible by a simple one-dimensional description of the reaction. The results suggest that hydrogen molecule formation at low temperatures are rather fast processes that should not be ignored in experimental settings and natural environments with graphene, graphite, and other planar carbon segments.

One Decade of Computational Studies on Single-Atom Alloys: Is In Silico Design within Reach?

ConspectusSingle-Atom alloys (SAAs) are an emerging class of materials consisting of a coinage metal (Cu, Ag, and Au) doped, at the single-atom limit, with another metal. As catalysts, coinage metals are rarely very active on their own, but when they are, they exhibit high selectivity. On the other hand, transition metals are usually very active but not as selective. Incorporating transition metals (guest elements) into coinage metals (host material) is therefore appealing for combining the activity and selectivity of each constituent in a balanced way. Additionally, first-principles calculations have shown that single atoms embedded in the surface of a coinage metal can exhibit emergent properties. Here, we describe how computational studies based on density functional theory (DFT) and kinetic Monte Carlo (KMC) simulations, often undertaken in close collaboration with experimental research groups, have shaped, over the past decade, the way we understand SAA catalysis.This Account reviews our contributions in elucidating the stability of SAAs, their electronic structure, and the way adsorbates interact and react on SAA catalytic surfaces. By studying in detail the processes that affect the stability of the SAA phase, we have shown that out of several bimetallic combinations of coinage metals with prominent Pt-group metals only PtCu and PdCu are stable surface alloys under vacuum. However, more surface alloy structures are possible in the presence of adsorbates because the latter can stabilize, via strong binding, dopants in the surface of the material. More interestingly, a large number of these surface alloys are resistant to the aggregation of dopant atoms into clusters, thereby favoring the SAA structure. These major results from DFT calculations serve as a guide for experimentalists to explore new SAA catalysts. Further analysis has shown that SAAs have a unique electronic structure with a very sharp d-band feature close to the Fermi level, analogous to the electronic structure of molecular entities. This is one of the reasons that SAAs are particularly sought after: although they are metallic nanoparticles, they have properties akin to those of homogeneous catalysts. In this context, we have contributed extensive screening studies, focusing on molecular fragments of catalytic relevance on a range of SAAs, which have driven the identification of new catalysts. We have also explored the rich chemistry of two-adsorbate systems via kinetic modeling, demonstrating how a spectator species with greater affinity for the dopant can modulate the reactivity of the catalyst via the so-called (punctured) molecular cork effect.Since the first experimental characterization of SAAs about a decade ago, theoretical models have been able to support and explain various experimental observations. These models have served as benchmarks for assessing the predictive capability of the underlying theoretical methods. In turn, the predictions that have been delivered have guided and continue to guide the experimental research efforts in the field. These advancements show that the in silico design of new SAA catalysts is now within reach.

Surface morphology effects on clathrate hydrate wettability.

HYPOTHESIS: Clathrate hydrates preferentially form at interfaces; hence, wetting properties play an important role in their formation, growth, and agglomeration. Experimental evidence suggests that the hydrate preparation process can strongly affect contact angle measurements, leading to the different results reported in the literature. These differences hamper technological progress. We hypothesize that changes in hydrate surface morphologies are responsible for the wide variation of contact angles reported in the literature. EXPERIMENTS: Experimental testing of our hypothesis is problematic due to the preparation history of hydrates on their surface properties, and the difficulties in advanced surface characterization. Thus, we employ molecular dynamics simulations, which allow us to systematically change the interfacial features and the system composition. Implementing advanced algorithms, we quantify fundamental thermodynamic properties to validate our observations. FINDINGS: We achieve excellent agreement with experimental observations for both atomically smooth and rough hydrate surfaces. Our results suggest that contact line pinning forces, enhanced by surface heterogeneity, are accountable for altering water contact angles, thus explaining the differences among reported experimental data. Our analysis and molecular level insights help interpret adhesion force measurements and yield a better understanding of the agglomeration between hydrate particles, providing a microscopic tool for advancing flow assurance applications.

Periodic Trends in Adsorption Energies around Single-Atom Alloy Active Sites.

Single-atom alloys (SAAs) make up a special class of alloy surface catalysts that offer well-defined, isolated active sites in a more inert metal host. The dopant sites are generally assumed to have little or no influence on the properties of the host metal, and transport of chemical reactants and products to and from the dopant sites is generally assumed to be facile. Here, by performing density functional theory calculations and surface science experiments, we identify a new physical effect on SAA surfaces, whereby adsorption is destabilized by ≤300 meV on host sites within the perimeter of the reactive dopant site. We identify periodic trends for this behavior and demonstrate a zone of exclusion around the reactive sites for a range of adsorbates and combinations of host and dopant metals. Experiments confirm an increased barrier for diffusion of CO toward the dopant on a RhCu SAA. This effect offers new possibilities for understanding and designing active sites with tunable energetic landscapes surrounding them.

Correlating Antiagglomerant Performance with Gas Hydrate Cohesion.

Although inhibiting hydrate formation in hydrocarbon-water systems is paramount in preventing pipe blockage in hydrocarbon transport systems, the molecular mechanisms responsible for antiagglomerant (AA) performance are not completely understood. To better understand why macroscopic performance is affected by apparently small changes in the AA molecular structure, we perform molecular dynamics simulations. We quantify the cohesion energy between two gas hydrate nanoparticles dispersed in liquid hydrocarbons in the presence of different AAs, and we achieve excellent agreement against experimental data obtained at high pressure using the micromechanical force apparatus. This suggests that the proposed simulation approach could provide a screening method for predicting, in silico, the performance of new molecules designed to manage hydrates in flow assurance. Our results suggest that entropy and free energy of solvation of AAs, combined in some cases with the molecular orientation at hydrate-oil interfaces, are descriptors that could be used to predict performance, should the results presented here be reproduced for other systems as well. These insights could help speed up the design of new AAs and guide future experiments.

Mechanistic insights into carbon-carbon coupling on NiAu and PdAu single-atom alloys.

Carbon-carbon coupling is an important step in many catalytic reactions, and performing sp3-sp3 carbon-carbon coupling heterogeneously is particularly challenging. It has been reported that PdAu single-atom alloy (SAA) model catalytic surfaces are able to selectively couple methyl groups, producing ethane from methyl iodide. Herein, we extend this study to NiAu SAAs and find that Ni atoms in Au are active for C-I cleavage and selective sp3-sp3 carbon-carbon coupling to produce ethane. Furthermore, we perform ab initio kinetic Monte Carlo simulations that include the effect of the iodine atom, which was previously considered a bystander species. We find that model NiAu surfaces exhibit a similar chemistry to PdAu, but the reason for the similarity is due to the role the iodine atoms play in terms of blocking the Ni atom active sites. Specifically, on NiAu SAAs, the iodine atoms outcompete the methyl groups for occupancy of the Ni sites leaving the Me groups on Au, while on PdAu SAAs, the binding strengths of methyl groups and iodine atoms at the Pd atom active site are more similar. These simulations shed light on the mechanism of this important sp3-sp3 carbon-carbon coupling chemistry on SAAs. Furthermore, we discuss the effect of the iodine atoms on the reaction energetics and make an analogy between the effect of iodine as an active site blocker on this model heterogeneous catalyst and homogeneous catalysts in which ligands must detach in order for the active site to be accessed by the reactants.