Importance of Site Diversity and Connectivity in Electrochemical CO Reduction on Cu

Electrochemical CO2 reduction on Cu is a promising approach to produce value-added chemicals using renewable feedstocks, yet various Cu preparations have led to differences in activity and selectivity toward single and multicarbon products. Here, we find, surprisingly, that the effective catalytic activity toward ethylene improves when there is a larger fraction of less active sites acting as reservoirs of *CO on the surface of Cu nanoparticle electrocatalysts. In an adaptation of chemical transient kinetics to electrocatalysis, we measure the dynamic response of a gas diffusion electrode (GDE) cell when the feed gas is abruptly switched between Ar (inert) and CO. When switching from Ar to CO, CO reduction (COR) begins promptly, but when switching from CO to Ar, COR can be maintained for several seconds (delay time) despite the absence of the CO reactant in the gas phase. A three-site microkinetic model captures the observed dynamic behavior and shows that Cu catalysts exhibiting delay times have a less active *CO reservoir that exhibits fast diffusion to active sites. The observed delay times and the estimated *CO reservoir sizes are affected by catalyst preparation, applied potential, and microenvironment (electrolyte cation identity, electrolyte pH, and CO partial pressure). Notably, we estimate that the *CO reservoir surface coverage can be as high as 88 ± 7% on oxide-derived Cu (OD-Cu) at high overpotentials (-1.52 V vs SHE) and this increases in reservoir coverage coincide with increased turnover frequencies to ethylene. We also estimate that *CO can travel substantial distances (up to 10s of nm) prior to desorption or reaction. It appears that active C-C coupling sites by themselves do not control selectivity to C2+ products in electrochemical COR; the supply of CO to those sites is also a crucial factor. More generally, the overall activity of Cu electrocatalysts cannot be approximated from linear combinations of individual site activities. Future designs must consider the diversity of the catalyst network and account for intersite transportation pathways.

Small, solubilized platinum nanocrystals consist of an ordered core surrounded by mobile surface atoms

In situ structures of Platinum (Pt) nanoparticles (NPs) can be determined with graphene liquid cell transmission electron microscopy. Atomic-scale three-dimensional structural information about their physiochemical properties in solution is critical for understanding their chemical function. We here analyze eight atomic-resolution maps of small (<3 nm) colloidal Pt NPs. Their structures are composed of an ordered crystalline core surrounded by surface atoms with comparatively high mobility. 3D reconstructions calculated from cumulative doses of 8500 and 17,000 electrons/pixel, respectively, are characterized in terms of loss of atomic densities and atomic displacements. Less than 5% of the total number of atoms are lost due to dissolution or knock-on damage in five of the structures analyzed, whereas 10-16% are lost in the remaining three. Less than 5% of the atomic positions are displaced due to the increased electron irradiation in all structures. The surface dynamics will play a critical role in the diverse catalytic function of Pt NPs and must be considered in efforts to model Pt NP function computationally.

Structural transformations in Cu, Ag, and Au metal nanoclusters

Finite-temperature structures of Cu, Ag, and Au metal nanoclusters are calculated in the entire temperature range from 0 K to melting using a computational methodology that we proposed recently [M. Settem et al., Nanoscale 14, 939 (2022)]. In this method, Harmonic Superposition Approximation (HSA) and Parallel Tempering Molecular Dynamics (PTMD) are combined in a complementary manner. HSA is accurate at low temperatures and fails at higher temperatures. PTMD, on the other hand, effectively samples the high temperature region and melts. This method is used to study the size- and system-dependent competition between various structural motifs of Cu, Ag, and Au nanoclusters in the size range 1-2 nm. Results show that there are mainly three types of structural changes in metal nanoclusters, depending on whether a solid-solid transformation occurs. In the first type, the global minimum is the dominant motif in the entire temperature range. In contrast, when a solid-solid transformation occurs, the global minimum transforms either completely to a different motif or partially, resulting in the co-existence of multiple motifs. Finally, nanocluster structures are analyzed to highlight the system-specific differences across the three metals.

Reactivity of Single-Atom Alloy Nanoparticles: Modeling the Dehydrogenation of Propane

Physical catalysts often have multiple sites where reactions can take place. One prominent example is single-atom alloys, where the reactive dopant atoms can preferentially locate in the bulk or at different sites on the surface of the nanoparticle. However, ab initio modeling of catalysts usually only considers one site of the catalyst, neglecting the effects of multiple sites. Here, nanoparticles of copper doped with single-atom rhodium or palladium are modeled for the dehydrogenation of propane. Single-atom alloy nanoparticles are simulated at 400-600 K, using machine learning potentials trained on density functional theory calculations, and then the occupation of different single-atom active sites is identified using a similarity kernel. Further, the turnover frequency for all possible sites is calculated for propane dehydrogenation to propene through microkinetic modeling using density functional theory calculations. The total turnover frequencies of the whole nanoparticle are then described from both the population and the individual turnover frequency of each site. Under operating conditions, rhodium as a dopant is found to almost exclusively occupy (111) surface sites while palladium as a dopant occupies a greater variety of facets. Undercoordinated dopant surface sites are found to tend to be more reactive for propane dehydrogenation compared to the (111) surface. It is found that considering the dynamics of the single-atom alloy nanoparticle has a profound effect on the calculated catalytic activity of single-atom alloys by several orders of magnitude.

Imaging Interface and Particle Size Effects by In Situ Correlative Microscopy of a Catalytic Reaction

The catalytic behavior of Rh particles supported by three different materials (Rh, Au, and ZrO₂) in H₂ oxidation has been studied in situ by correlative photoemission electron microscopy (PEEM) and scanning photoemission electron microscopy (SPEM). Kinetic transitions between the inactive and active steady states were monitored, and self-sustaining oscillations on supported Rh particles were observed. Catalytic performance differed depending on the support and Rh particle size. Oscillations varied from particle size-independent (Rh/Rh) via size-dependent (Rh/ZrO₂) to fully inhibited (Rh/Au). For Rh/Au, the formation of a surface alloy induced such effects, whereas for Rh/ZrO₂, the formation of substoichiometric Zr oxides on the Rh surface, enhanced oxygen bonding, Rh-oxidation, and hydrogen spillover onto the ZrO₂ support were held responsible. The experimental observations were complemented by micro-kinetic simulations, based on variations of hydrogen adsorption and oxygen binding. The results demonstrate how correlative in situ surface microscopy enables linking of the local structure, composition, and catalytic performance.

Bimetallic Sites for Catalysis: From Binuclear Metal Sites to Bimetallic Nanoclusters and Nanoparticles

Heterogeneous bimetallic catalysts have broad applications in industrial processes, but achieving a fundamental understanding on the nature of the active sites in bimetallic catalysts at the atomic and molecular level is very challenging due to the structural complexity of the bimetallic catalysts. Comparing the structural features and the catalytic performances of different bimetallic entities will favor the formation of a unified understanding of the structure-reactivity relationships in heterogeneous bimetallic catalysts and thereby facilitate the upgrading of the current bimetallic catalysts. In this review, we will discuss the geometric and electronic structures of three representative types of bimetallic catalysts (bimetallic binuclear sites, bimetallic nanoclusters, and nanoparticles) and then summarize the synthesis methodologies and characterization techniques for different bimetallic entities, with emphasis on the recent progress made in the past decade. The catalytic applications of supported bimetallic binuclear sites, bimetallic nanoclusters, and nanoparticles for a series of important reactions are discussed. Finally, we will discuss the future research directions of catalysis based on supported bimetallic catalysts and, more generally, the prospective developments of heterogeneous catalysis in both fundamental research and practical applications.

Development of nanoparticle bulk morphology analysis: a multidomain XRD approach

The appearance of twin/stacking faults in nanoparticles creates strains affecting the catalytic, optical, and electrical properties of nanomaterials. Currently, there is a lack of experimental tools for a numeric characterization of these defects in samples. Therefore, many structure-property correlations are poorly understood. Here, we report the exploration of the twinning effect on the XRD pattern and its practical application. We developed a new approach focused on the special mutual orientation of periodic fcc segments, domains. Using computational simulations, we found that the more domains, the smaller the height ratio of 220 to 111 diffraction peaks. Knowing this correlation, we performed the XRD bulk morphology and size analysis of Au and AuPt samples. The obtained results were compared with the results of TEM and SAXS analyses. In a broader context, our multidomain XRD method is a simple alternative to TEM which enables unraveling the structure-property correlations in NP studies.

Identifying the morphology of Pt nanoparticles for the optimal catalytic activity towards CO oxidation

The morphology of nanoparticles (NPs) is crucial for determining their catalytic performance. The dramatic changes in the morphology of metal NPs during reactions observed in many in situ experiments pose great challenges for the identification of the geometry for optimal catalytic activities, which arouses the controversial understanding of the reaction mechanism. In this work, taking CO oxidation as a model reaction, we coupled a multiscale structure reconstruction model with kinetic Monte Carlo simulations to study the catalytic performance of the Pt NPs with changing morphology and reaction conditions. Through the quantitative analysis of contour plots for turnover frequencies, we show that the NPs with more well-coordinated sites exhibit optimal activity under CO-rich conditions at higher temperatures, while the reactivity of NPs with more low-coordination sites is optimal under O₂-rich conditions at lower temperatures. Further analysis indicates that the competitive adsorption of CO and O₂ plays the key role, in which the structure with optimal activity has a closer CO and O coverage. This work not only reconciles the controversy of the active geometry in the experiments, but offers an efficient method to guide the rational design of high-performance catalysts.

Kinetic Monte Carlo simulations for heterogeneous catalysis: Fundamentals, current status, and challenges

Kinetic Monte Carlo (KMC) simulations in combination with first-principles (1p)-based calculations are rapidly becoming the gold-standard computational framework for bridging the gap between the wide range of length scales and time scales over which heterogeneous catalysis unfolds. 1p-KMC simulations provide accurate insights into reactions over surfaces, a vital step toward the rational design of novel catalysts. In this Perspective, we briefly outline basic principles, computational challenges, successful applications, as well as future directions and opportunities of this promising and ever more popular kinetic modeling approach.

Structure-Reactivity Relationship for Nano-Catalysts in the Hydrogenation/Dehydrogenation Controlled Reaction Systems

For the activity of a nano-catalyst, a general and quantitative solution to building direct structure-reactivity relationship has not yet been established. On top of the first-principle-based kinetic Monte Carlo (KMC) simulations, we developed a model to build the adsorption site dependence of the activity. We applied this model to study the nano effects of Cu catalysts in the water-gas shift reaction. By accumulating the activities of different adsorption sites, our model satisfactorily reproduced the experimental apparent activation energies for catalysts with sizes over hundreds of nanometers, which were out of reach for conventional KMC simulations. Our results disclose that, even for a cubic catalyst with size of 877 nm, its activity can still be closely related to the activity of edge sites, instead of only the exposed Cu(100) facets as might be expected. The present model is expected to be useful for systems that are controlled by the hydrogenation/dehydrogenation processes.

Dynamic Microkinetic Modeling for Heterogeneously Catalyzed Hydrogenation Reactions: a Coverage-Oriented View

In most studies, the microkinetics for multistep reactions are numerically solved due to their complexity; the obtained numerical results are only valid under given reaction conditions at a static point. In this work, the microkinetics of heterogeneously catalyzed hydrogenation reactions are analytically solved as a function of three coupled physical parameters, which are energy, reaction rate, and coverage. The results correlate the surface reactions and the gaseous-phased reactant/product by energy and thus provide a dynamic view over the whole reaction process rather than at a static point. The analytical expressions are given for a simple hydrogenation reaction and three more complicated hypothetical hydrogenation reactions with side products, side reaction paths, or even multiple active sites. Compared with the numerical solution, the analytical solution is valid under all reaction conditions in practice and can provide more guidance to optimize the overall outcome or catalyst development.

The origin of the particle-size-dependent selectivity in 1-butene isomerization and hydrogenation on Pd/Al2O3 catalysts

The selectivity of 1-butene hydrogenation/isomerization on Pd catalysts is known to be particle size dependent. Here we show that combining well-defined model catalysts, atmospheric pressure reaction kinetics, DFT calculations and microkinetic modeling enables to rationalize the particle size effect based on the abundance and the specific properties of the contributing surface facets.

Reduced Carbon Monoxide Saturation Coverage on Vicinal Palladium Surfaces: the Importance of the Adsorption Site

Steps at metal surfaces may influence energetics and kinetics of catalytic reactions in unexpected ways. Here, we report a significant reduction of the CO saturation coverage in Pd vicinal surfaces, which in turn is relevant for the light-off of the CO oxidation reaction. The study is based on a systematic investigation of CO adsorption on vicinal Pd(111) surfaces making use of a curved Pd crystal. A combined X-ray Photoelectron Spectroscopy and DFT analysis allows us to demonstrate that an entire row of atomic sites under Pd steps remains free of CO upon saturation at 300 K, leading to a step-density-dependent reduction of CO coverage that correlates with the observed decrease of the light-off temperature during CO oxidation in vicinal Pd surfaces.

Single alloy nanoparticle x-ray imaging during a catalytic reaction

The imaging of active nanoparticles represents a milestone in decoding heterogeneous catalysts’ dynamics. We report the facet-resolved, surface strain state of a single PtRh alloy nanoparticle on SrTiO3 determined by coherent x-ray diffraction imaging under catalytic reaction conditions. Density functional theory calculations allow us to correlate the facet surface strain state to its reaction environment–dependent chemical composition. We find that the initially Pt-terminated nanoparticle surface gets Rh-enriched under CO oxidation reaction conditions. The local composition is facet orientation dependent, and the Rh enrichment is nonreversible under subsequent CO reduction. Tracking facet-resolved strain and composition under operando conditions is crucial for a rational design of more efficient heterogeneous catalysts with tailored activity, selectivity, and lifetime.

Shedding Light on CO Oxidation Surface Chemistry on Single Pt Catalyst Nanoparticles Inside a Nanofluidic Model Pore

Investigating a catalyst under relevant application conditions is experimentally challenging and parameters like reaction conditions in terms of temperature, pressure, and reactant mixing ratios, as well as catalyst design, may significantly impact the obtained experimental results. For Pt catalysts widely used for the oxidation of carbon monoxide, there is keen debate on the oxidation state of the surface at high temperatures and at/above atmospheric pressure, as well as on the most active surface state under these conditions. Here, we employ a nanoreactor in combination with single-particle plasmonic nanospectroscopy to investigate individual Pt catalyst nanoparticles localized inside a nanofluidic model pore during carbon monoxide oxidation at 2 bar in the 450-550 K temperature range. As a main finding, we demonstrate that our single-particle measurements effectively resolve a kinetic phase transition during the reaction and that each individual particle has a unique response. Based on spatially resolved measurements, we furthermore observe how reactant concentration gradients formed due to conversion inside the model pore give rise to position-dependent kinetic phase transitions of the individual particles. Finally, employing extensive electrodynamics simulations, we unravel the surface chemistry of the individual Pt nanoparticles as a function of reactant composition and find strongly temperature-dependent Pt-oxide formation and oxygen spillover to the SiO2 support as the main processes. These results therefore support the existence of a Pt surface oxide in the regime of high catalyst activity and demonstrate the possibility to use plasmonic nanospectroscopy in combination with nanofluidics as a tool for in situ studies of individual catalyst particles.

High energy surface x-ray diffraction applied to model catalyst surfaces at work

Catalysts are materials that accelerate the rate of a desired chemical reaction. As such, they constitute an integral part in many applications ranging from the production of fine chemicals in chemical industry to exhaust gas treatment in vehicles. Accordingly, it is of utmost economic interest to improve catalyst efficiency and performance, which requires an understanding of the interplay between the catalyst structure, the gas phase and the catalytic activity under realistic reaction conditions at ambient pressures and elevated temperatures. In recent years efforts have been made to increasingly develop techniques that allow for investigating model catalyst samples under conditions closer to those of real technical catalysts. One of these techniques is high energy surface x-ray diffraction (HESXRD), which uses x-rays with photon energies typically in the range of 70-80 keV. HESXRD allows a fast data collection of three dimensional reciprocal space for the structure determination of model catalyst samples under operando conditions and has since been used for the investigation of an increasing number of different model catalysts. In this article we will review general considerations of HESXRD including its working principle for different model catalyst samples and the experimental equipment required. An overview over HESXRD investigations performed in recent years will be given, and the advantages of HESXRD with respect to its application to different model catalyst samples will be presented. Moreover, the combination of HESXRD with other operando techniques such as in situ mass spectrometry, planar laser-induced fluorescence and surface optical reflectance will be discussed. The article will close with an outlook on future perspectives and applications of HESXRD.

Correlating 3D Surface Atomic Structure and Catalytic Activities of Pt Nanocrystals

Active sites and catalytic activity of heterogeneous catalysts is determined by their surface atomic structures. However, probing the surface structure at an atomic resolution is difficult, especially for solution ensembles of catalytic nanocrystals, which consist of heterogeneous particles with irregular shapes and surfaces. Here, we constructed 3D maps of the coordination number (CN) and generalized CN (CN_) for individual surface atoms of sub-3 nm Pt nanocrystals. Our results reveal that the synthesized Pt nanocrystals are enclosed by islands of atoms with nonuniform shapes that lead to complex surface structures, including a high ratio of low-coordination surface atoms, reduced domain size of low-index facets, and various types of exposed high-index facets. 3D maps of CN_ are directly correlated to catalytic activities assigned to individual surface atoms with distinct local coordination structures, which explains the origin of high catalytic performance of small Pt nanocrystals in important reactions such as oxygen reduction reactions and CO electro-oxidation.

Interplay between CO Disproportionation and Oxidation: On the Origin of the CO Reaction Onset on Atomic Layer Deposition-Grown Pt/ZrO2 Model Catalysts

Pt/ZrO₂ model catalysts were prepared by atomic layer deposition (ALD) and examined at mbar pressure by operando sum frequency generation (SFG) spectroscopy and near-ambient pressure X-ray photoelectron spectroscopy (NAP-XPS) combined with differentially pumped mass spectrometry (MS). ALD enables creating model systems ranging from Pt nanoparticles to bulk-like thin films. Polarization-dependent SFG of CO adsorption reveals both the adsorption configuration and the Pt particle morphology. By combining experimental data with ab initio density functional theory (DFT) calculations, we show that the CO reaction onset is determined by a delicate balance between CO disproportionation (Boudouard reaction) and oxidation. CO disproportionation occurs on low-coordinated Pt sites, but only at high CO coverages and when the remaining C atom is stabilized by a favorable coordination. Thus, under the current conditions, initial CO oxidation is found to be strongly influenced by the removal of carbon deposits formed through disproportionation mechanisms rather than being determined by the CO and oxygen inherent activity. Accordingly, at variance with the general expectation, rough Pt nanoparticles are seemingly less active than smoother Pt films. The applied approach enables bridging both the “materials and pressure gaps”.

Computational Methods in Heterogeneous Catalysis

The unprecedented ability of computations to probe atomic-level details of catalytic systems holds immense promise for the fundamentals-based bottom-up design of novel heterogeneous catalysts, which are at the heart of the chemical and energy sectors of industry. Here, we critically analyze recent advances in computational heterogeneous catalysis. First, we will survey the progress in electronic structure methods and atomistic catalyst models employed, which have enabled the catalysis community to build increasingly intricate, realistic, and accurate models of the active sites of supported transition-metal catalysts. We then review developments in microkinetic modeling, specifically mean-field microkinetic models and kinetic Monte Carlo simulations, which bridge the gap between nanoscale computational insights and macroscale experimental kinetics data with increasing fidelity. We finally review the advancements in theoretical methods for accelerating catalyst design and discovery. Throughout the review, we provide ample examples of applications, discuss remaining challenges, and provide our outlook for the near future.

Structure-Dependent Strain Effects

Density functional theory calculations of atomic and molecular adsorption on (111) and (100) metal surfaces reveal marked surface and structure dependent effects of strain. Adsorption in three-fold hollow sites is found to be destabilized by compressive strain whereas the reversed trend is commonly valid for adsorption in four-fold sites. The effects, which are qualitatively explained using a simple two-orbital model, provide insights on how to modify chemical properties by strain design.

Copper catalysis at operando conditions-bridging the gap between single nanoparticle probing and catalyst-bed-averaging

In catalysis, nanoparticles enable chemical transformations and their structural and chemical fingerprints control activity. To develop understanding of such fingerprints, methods studying catalysts at realistic conditions have proven instrumental. Normally, these methods either probe the catalyst bed with low spatial resolution, thereby averaging out single particle characteristics, or probe an extremely small fraction only, thereby effectively ignoring most of the catalyst. Here, we bridge the gap between these two extremes by introducing highly multiplexed single particle plasmonic nanoimaging of model catalyst beds comprising 1000 nanoparticles, which are integrated in a nanoreactor platform that enables online mass spectroscopy activity measurements. Using the example of CO oxidation over Cu, we reveal how highly local spatial variations in catalyst state dynamics are responsible for contradicting information about catalyst active phase found in the literature, and identify that both surface and bulk oxidation state of a Cu nanoparticle catalyst dynamically mediate its activity.

Predicting metal-metal interactions. II. Accelerating generalized schemes through physical insights

Operando-computational frameworks that integrate descriptors for catalyst stability within catalyst screening paradigms enable predictions of rates and selectivity on chemically faithful representations of nanoparticles under reaction conditions. These catalyst stability descriptors can be efficiently predicted by density functional theory (DFT)-based models. The alloy stability model, for example, predicts the stability of metal atoms in nanoparticles with site-by-site resolution. Herein, we use physical insights to present accelerated approaches of parameterizing this recently introduced alloy-stability model. These accelerated approaches meld quadratic functions for the energy of metal atoms in terms of the coordination number with linear correlations between model parameters and the cohesive energies of bulk metals. By interpolating across both the coordination number and chemical space, these accelerated approaches shrink the training set size for 12 fcc p- and d-block metals from 204 to as few as 24 DFT calculated total energies without sacrificing the accuracy of our model. We validate the accelerated approaches by predicting adsorption energies of metal atoms on extended surfaces and 147 atom cuboctahedral nanoparticles with mean absolute errors of 0.10 eV and 0.24 eV, respectively. This efficiency boost will enable a rapid and exhaustive exploration of the vast material space of transition metal alloys for catalytic applications.

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.

Understanding supported noble metal catalysts using first-principles calculations

Heterogeneous catalysis on supported and nonsupported nanoparticles is of fundamental importance in the energy and chemical conversion industries. Rather than laboratory analysis, first-principles calculations give us an atomic-level understanding of the structure and reactivity of nanoparticles and supports, greatly reducing the efforts of screening and design. However, unlike catalysis on low index single crystalline surfaces, nanoparticle catalysis relies on the tandem properties of a support material as well as the metal cluster itself, often with charge transfer processes being of key importance. In this perspective, we examine current state-of-the-art quantum-chemical research for the modeling of reactions that utilize small transition metal clusters on metal oxide supports. This should provide readers with useful insights when dealing with chemical reactions on such systems, before discussing the possibilities and challenges in the field.

Predicting Adsorption Properties of Catalytic Descriptors on Bimetallic Nanoalloys with Site-Specific Precision

Bimetallic nanoparticles present a vastly tunable structural and compositional design space rendering them promising materials for catalytic and energy applications. Yet it remains an enduring challenge to efficiently screen candidate alloys with atomic level specificity while explicitly accounting for their inherent stabilities under reaction conditions. Herein, by leveraging correlations between binding energies of metal adsorption sites and metal-adsorbate complexes, we predict adsorption energies of typical catalytic descriptors (OH*, CH₃*, CH*, and CO*) on bimetallic alloys with site-specific resolution. We demonstrate that our approach predicts adsorption energies on top and bridge sites of bimetallic nanoparticles having generic morphologies and chemical environments with errors between 0.09 and 0.18 eV. By forging a link between the inherent stability of an alloy and the adsorption properties of catalytic descriptors, we can now identify active site motifs in nanoalloys that possess targeted catalytic descriptor values while being thermodynamically stable under working conditions.

Surface and interface design for heterogeneous catalysis

Recent progresses in catalytic nanocrystals with uniform and well-defined structures, in situ characterization techniques, and theoretical calculations are facilitating the innovation of efficient catalysts via surface and interface designs, including crystal phase design, morphology/facet design, and size design, followed by controlled synthesis.

Influence of atomic site-specific strain on catalytic activity of supported nanoparticles

Heterogeneous catalysis is an enabling technology that utilises transition metal nanoparticles (NPs) supported on oxides to promote chemical reactions. Structural mismatch at the NP–support interface generates lattice strain that could affect catalytic properties. However, detailed knowledge about strain in supported NPs remains elusive. We experimentally measure the strain at interfaces, surfaces and defects in Pt NPs supported on alumina and ceria with atomic resolution using high-precision scanning transmission electron microscopy. The largest strains are observed at the interfaces and are predominantly compressive. Atomic models of Pt NPs with experimentally measured strain distributions are used for first-principles kinetic Monte Carlo simulations of the CO oxidation reaction. The presence of only a fraction of strained surface atoms is found to affect the turnover frequency. These results provide a quantitative understanding of the relationship between strain and catalytic function and demonstrate that strain engineering can potentially be used for catalyst design.

Detailed knowledge of how strain influences catalytic reactions remains elusive. Here, the authors experimentally measure the strain in supported Pt nanoparticles on alumina and ceria with atomic resolution and computationally explore how the strain affects the CO oxidation reaction.