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In acidic conditions, the electroreduction of CO or CO2 (noted CO(2)RR) on metal surfaces is conventionally hindered by intense competition with the hydrogen evolution reaction (HER). In this study, we present first-principles calculations of a mechanism wherein the formation of H-induced Cu adatoms on Cu(111) serves as a pivotal trigger for CORR in acidic environments. Through an analysis of the grand canonical surface state population, we elucidate that these newly formed adatoms create an array of active sites essential for both CO adsorption and subsequent reduction. Our ensemble-based kinetic models unveil the role of adatoms, enhancing the HER while simultaneously initiating CORR. Notably, the cumulative activity of the HER and CORR is contingent upon the combination of various surface states, with their individual contributions varying based on the electrode potential and pH. The interplay between surface state dynamics and electrochemical activity sheds new light on the potential-dependent nature of the active site and reaction kinetics governing CORR on Cu(111) in acidic media.

Abstract: Addressing sustainable energy storage remains crucial for transitioning to renewable sources. While Li‐ion batteries have made significant contributions, enhancing their capacity through alternative materials remains a key challenge. Micro‐sized silicon is a promising anode material due to its tenfold higher theoretical capacity compared to conventional graphite. However, its substantial volumetric expansion during cycling impedes practical application due to mechanical failure and rapid capacity fading. A novel approach is proposed to mitigate this issue by incorporating trace amounts of aluminum into the micro‐sized silicon electrode using ball milling. Density functional theory (DFT) is employed to establish a theoretical framework elucidating how grain boundary sliding, a key mechanism involved in preventing mechanical failure is facilitated by the presence of trace aluminum at grain boundaries. This, in turn, reduces stress accumulation within the material, reducing the likelihood of failure. To validate the theoretical predictions, capacity retention experiments are conducted on undoped and Al‐doped micro‐sized silicon samples. The results demonstrate significantly reduced capacity fading in the doped sample, corroborating the theoretical framework and showcasing the potential of aluminum doping for improved Li‐ion battery performance.

The growing concern over the escalating levels of anthropogenic CO2 emissions necessitates effective strategies for its conversion to valuable chemicals and fuels. In this research, we embark on a comprehensive investigation of the nature of zirconia on a copper inverse catalyst under the conditions of CO2 hydrogenation to methanol. We employ density functional theory calculations in combination with the Grand Canonical Basin Hopping method, enabling an exploration of the free energy surface including a variable amount of adsorbates within the relevant reaction conditions. Our focus centers on a model three-atom Zr cluster on a Cu(111) surface decorated with various OH, O, and formate ligands, noted Zr3Ox (OH)y (HCOO)z/Cu(111), revealing major changes in the active site induced by various reaction parameters such as the gas pressure, temperature, conversion levels, and CO2/H2 feed ratios. Through our analysis, we have unveiled insights into the dynamic behavior of the catalyst. Specifically, under reaction conditions, we observe a large number of composition and structures with similar free energy for the catalyst, with respect to changing the type, number, and binding sites of adsorbates, suggesting that the active site should be regarded as a statistical ensemble of diverse structures that interconvert.

Noble metals supported on reducible oxides, like CoOx and TiOx, exhibit superior activity in many chemical reactions, but the origin of the increased activity is not well understood. To answer this question we studied thin films of CoOx supported on an Au(111) single crystal surface as a model for the CO oxidation reaction. We show that three reaction regimes exist in response to chemical and topographic restructuring of the CoOx catalyst as a function of reactant gas phase CO/O2 stoichiometry and temperature. Under oxygen-lean conditions and moderate temperatures (≤150 °C), partially oxidized films (CoOx1) forms containing Co3+ species that are effective in a wide temperature range. Resonant photoemission spectroscopy (ResPES) revealed the unique role of Co3+ sites in catalyzing the CO oxidation. Density function theory (DFT) calculations provided deeper insights into the pathway and free energy barriers for the reactions on these oxide phases. These findings in this work highlight the versatility of catalysts and their evolution to form different active phases, both topological and chemically, in response to reaction conditions exposing a new paradigm in the catalyst structure during operation.

Despite the wide applications, the ab initio modeling of the ceria based catalyst is challenging. The partial occupation in the 4f orbitals creates a fundamental challenge for commonly used density functional theory (DFT) methods, including semilocal functionals with Hubbard U correction to force localization and hybrid functionals. In this work, we benchmark the random phase approximation (RPA) for ceria surface properties, including surface energy and hydrogenation energy, compared to the results utilizing the DFT + U approach or hybrid functionals. We show that, for the latter approaches, different surface properties require opposite directions of parameter tuning. This forms a dilemma for the parameter based DFT methods, as the improvement of a certain property by tuning parameters will inevitably lead to the worsening of other properties. Our results suggest that the parameter-free many-body perturbation theory methods exemplified by RPA are a promising strategy to escape the dilemma and provide highly accurate descriptions, which will allow us to better understand the catalytic reactions in ceria related systems.

Hydrazine-assisted water electrolysis offers a feasible path for low-voltage green hydrogen production. Herein, the design and synthesis of ultrathin RhRu0.5 -alloy wavy nanowires as bifunctional electrocatalysts for both the anodic hydrazine oxidation reaction (HzOR) and the cathodic hydrogen evolution reaction (HER) is reported. It is shown that the RhRu0.5 -alloy wavy nanowires can achieve complete electrooxidation of hydrazine with a low overpotential and high mass activity, as well as improved performance for the HER. The resulting RhRu0.5 bifunctional electrocatalysts enable, high performance hydrazine-assisted water electrolysis delivering a current density of 100 mA cm-2 at an ultralow cell voltage of 54 mV and a high current density of 853 mA cm-2 at a cell voltage of 0.6 V. The RhRu0.5  electrocatalysts further demonstrate a stable operation at a high current density of 100 mA cm-2 for 80 hours of testing period with little irreversible degradation. The overall performance greatly exceeds that of the previously reported hydrazine-assisted water electrolyzers, offering a pathway for efficiently converting hazardous hydrazine into molecular hydrogen.

As a showcase for experimentally accessible single-site catalysts, well-defined and characterized isolated Ir sites anchored on a covalent triazine framework (CTF) were investigated with computational methods.

We report the size-dependent activity and stability of supported Pt1,4,7,8 for electrocatalytic hydrogen evolution reaction, and show that clusters outperform polycrystalline Pt in activity, with size-dependent stability. To understand the size effects, we use DFT calculations to study the structural fluxionality under varying potentials. We show that the clusters can reshape under H coverage and populate an ensemble of states with diverse stoichiometry, structure, and thus reactivity. Both experiment and theory suggest that electrocatalytic species are hydridic states of the clusters (≈2 H/Pt). An ensemble-based kinetic model reproduces the experimental activity trend and reveals the role of metastable states. The stability trend is rationalized by chemical bonding analysis. Our joint study demonstrates the potential- and adsorbate-coverage-dependent fluxionality of subnano clusters of different sizes and offers a systematic modeling strategy to tackle the complexities.

Single-atom catalysts (SACs) have attracted attention for their high catalytic activity and selectivity, but the nature of their active sites under realistic reaction conditions, involving various ligands, is not well-understood. In this study, we use density functional theory calculations and grand canonical basin hopping to theoretically investigate the active site for the oxygen evolution reaction (OER) on a single Pt atom supported on indium tin oxide, including the influence of the electrochemical potential. We show that the ligands on the Pt atom change from Pt-OH in the absence of electrochemical potential to PtO(OH)4 in electrochemical conditions. This change of the chemical state of Pt is associated with a decrease of 0.3 V for the OER overpotential. This highlights the importance of accurately identifying the nature of the active site under reaction conditions and the impact of adsorbates on the electrocatalytic activity. This theoretical investigation enhances our understanding of SACs for the OER.

A combination of density functional theory (DFT) and experiments with atomically size-selected Ptn clusters deposited on indium-tin oxide (ITO) electrodes was used to examine the effects of applied potential and Ptn size on the electrocatalytic activity of Ptn (n = 1, 4, 7, and 8) for the hydrogen evolution reaction (HER). Activity is found to be negligible for isolated Pt atoms on ITO, increasing rapidly with Ptn size such that Pt7/ITO and Pt8/ITO have roughly double the activity per Pt atom compared to atoms in the surface layer of polycrystalline Pt. Both the DFT and experiment find that hydrogen under-potential deposition (Hupd) results in Ptn/ITO (n = 4, 7, and 8) adsorbing ∼2H atoms/Pt atom at the HER threshold potential, equal to ca. double the Hupd observed for Pt bulk or nanoparticles. The cluster catalysts under electrocatalytic conditions are hence best described as a Pt hydride compound, significantly departing from a metallic Pt cluster. The exception is Pt1/ITO, where H adsorption at the HER threshold potential is energetically unfavorable. The theory combines global optimization with grand canonical approaches for the influence of potential, uncovering the fact that several metastable structures contribute to the HER, changing with the applied potential. It is hence critical to include reactions of the ensemble of energetically accessible PtnHx/ITO structures to correctly predict the activity vs Ptn size and applied potential. For the small clusters, spillover of Hads from the clusters to the ITO support is significant, resulting in a competing channel for loss of Hads, particularly at slow potential scan rates.

We report the size-dependent activity and stability of FTO-supported Pt1,4,7,8 for electrocatalytic hydrogen evolution reaction, and show that clusters are significantly more active than polycrystalline Pt, but also have stability under HER conditions that is size-dependent. To understand the mechanistic origin of the size effects, we carried out detailed DFT-based theory, accounting for the structural fluxionality under varying potentials. We show that, even under coverage of the simplest adsorbate H, the clusters can undergo drastic changes and populate a grand canonical ensemble of hydride states with diverse distributions of stoichiometry, structure, and thus reactivity. Both experiment and theory find that electrocatalysis mainly results from heavily hydrogenated states of the clusters (~2 H/Pt), and an ensemble-based kinetic model reproduces the experimental activity trend and provides detailed insights into the contributions from metastable configurations. The size-dependent stability trend is rationalized by chemical bonding analysis. The comparison of experiment and theory demonstrates the potential- and adsorbate-coverage-dependent fluxionality of subnano clusters of different sizes and offers a systematic modeling strategy to tackle the complexities.

A combination of density functional theory (DFT) and experiments with atomically size-selected Ptn clusters deposited on indium-tin oxide (ITO) electrodes was used to examine the effects of applied potential and Ptn size on the electrocatalytic activity of Ptn (n = 1, 4, 7, 8) for the hydrogen evolution reaction (HER). Activity is found to be negligible for isolated Pt atoms on ITO, increasing rapidly with Ptn size, such that Pt7/ITO and Pt8/ITO have roughly double the activity per Pt atom compared atoms in the surface layer of polycrystalline Pt. Both DFT and experiment find that hydrogen under-potential deposition (Hupd) results in Ptn/ITO (n = 4, 7, 8) adsorbing ~2 H atoms/Pt atom at the HER threshold potential, equal to ca. double the Hupd observed for bulk Pt or Pt nanoparticles. The cluster catalysts under electrocatalytic conditions are hence best described as a Pt hydride compound, significantly departing from a metallic Pt cluster. The exception is Pt1/ITO, where H adsorption at the HER threshold potential is energetically unfavorable. Theory combines global optimization with grand canonical approaches for the influence of potential, uncovering that several metastable structures contribute to HER, changing with the applied potential. It is hence critical to include reactions of the ensemble of energetically accessible PtnHx/ITO structures to correctly predict the activity vs. Ptn size and applied potential. For the small clusters, spillover of Hads from the clusters to the ITO support is significant, resulting in a competing channel for loss of Hads, particularly at slow potential scan rates.

The oxygen reduction reaction (ORR) plays a key role in renewable energy transformation processes. Unfortunately, it is inherently sluggish, which greatly limits its industrial application. Sub-nano-cluster-decorated electrode interfaces are promising candidate ORR electrocatalysts. However, understanding the nature of the active sites on these catalysts under electrocatalytic conditions presents a formidable challenge for both experiment and theory, due to their dynamic fluxional character. Here, we combine global optimization with the electronic Grand Canonical DFT to elucidate the structure and dynamics of subnano Ptnclusters deposited on electrified graphite. We show that, under electrochemical conditions, these clusters exist as statistical ensembles of multiple states, whose fluxionality is greatly affected by the applied potential, electrolyte, and adsorbate coverage. The results reveal the presence of potential-dependent active sites and, hence, reaction energetics.

The rearrangement of Cu surfaces under electrochemical conditions is known to play a key role in the surface activation for major electrocatalytic reactions. Despite the extensive experimental insights into such rearrangements, from surface-sensitive spectroscopy and microscopy, the spatial and temporal resolution of these methods is insufficient to provide an atomistic picture of the electrochemical interface. Theoretical characterization has also been challenged by the diversity of restructuring configurations, surface stoichiometry, adsorbate configurations, and the effect of the electrode potential. Here, atomistic insight into the restructuring of the electrochemical interface is gained from first principles. Cu(100) restructuring under varying applied potentials and adsorbate coverages is studied by grand canonical density functional theory and global optimization techniques, as well as ab initio molecular dynamics and mechanistic calculations. We show that electroreduction conditions cause the formation of a shifted-row reconstruction on Cu(100), induced by hydrogen adsorption. The reconstruction is initiated at 1/6 ML H coverage, when the Cu-H bonding sufficiently weakens the Cu-Cu bonds between the top- and sublayer, and further stabilized at 1/3 ML when H adsorbates fill all the created 3-fold hollow sites. The simulated scanning tunneling microscopy (STM) images of the calculated reconstructed interfaces agree with experimental in situ STM. However, compared to the thermodynamic prediction, the onsets of reconstruction events in the experiment occur at more negative applied voltages. This is attributed to kinetic effects in restructuring, which we describe via different statistical models, to produce the potential- and pH-dependent surface stability diagram. This manuscript provides rich atomistic insight into surface restructuring in electroreduction conditions, which is required for the understanding and design of Cu-based materials for electrocatalytic processes. It also offers the methodology to study the problem of in situ electrode reconstruction.

Copper (Cu) remains the most important metal catalyst for the carbon dioxide reduction reaction (CO2 RR) into C2 products. Due to limited evidence from in situ experiments, mechanistic studies are often performed in the framework of density functional theory (DFT), using functionals at the generalized gradient approximation (GGA) level, which have fundamental difficulties to correctly describe CO adsorption and surface stability. We employ the adiabatic connection fluctuation dissipation theorem within the random phase approximation (RPA), in combination with the linearized Poisson-Boltzmann equation to describe solvation effects, to investigate the mechanism of CO2 RR on the Cu(100) facet. Qualitatively different from the DFT-GGA results, RPA results propose the formation of *OCCHO as the potential determining step towards C2 products. The results suggest that it is important to use more accurate methods like RPA when modeling reactions involving multiple CO-related species like CO2 RR.

Dynamic restructuring of bimetallic catalysts plays a crucial role in their catalytic activity and selectivity. In particular, catalyst pretreatment with species such as carbon monoxide and oxygen has been shown to be an effective strategy for tuning the surface composition and morphology. Mechanistic and kinetic understanding of such restructuring is fundamental to the chemistry and engineering of surface active sites but has remained challenging due to the large structural, chemical, and temporal degrees of freedom. Here, we combine time-resolved temperature-programmed infrared reflection absorption spectroscopy, ab initio thermodynamics, and machine-learning molecular dynamics to uncover previously unidentified timescale and kinetic parameters of in situ restructuring in Pd/Au(111), a highly relevant model system for dilute Pd-in-Au nanoparticle catalysts. The key innovation lies in utilizing CO not only as a chemically sensitive probe of surface Pd but also as an agent that induces restructuring of the surface. Upon annealing in vacuum, as-deposited Pd islands became encapsulated by Au and partially dissolved into the subsurface, leaving behind isolated Pd monomers on the surface. Subsequent exposure to 0.1 mbar CO enabled Pd monomers to repopulate the surface up to 373 K, above which complete Pd dissolution occurred by 473 K, with apparent activation energies of 0.14 and 0.48 eV, respectively. These restructuring processes occurred over the span of ∼1000 s at a given temperature. Such a minute-timescale dynamics not only elucidates the fluxional nature of alloy catalysts but also presents an opportunity to fine-tune the surface under moderate temperature and pressure conditions.

Electrocatalysis plays a key role in sustainable energy conversion and storage. It is critical to model the grand canonical treatment of electrons, which accounts for the electrochemical potential explicitly, at the atomic scale and understand these reactions at electrified interfaces. However, such a grand canonical treatment for electrocatalytic modeling is in practice restricted to a treatment of electronic structure with density functional theory, and more accurate methods are in many cases desirable. Here, we develop an original workflow combining the grand canonical treatment of electrons with many-body perturbation theory in its random phase approximation (RPA). Using the potential dependent adsorption of carbon monoxide on the copper (100) facet, we show that the grand canonical RPA energetics provide the correct on-top Cu geometry for CO at reducing potential. The match with experimental results is significantly improved compared to the functionals at the generalized gradient approximation level, which is the most commonly used approximation for electrochemical applications. We expect this development to pave the way to further electrochemical applications using RPA.

Abstract Noble metals supported on reducible oxides, like CoOx and TiOx, exhibit superior activity in many chemical reactions, but the origin of the increased activity is not well understood. To answer this question we studied thin films of CoOx supported on an Au(111) single crystal surface as a model for the CO oxidation reaction. We show that three reaction regimes exist in response to chemical and topographic restructuring of the CoOx catalyst as a function of reactant gas phase CO/O2 stoichiometry and temperature. Under oxygen-lean conditions and moderate temperatures (≤150 °C), partially oxidized films (CoOx1) forms containing Co3+ species that are effective in a wide temperature range. Resonant photoemission spectroscopy (ResPES) revealed the unique role of Co3+ sites in catalyzing the CO oxidation. Density function theory (DFT) calculations provided deeper insights into the pathway and free energy barriers for the reactions on these oxide phases. These findings in this work highlight the versatility of catalysts and their evolution to form different active phases, both topological and chemically, in response to reaction conditions exposing a new paradigm in the catalyst structure during operation.

The development of new catalyst materials for energy-efficient chemical synthesis is critical as over 80% of industrial processes rely on catalysts, with many of the most energy-intensive processes specifically using heterogeneous catalysis. Catalytic performance is a complex interplay of phenomena involving temperature, pressure, gas composition, surface composition, and structure over multiple length and time scales. In response to this complexity, the integrated approach to heterogeneous dilute alloy catalysis reviewed here brings together materials synthesis, mechanistic surface chemistry, reaction kinetics, in situ and operando characterization, and theoretical calculations in a coordinated effort to develop design principles to predict and improve catalytic selectivity. Dilute alloy catalysts─in which isolated atoms or small ensembles of the minority metal on the host metal lead to enhanced reactivity while retaining selectivity─are particularly promising as selective catalysts. Several dilute alloy materials using Au, Ag, and Cu as the majority host element, including more recently introduced support-free nanoporous metals and oxide-supported nanoparticle "raspberry colloid templated (RCT)" materials, are reviewed for selective oxidation and hydrogenation reactions. Progress in understanding how such dilute alloy catalysts can be used to enhance selectivity of key synthetic reactions is reviewed, including quantitative scaling from model studies to catalytic conditions. The dynamic evolution of catalyst structure and composition studied in surface science and catalytic conditions and their relationship to catalytic function are also discussed, followed by advanced characterization and theoretical modeling that have been developed to determine the distribution of minority metal atoms at or near the surface. The integrated approach demonstrates the success of bridging the divide between fundamental knowledge and design of catalytic processes in complex catalytic systems, which can accelerate the development of new and efficient catalytic processes.

Alloy nanocatalysts have found broad applications ranging from fuel cells tocatalytic converters and hydrogenation reactions. Despite extensive studies,identifying the active sites of nanocatalysts remains a major challenge due tothe heterogeneity of the local atomic environment. Here, we advance atomicelectron tomography to determine the 3D local atomic structure, surfacemorphology and chemical composition of PtNi and Mo-doped PtNi nanocatalysts.Using machine learning trained by density functional theory calculations, weidentify the catalytic active sites for the oxygen reduction reaction fromexperimental 3D atomic coordinates, which are corroborated by electrochemicalmeasurements. By quantifying the structure-activity relationship, we discover alocal environment descriptor to explain and predict the catalytic active sitesat the atomic level. The ability to determine the 3D atomic structure andchemical species coupled with machine learning is expected to expand ourfundamental understanding of a wide range of nanocatalysts.

Graphene has received tremendous interest in both chemical and physical fields. Among different edges of the graphene system, the zigzag edge terminated graphene nanoribbons (ZGNRs) show unique magnetic properties in the antiferromagnetic (AFM) state. However, to date, the understanding of ZGNR chemical properties is mainly based on the partial radical concept, and in previous studies, the energy differences between the ferromagnetic (FM) and AFM states are smaller than experimental evidence. Here, we report that the strongly constrained and appropriately normed functional gives a significantly larger energy difference, which matches the experimental observation. Furthermore, utilizing the energetics in the large difference case, we propose a conceptual supplement to the previous partial radical concept: the overall stabilization of the AFM state compared to the nonmagnetic (NM) state consists of two parts that affect the adsorption energy conversely. The NM-FM energy differences will strengthen the adsorption, being in line with the previous partial radical concept. The FM-AFM energy differences will instead weaken the adsorption. We perform calculations of H, OH, and LiS radical adsorption energies on ZGNRs to show that this weakening effect is numerically non-negligible: at least a ∼0.2 eV difference in the adsorption energies is found. We expect that this refinement of the partial radical concept can provide a more comprehensive understanding of the chemical properties of ZGNRs. The differences in adsorption energies for the H, OH, and LiS radicals found here lead to significant changes in the predicted reactivity of the ZGNR models.

With the emergence of methods for computing rate constants for elementary reaction steps of catalytic reactions, benchmarking their accuracy becomes important. The unimolecular dehydrogenation of adsorbed formate on metal surfaces serves as a prototype for comparing experiment and theory. Previously measured pre-exponential factors for CO2 formation from formate on metal surfaces, including Cu(110), are substantially higher than expected from the often used value of k B T/h, or ∼6 × 1012 s-1, suggesting that the entropy of the transition state is higher than that of the adsorbed formate. Herein, the rate constant parameters for formate decomposition on Au(110) and Cu(110) are addressed quantitatively by both experiment and theory and compared. A pre-exponential factor of 2.3 × 1014 s-1 was obtained experimentally on Au(110). DFT calculations revealed the most stable configuration of formate on both surfaces to be bidentate and the transition states to be less rigidly bound to the surface compared to the reactant state, resulting in a higher entropy of activation and a pre-exponential factor exceeding k B T/h. Though reasonable agreement is obtained between experiment and theory for the pre-exponential factors, the activation energies determined experimentally remain consistently higher than those computed by DFT using the GGA-PBE functional. This difference was largely erased when the metaGGA-SCAN functional was applied. This study provides insight into the underlying factors that result in the relatively high pre-exponential factors for unimolecular decomposition on metal surfaces generally, highlights the importance of mobility for the transition state, and offers vital information related to the direct use of DFT to predict rate constants for elementary reaction steps on metal surfaces.

Rational catalyst design is crucial toward achieving more energy-efficient and sustainable catalytic processes. Understanding and modeling catalytic reaction pathways and kinetics require atomic level knowledge of the active sites. These structures often change dynamically during reactions and are difficult to decipher. A prototypical example is the hydrogen-deuterium exchange reaction catalyzed by dilute Pd-in-Au alloy nanoparticles. From a combination of catalytic activity measurements, machine learning-enabled spectroscopic analysis, and first-principles based kinetic modeling, we demonstrate that the active species are surface Pd ensembles containing only a few (from 1 to 3) Pd atoms. These species simultaneously explain the observed X-ray spectra and equate the experimental and theoretical values of the apparent activation energy. Remarkably, we find that the catalytic activity can be tuned on demand by controlling the size of the Pd ensembles through catalyst pretreatment. Our data-driven multimodal approach enables decoding of reactive structures in complex and dynamic alloy catalysts.

Elucidation of reaction mechanisms and the geometric and electronic structure of the active sites themselves is a challenging, yet essential task in the design of new heterogeneous catalysts. Such investigations are best implemented via a multipronged approach that comprises ambient pressure catalysis, surface science, and theory. Herein, we employ this strategy to understand the workings of NiAu single-atom alloy (SAA) catalysts for the selective nonoxidative dehydrogenation of ethanol to acetaldehyde and hydrogen. The atomic dispersion of Ni is paramount for selective ethanol to acetaldehyde conversion, and we show that even the presence of small Ni ensembles in the Au surface results in the formation of undesirable byproducts via C-C scission. Spectroscopic, kinetic, and theoretical investigations of the reaction mechanism reveal that both C-H and O-H bond cleavage steps are kinetically relevant and single Ni atoms are confirmed as the active sites. X-ray absorption spectroscopy studies allow us to follow the charge of the Ni atoms in the Au host before, under, and after a reaction cycle. Specifically, in the pristine state the Ni atoms carry a partial positive charge that increases upon coordination to the electronegative oxygen in ethanol and decreases upon desorption. This type of oxidation state cycling during reaction is similar to the behavior of single-site homogeneous catalysts. Given the unique electronic structure of many single-site catalysts, such a combined approach in which the atomic-scale catalyst structure and charge state of the single atom dopant can be monitored as a function of its reactive environment is a key step toward developing structure-function relationships that inform the design of new catalysts.

First-principles calculations play a key role in understanding the interactions of molecules with transition-metal surfaces and the energy profiles for catalytic reactions. However, many of the commonly used density functionals are not able to correctly predict the surface energy as well as the adsorption site preference for a key molecule such as CO, and it is not clear to what extent this shortcoming influences the prediction of reaction or diffusion pathways. Here, we report calculations of carbon monoxide diffusion on the Cu(001) surface along the [100] and [110] pathways, as well as the surface energy of Cu(001), and CO-adsorption energy and compare the performance of the Perdew-Burke-Ernzerhof (PBE), PBE + D2, PBE + D3, RPBE, Bayesian error estimation functional with van der Waals correlation (BEEF-vdW), HSE06 density functionals, and the random phase approximation (RPA), a post-Hartree-Fock method based on many-body perturbation theory. We critically evaluate the performance of these methods and find that RPA appears to be the only method giving correct site preference, overall barrier, adsorption enthalpy, and surface energy. For all of the other methods, at least one of these properties is not correctly captured. These results imply that many density functional theory (DFT)-based methods lead to qualitative and quantitative errors in describing CO interaction with transition-metal surfaces, which significantly impacts the description of diffusion pathways. It is well conceivable that similar effects exist when surface reactions of CO-related species are considered. We expect that the methodology presented here will be used to get more detailed insights into reaction pathways for CO conversion on transition-metal surfaces in general and Cu in particular, which will allow us to better understand the catalytic and electrocatalytic reactions involving CO-related species.

Step and kink sites at Pt surfaces have crucial importance in catalysis. We employ a high dimensional neural network potential (HDNNP) trained using first-principles calculations to determine the adsorption structure of CO under ambient conditions (T = 300 K and P = 1 atm) on these surfaces. To thoroughly explore the potential energy surface (PES), we use a modified basin hopping method. We utilize the explored PES to identify the adsorbate structures and show that under the considered conditions several low free energy structures exist. Under the considered temperature and pressure conditions, the step edge (or kink) is totally occupied by on-top CO molecules. We show that the step structure and the structure of CO molecules on the step dictate the arrangement of CO molecules on the lower terrace. On surfaces with (111) steps, like Pt(553), CO forms quasi-hexagonal structures on the terrace with the top site preferred, with on average two top site CO for one multiply bonded CO, while in contrast surfaces with (100) steps, like Pt(557), present a majority of multiply bonded CO on their terrace. Short terraced surfaces, like Pt(643), with square (100) steps that are broken by kink sites constrain the CO arrangement parallel to the step edge. Overall, this effort provides detailed analysis on the influence of the step edge structure, kink sites, and terrace width on the organization of CO molecules on non-reconstructed stepped surfaces, yielding initial structures for understanding restructuring events driven by CO at high coverages and ambient pressure.

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.

Acceptorless dehydrogenation into carbonyls and molecular hydrogen is an attractive strategy to valorize (biobased) alcohols. Using 2-octanol dehydrogenation as benchmark reaction in a continuous reactor, a library of metal-supported catalysts is tested to validate the predictive level of catalytic activity for combined DFT and micro-kinetic modeling. Based on a series of transition metals, scaling relations are determined as a function of two descriptors, i.e. the surface binding energies of atomic carbon and oxygen. Then, a volcano-shape relation based on both descriptors is derived, paving the way to further optimization of active catalysts. Evaluation of 294 diluted alloys but also a series of carbides and nitrides with the volcano map identified 12 promising candidates with potentially improved activity for alcohol dehydrogenation, which provides useful guidance for experimental catalyst design. Further screening identifies β-Mo2N and γ-Mo2N exposing mostly (001) and (100) facets as potential candidates for alcohol dehydrogenation.