Identification of general linear relationships between activation energies and enthalpy changes for dissociation reactions at surfaces

Revealing operando surface defect-dependent electrocatalytic performance of Pt at the subparticle level

Understanding the operando defect-tuning performance of catalysts is critical to establish an accurate structure-activity relationship of a catalyst. Here, with the tool of single-molecule super-resolution fluorescence microscopy, by imaging intermediate CO formation/oxidation during the methanol oxidation reaction process on individual defective Pt nanotubes, we reveal that the fresh Pt ends with more defects are more active and anti-CO poisoning than fresh center areas with less defects, while such difference could be reversed after catalysis-induced step-by-step creation of more defects on the Pt surface. Further experimental results reveal an operando volcano relationship between the catalytic performance (activity and anti-CO ability) and the fine-tuned defect density. Systematic DFT calculations indicate that such an operando volcano relationship could be attributed to the defect-dependent transition state free energy and the accelerated surface reconstructing of defects or Pt-atom moving driven by the adsorption of the CO intermediate. These insights deepen our understanding to the operando defect-driven catalysis at single-molecule and subparticle level, which is able to help the design of highly efficient defect-based catalysts.

Structure Sensitivity of Metal Catalysts Revealed by Interpretable Machine Learning and First-Principles Calculations

The nature of the active sites and their structure sensitivity are the keys to rational design of efficient catalysts but have been debated for almost one century in heterogeneous catalysis. Though the Brønsted-Evans-Polanyi (BEP) relationship along with linear scaling relation has long been used to study the reactivity, explicit geometry, and composition properties are absent in this relationship, a fact that prevents its exploration in structure sensitivity of supported catalysts. In this work, based on interpretable multitask symbolic regression and a comprehensive first-principles data set, we discovered a structure descriptor, the topological under-coordinated number mediated by number of valence electrons and the lattice constant, to successfully address the structure sensitivity of metal catalysts. The database used for training, testing, and transferability investigation includes bond-breaking barriers of 20 distinct chemical bonds over 10 transition metals, two metal crystallographic phases, and 17 different facets. The resulting 2D descriptor composing the structure term and the reaction energy term shows great accuracy to predict the reaction barriers and generalizability over the data set with diverse chemical bonds in symmetry, bond order, and steric hindrance. The theory is physical and concise, providing a constructive strategy not only to understand the structure sensitivity but also to decipher the entangled geometric and electronic effects of metal catalysts. The insights revealed are valuable for the rational design of the site-specific metal catalysts.

Enhanced Carbon-Carbon Coupling at Interfaces with Abrupt Coordination Number Changes

Cu-catalyzed electrochemical CO2 reduction reaction (CO2RR) produces multi-carbon (C2+) chemicals with considerable selectivities and activities, yet required high overpotentials impede its practical application. Here, we design interfaces with abrupt coordination number (CN) changes that greatly reduce the applied potential for achieving high C2+ Faradaic efficiency (FE). Encouraged by the mechanistic finding that the coupling between *CO and *CO(H) is the most probable C-C bond formation path, we use Cu2O- and Cu-phthalocyanine-derived Cu (OD-Cu and PD-Cu) to build the interface. Using operando X-ray absorption spectroscopy (XAS), we find that the Cu CN of OD-Cu is ~11, favoring CO* adsorption, while the PD-Cu has a COH*-favorable CN of ~4. Operando Raman spectroscopy revealed that the interfaces with abrupt CN changes promote *OCCOH formation. As a result, the designed catalyst achieves a C2+ FE of 85±2 % at 220 mA cm-2 in a zero-gap CO2 electrolyzer. An improvement of C2+ FE by 3 times is confirmed at the low potential regime where the current density is 60-140 mA cm-2, compared to bare OD-Cu. We report a 45-h stable CO2RR operation at 220 mA cm-2, producing a C2+ product FE of ~80 %.

Michaelis-Menten kinetics during dry etching processes

The chemical etching of germanium in Br2 environment at elevated temperatures is described by the Michaelis-Menten equation. The validity limit of Michaelis-Menten kinetics is subjected to the detailed analysis. The steady-state etching rate requires synergy of two different process parameters. High purity gas should be directed to the substrate on which intermediate reaction product does not accumulate. Theoretical calculations indicate that maximum etching rate is maintained when 99.89% of the germanium surface is covered by the reaction product, and 99.9999967% of the incident Br2 molecules are reflected from the substrate surface. Under these conditions, single GeBr2 molecule is formed after 30 million collisions of Br2 molecules with the germanium surface.

S-Se oxidative addition to auranofin derivatives: a DFT study

Oxidative addition of the S-Se bond to Au(I) complexes is discussed for a series of 26 auranofin (AF) derivatives. AF and its analogues are Au(I) complexes with recognized anticancer activity that act by binding and inhibiting the thioredoxin reductase (TrxR) enzyme. Generally, the oxidative addition to Au(I) is a sluggish reaction under mild conditions (i.e., a high activation barrier - ΔH‡), which is also verified here for AF, ΔH‡ = 33.0 kcal mol-1. However, we predicted that subtle changes in the AF ligands can make the process feasible under standard conditions. For instance, the exchange of -PEt3 by -P(Et2)(OEt), which is a weaker electron σ-donor, reduced the activation barrier to 17.1 kcal mol-1. Furthermore, substitution of the -SAtg ligand by -Cl- leads to a ΔH‡ value of 22.5 kcal mol-1. Overall, the reaction is driven by the nucleophilic attack of the S-Se bond on the Au(I) center, attributed mainly to the charge transfer (4p)Se → (6p)Au, which characterizes the addition step. At the transition state (TS) point, the (5d)Au → σ*(S-Se) charge transfer becomes relevant, facilitating the S-Se bond breakage and the oxidation step. In addition to the electron transfers, the strain energy to deform the linear Au(I) geometry to the tetracoordinated Au(III) arrangement in the TS structure plays a primary role in explaining the trends in the activation barriers. Finally, the activation barrier (ΔH‡) and reaction energy (ΔH°) were correlated for most of the complexes studied, which suggests that the reaction passes through a late or product-like TS and, therefore, the steric and electronic factors affecting ΔH‡ also act on ΔH°. Overall, the results presented here might open up a new field of investigation for interactions between AF derivatives and TrxR, which contributes to a full understanding of the biological mechanism of action of these species.

Design of MoS2 edge-anchored single-atom catalysts for propane dehydrogenation driven by DFT and microkinetic modeling

The design of efficient catalysts for direct propane dehydrogenation (PDH) to inhibit coke formation and deactivation of traditional Pt-based catalysts are challenging tasks. Herein, by exploiting the unique geometric feature and tunability of single atom catalysts (SACs), a wide range of 3d-5d transition metals anchored on the MoS2 edge in the single atom form (TM1-S4/edge) are comprehensively investigated for the PDH application by first-principles calculations, ab initio molecular dynamics (AIMD) simulations and microkinetic modeling. Five criteria are assessed in terms of the feasibility of preparation, practical stability, feasibility of recovery after air oxidation, activity and selectivity. We identified Ru1-S4/edge SAC as the most promising candidate with activity six times higher than that of the conventional Pt(111) catalyst. Interestingly, AIMD simulations show that the motif region of the highly reactive TM1-S4/edge SACs (such as Ru, Os, Rh, and Ir) exhibits a dynamic change, with a TM-coordinated S atom tending to flutter at reaction temperatures and return to its initial position when the species is adsorbed on TMs, thereby affecting the PDH activities. In addition to identifying the potential PDH catalyst from a practical application point of view, we believe that this study also provides a comprehensive picture for the theoretical screening of low-coordination single-atom catalysts.

High-Throughput Calculations for Screening d- and p-Block Single-Atom Catalysts toward Li2 S/Na2 S Decomposition Guided by Facile Descriptor beyond Brønsted-Evans-Polanyi Relationship

Single-atom catalysts (SACs) are promising cathode materials for addressing issues faced by lithium-sulfur batteries. Considering the ample chemical space of SACs, high-throughput calculations are efficient strategies for their rational design. However, the high throughput calculations are impeded by the time-consuming determination of the decomposition barrier (Eb ) of Li2 S. In this study, the effects of bond formation and breakage on the kinetics of SAC-catalyzed Li2 S decomposition with g-C3 N4 as the substrate are clarified. Furthermore, a new efficient and easily-obtained descriptor Li─S─Li angle (ALi─S─Li ) of adsorbed Li2 S, different from the widely accepted thermodynamic data for predicting Eb , which breaks the well-known Brønsted-Evans-Polanyi relationship, is identified. Under the guidance of ALi─S─Li , several superior SACs with d- and p-block metal centers supported by g-C3 N4 are screened to accelerate the sulfur redox reaction and fix the soluble lithium polysulfides. The newly identified descriptor of ALi─S─Li can be extended to rationally design SACs for Na─S batteries. This study opens a new pathway for tuning the performance of SACs to catalyze the decomposition of X2 S (X = Li, Na, and K) and thus accelerate the design of SACs for alkaline-chalcogenide batteries.

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 Bro̷nsted-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.

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.

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.

Unravelling the Impact of Metal Dopants and Oxygen Vacancies on Syngas Conversion over Oxides: A Machine Learning-Accelerated Study of CO Activation on Cr-Doped ZnO Surfaces

As a critical component of the OX-ZEO composite catalysts toward syngas conversion, the Cr-doped ZnO ternary system can be considered as a model system for understanding oxide catalysts. However, due to the complexity of its structures, traditional approaches, both experimental and theoretical, encounter significant challenges. Herein, we employ machine learning-accelerated methods, including grand canonical Monte Carlo and genetic algorithm, to explore the ZnO(1010) surface with various Cr and oxygen vacancy (OV) concentrations. Stable surfaces with varied Cr and OV concentrations were then systematically investigated to examine their influence on the CO activation via density functional theory calculations. We observe that Cr tends to preferentially appear on the surface of ZnO(1010) rather than in its interior regions and Cr-doped structures incline to form rectangular islands along the [0001] direction at high Cr and OV concentrations. Additionally, detailed calculations of CO reactivity unveil an inverse relationship between the reaction barrier (Ea) for C-O bond dissociation and the Cr and OV concentrations, and a linear relationship is observed between OV formation energy and Ea for CO activation. Further analyses indicate that the C-O bond dissociation is much more favored when the adjacent OVs are geometrically aligned in the [1210] direction, and Cr is doped around the reactive sites. These findings provide a deeper insight into CO activation over the Cr-doped ZnO surface and offer valuable guidance for the rational design of effective catalysts for syngas conversion.

Comparative theoretical study of CO2 activation on clean and potassium-preadsorbed low index surfaces of transition metals

CONTEXT

The efficient catalysis of CO2 adsorption and activation presents a formidable challenge due to its pronounced thermodynamic stability and kinetic inertia. Previous experiments have left gaps in understanding the promotional effects and underlying mechanism of potassium. In this study, we systematically investigate CO2 adsorption and activation on clean and potassium-preadsorbed low index surfaces of transition metals. Theoretical results reveal a substantial augmentation in CO2 binding strength when potassium is introduced, concomitant with a general reduction in activation energies. Notably, linear correlations are significant on close-packed metal surfaces without and with potassium additive. Through a comprehensive analysis encompassing geometric parameters, electronic structures, and energy decomposition, we discern the physical underpinnings of the potassium effect. This enhancement is primarily ascribed to direct electron transfer and dipole-dipole interactions. Furthermore, we scrutinize the impact of an external electric field, demonstrating that the application of a negative electric field accelerates CO2 activation, mirroring the effects observed with potassium.

METHODS

All the periodic density function theory (DFT) calculations were performed by the Vienna Ab Initio Simulation package (VASP). The interaction between nucleus and valence electron was described using the pseudopotentials found in the projector augmented wave method (PAW). Throughout the entire work, the Bayesian error estimation functional (BEEF) was used.

Toward the Rational Design of More Efficient Mo2C Catalysts for Hydrodeoxygenation-Mechanism and Descriptor Identification

Viable alternatives to scarce and expensive noble-metal-based catalysts are transition-metal carbides such as Mo and W carbides. It has been shown that these are active and selective catalysts in the hydrodeoxygenation of renewable lipid-based feedstocks. However, the reaction mechanism and the structure-activity relationship of these transition-metal carbides have not yet been fully clarified. In this work, the reaction mechanism of butyric acid hydrodeoxygenation (HDO) over molybdenum carbide (Mo2C) has been studied comprehensively by means of density functional theory coupled with microkinetic modeling. We identified the rate-determining step to be butanol dissociation: C4H9*OH + * → C4H9* + *OH. Then we further explored the possibility to facilitate this step upon heteroatom doping and found that Zr- and Nb-doped Mo2C are the most promising catalysts with enhanced HDO catalytic activity. Linear-scaling relationships were established between the electronic and geometrical descriptors of the dopants and the catalytic performance of various doped Mo2C catalysts. It was demonstrated that descriptors such as dopants' d-band filling and atomic radius play key roles in governing the catalytic activity. This fundamental understanding delivers practical strategies for the rational design of Mo2C-based transition-metal carbide catalysts with improved HDO performance.

Machine Learning-Based Prediction of Activation Energies for Chemical Reactions on Metal Surfaces

In computational surface catalysis, the calculation of activation energies of chemical reactions is expensive, which, in many cases, limits our ability to understand complex reaction networks. Here, we present a universal, machine learning-based approach for the prediction of activation energies for reactions of C-, O-, and H-containing molecules on transition metal surfaces. We rely on generalized Bronsted-Evans-Polanyi relationships in combination with machine learning-based multiparameter regression techniques to train our model for reactions included in the University of Arizona Reaction database. In our best approach, we find a mean absolute error for activation energies within our test set of 0.14 eV if the reaction energy is known and 0.19 eV if the reaction energy is unknown. We expect that this methodology will often replace the explicit calculation of activation energies within surface catalysis when exploring large reaction networks or screening catalysts for desirable properties in the future.

Reactivity Prediction of Cu-Catalyzed Halogen Atom Transfer Reactions Using Data-Driven Techniques

In catalysis, linear free energy relationships (LFERs) are commonly used to identify reaction descriptors that enable the prediction of outcomes and the design of more effective catalysts. Herein, LFERs are established for the reductive cleavage of the C(sp3)-X bond in alkyl halides (RX) by Cu complexes. This reaction represents the activation step in atom transfer radical polymerization and atom transfer radical addition/cyclization. The values of the activation rate constant, kact, for 107 Cu complex/RX couples in 5 different solvents spanning over 13 orders of magnitude were effectively interpolated by the equation: log kact = sC(I + C + S), where I, C, and S are, respectively, the initiator, catalyst, and solvent parameters, and sC is the catalyst-specific sensitivity parameter. Furthermore, each of these parameters was correlated to relevant descriptors, which included the bond dissociation free energy of RX and its Tolman cone angle θ, the electron affinity of X, the radical stabilization energy, the standard reduction potential of the Cu complex, the polarizability parameter π* of the solvent, and the distortion energy of the complex in its transition state. This set of descriptors establishes the fundamental properties of Cu complexes and RX that determine their reactivity and that need to be considered when designing novel systems for atom transfer radical reactions. Finally, a multivariate linear regression (MLR) approach was adopted to develop an objective model that surpassed the predictive capability of the LFER equation. Thus, the MLR model was employed to predict kact values for >2000 Cu complex/RX pairs.

Ru-Cu Nanoheterostructures for Efficient Hydrogen Evolution Reaction in Alkaline Water Electrolyzers

Combining multiple species working in tandem for different hydrogen evolution reaction (HER) steps is an effective strategy to design HER electrocatalysts. Here, we engineered a hierarchical electrode for the HER composed of amorphous-TiO2/Cu nanorods (NRs) decorated with cost-effective Ru-Cu nanoheterostructures (Ru mass loading = 52 μg/cm2). Such an electrode exhibits a stable, over 250 h, low overpotential of 74 mV at -200 mA/cm2 for the HER in 1 M NaOH. The high activity of the electrode is attributed, by structural analysis, operando X-ray absorption spectroscopy, and first-principles simulations, to synergistic functionalities: (1) mechanically robust, vertically aligned Cu NRs with high electrical conductivity and porosity provide fast charge and gas transfer channels; (2) the Ru electronic structure, regulated by the size of Cu clusters at the surface, facilitates the water dissociation (Volmer step); (3) the Cu clusters grown atop Ru exhibit a close-to-zero Gibbs free energy of the hydrogen adsorption, promoting fast Heyrovsky/Tafel steps. An alkaline electrolyzer (AEL) coupling the proposed cathode and a stainless-steel anode can stably operate in both continuous (1 A/cm2 for over 200 h) and intermittent modes (accelerated stress tests). A techno-economic analysis predicts the minimal overall hydrogen production cost of US$2.12/kg in a 1 MW AEL plant of 30 year lifetime based on our AEL single cell, hitting the worldwide targets (US$2-2.5/kgH2).

Thermodynamic and kinetic modeling of electrocatalytic reactions using a first-principles approach

The computational modeling of electrochemical interfaces and their applications in electrocatalysis has attracted great attention in recent years. While tremendous progress has been made in this area, however, the accurate atomistic descriptions at the electrode/electrolyte interfaces remain a great challenge. The Computational Hydrogen Electrode (CHE) method and continuum modeling of the solvent and electrolyte interactions form the basis for most of these methodological developments. Several posterior corrections have been added to the CHE method to improve its accuracy and widen its applications. The most recently developed grand canonical potential approaches with the embedded diffuse layer models have shown considerable improvement in defining interfacial interactions at electrode/electrolyte interfaces over the state-of-the-art computational models for electrocatalysis. In this Review, we present an overview of these different computational models developed over the years to quantitatively probe the thermodynamics and kinetics of electrochemical reactions in the presence of an electrified catalyst surface under various electrochemical environments. We begin our discussion by giving a brief picture of the different continuum solvation approaches, implemented within the ab initio method to effectively model the solvent and electrolyte interactions. Next, we present the thermodynamic and kinetic modeling approaches to determine the activity and stability of the electrocatalysts. A few applications to these approaches are also discussed. We conclude by giving an outlook on the different machine learning models that have been integrated with the thermodynamic approaches to improve their efficiency and widen their applicability.

Hydrogen Evolution Reaction on Ultra-Smooth Sputtered Nanocrystalline Ni Thin Films in Alkaline Media-From Intrinsic Activity to the Effects of Surface Oxidation

Highly effective yet affordable non-noble metal catalysts are a key component for advances in hydrogen generation via electrolysis. The synthesis of catalytic heterostructures containing established Ni in combination with surface NiO, Ni(OH)₂, and NiOOH domains gives rise to a synergistic effect between the surface components and is highly beneficial for water splitting and the hydrogen evolution reaction (HER). Herein, the intrinsic catalytic activity of pure Ni and the effect of partial electrochemical oxidation of ultra-smooth magnetron sputter-deposited Ni surfaces are analyzed by combining electrochemical measurements with transmission electron microscopy, selected area electron diffraction, X-ray photoelectron spectroscopy, and atomic force microscopy. The experimental investigations are supplemented by Density Functional Theory and Kinetic Monte Carlo simulations. Kinetic parameters for the HER are evaluated while surface roughening is carefully monitored during different Ni film treatment and operation stages. Surface oxidation results in the dominant formation of Ni(OH)₂, practically negligible surface roughening, and 3-5 times increased HER exchange current densities. Higher levels of surface roughening are observed during prolonged cycling to deep negative potentials, while surface oxidation slows down the HER activity losses compared to as-deposited films. Thus, surface oxidation increases the intrinsic HER activity of nickel and is also a viable strategy to improve catalyst durability.

Inverted Region in Electrochemical Reduction of CO2 Induced by Potential-Dependent Pauli Repulsion

Electrochemical CO₂ reduction reaction (eCO₂RR) is of great significance to energy and environmental engineering, while fundamental questions remain regarding its mechanisms. Herein, we formulate a fundamental understanding of the interplay between the applied potential (U) and kinetics of CO₂ activation in eCO₂RR on Cu surfaces. We find that the nature of the CO₂ activation mechanism in eCO₂RR varies with U, and it is the sequential electron-proton transfer (SEPT) mechanism dominant at the working U but switched to the concerted proton-electron transfer (CPET) mechanism at highly negative U. We then identify that the barrier of the electron-transfer step in the SEPT mechanism exhibits an inverted region as U decreases, which originates from the rapidly rising Pauli repulsion in the physisorption of CO₂ with decreasing U. We further demonstrate catalyst designs that effectively suppress the adverse effect of Pauli repulsion. This fundamental understanding may be general for the electrochemical reduction reactions of closed-shell molecules.

Surface hydroxide promotes CO2 electrolysis to ethylene in acidic conditions

Performing CO₂ reduction in acidic conditions enables high single-pass CO₂ conversion efficiency. However, a faster kinetics of the hydrogen evolution reaction compared to CO₂ reduction limits the selectivity toward multicarbon products. Prior studies have shown that adsorbed hydroxide on the Cu surface promotes CO₂ reduction in neutral and alkaline conditions. We posited that limited adsorbed hydroxide species in acidic CO₂ reduction could contribute to a low selectivity to multicarbon products. Here we report an electrodeposited Cu catalyst that suppresses hydrogen formation and promotes selective CO₂ reduction in acidic conditions. Using in situ time-resolved Raman spectroscopy, we show that a high concentration of CO and OH on the catalyst surface promotes C-C coupling, a finding that we correlate with evidence of increased CO residence time. The optimized electrodeposited Cu catalyst achieves a 60% faradaic efficiency for ethylene and 90% for multicarbon products. When deployed in a slim flow cell, the catalyst attains a 20% energy efficiency to ethylene, and 30% to multicarbon products.

Comprehensive Study of Oxygen Vacancies on the Catalytic Performance of ZnO for CO/H2 Activation Using Machine Learning-Accelerated First-Principles Simulations

Oxygen vacancies (OVs) play important roles on any oxide catalysts. In this work, using an investigation of the OV effects on ZnO(101̅0) for CO and H₂ activation as an example, we demonstrate, via machine learning potentials (MLPs), genetic algorithm (GA)-based global optimization, and density functional theory (DFT) validations, that the ZnO(101̅0) surface with 0.33 ML OVs is the most likely surface configuration under experimental conditions (673 K and 2.5 MPa syngas (H₂:CO = 1.5)). It is found that a surface reconstruction from the wurtzite structure to a body-centered-tetragonal one would occur in the presence of OVs. We show that the OVs create a Zn₃ cluster site, allowing H₂ homolysis and C-O bond cleavage to occur. Furthermore, the activity of intrinsic sites (Zn_3c and O_3c sites) is almost invariable, while the activity of the generated OV sites is strongly dependent on the concentration of the OVs. It is also found that OV distributions on the surface can considerably affect the reactions; the barrier of C-O bond dissociation is significantly reduced when the OVs are aligned along the [12̅10] direction. These findings may be general in the systems with metal oxides in heterogeneous catalysis and may have significant impacts on the field of catalyst design by regulating the concentration and distribution of the OVs.

Promoted coke resistance of Ni by surface carbon for the dry reforming of methane

Dry reforming of methane (DRM) is an efficient process to transform methane and carbon dioxide to syngas. Nickel could show good catalytic activity for DRM, whereas the deactivation of nickel surfaces by the formation of inert carbon structures is inevitable. In this study, we carry out a detailed investigation of the evolution and catalytic performance of the carbon-covered surface structure on Ni(100) with a combined density functional theory and microkinetic modeling approach. The results suggest that the pristine Ni(100) surface is prone to carbon deposition and accumulation under reaction conditions. Further studies show that over this carbon-covered reconstructed Ni(100) surface, a carbon-based Mars-van-Krevelen mechanism would be favored, and the activity and coke resistance is promoted. This surface state and reaction mechanism were rarely reported before and would provide more insights into the DRM process under real reaction conditions and would help design more stable Ni catalysts.

Synergistic promotions between CO2 capture and in-situ conversion on Ni-CaO composite catalyst

The integrated CO₂ capture and conversion (iCCC) technology has been booming as a promising cost-effective approach for Carbon Neutrality. However, the lack of the long-sought molecular consensus about the synergistic effect between the adsorption and in-situ catalytic reaction hinders its development. Herein, we illustrate the synergistic promotions between CO₂ capture and in-situ conversion through constructing the consecutive high-temperature Calcium-looping and dry reforming of methane processes. With systematic experimental measurements and density functional theory calculations, we reveal that the pathways of the reduction of carbonate and the dehydrogenation of CH₄ can be interactively facilitated by the participation of the intermediates produced in each process on the supported Ni-CaO composite catalyst. Specifically, the adsorptive/catalytic interface, which is controlled by balancing the loading density and size of Ni nanoparticles on porous CaO, plays an essential role in the ultra-high CO₂ and CH₄ conversions of 96.5% and 96.0% at 650 °C, respectively.

First principles insights into the relative stability, electronic and catalytic properties of core-shell, Janus and mixed structural patterns for bimetallic Pd-X nano-alloys (X = Co, Ni, Cu, Rh, Ag, Ir, Pt, Au)

The three well-known orderings of the two constituting atomic species in a bimetallic nano-alloy - core-shell, Janus and mixed structural patterns - may be interconvertible depending on the synthesis conditions. Using first principles electronic structure calculations in the present work, we look for the microscopic origin for such structural transformation considering eight Pd-related bimetallic nano-alloys. Our analysis shows that it is the change in atom-atom covalency that is responsible for such structural transformation. Our study also reveals that the three patterns are distinctly identified in terms of total orbital hybridization. Finally, we have analyzed the trend in the relative catalytic activity for the three structures of each bimetallic nano-alloy using the d-band model. Our analysis indicates that the trend in the catalytic activity for the bimetallic Pd-X nano-alloys seems to be intermediate to those of the pristine Pd and Pt nano-clusters possessing similar structure and equal number of total atoms. Among the studied binary nano-alloys, the bimetallic Pd-Ni nano-alloy appears as the most suitable binary pair to develop a non-Pt catalyst.

Hydride Generation on the Cu-Doped CeO2(111) Surface and Its Role in CO2 Hydrogenation Reactions

Ceria-based catalysts exhibit great activity in catalyzing selective hydrogenation of CO2 to methanol. However, the underlying mechanism of this reaction, especially the generation of active H species, remains unclear. In this work, we performed extensive density functional theory calculations corrected by on-site Coulomb interaction (DFT + U) to investigate the H2 dissociation and the reaction between the active H species and CO2 on the pristine and Cu-doped CeO2(111) (denoted as Cu/CeO2(111)) surfaces. Our calculations evidenced that the heterolytic H2 dissociation for hydride generation can more readily occur on the Cu/CeO2(111) surface than on the pristine CeO2(111) surface. We also found that the Cu dopant can facilitate the formation of surface oxygen vacancies, further promoting the generation of hydride species. Moreover, the adsorption of CO2 and the hydrogenation of CO2 to HCOO* can be greatly promoted on the Cu/CeO2(111) surface with hydride species, which can lead to the high activity and selectivity toward CO2 hydrogenation to methanol.

Graphene as an Adsorption Template for Studying Double Bond Activation in Catalysis

Hydrogenated graphene (H-Gr) is an extensively studied system not only because of its capabilities as a simplified model system for hydrocarbon chemistry but also because hydrogenation is a compelling method for Gr functionalization. However, knowledge of how H-Gr interacts with molecules at higher pressures and ambient conditions is lacking. Here we present experimental and theoretical evidence that room temperature O₂ exposure at millibar pressures leads to preferential removal of H dimers on H-functionalized graphene, leaving H clusters on the surface. Our density functional theory (DFT) analysis shows that the removal of H dimers is the result of water or hydrogen peroxide formation. For water formation, we show that the two H atoms in the dimer motif attack one end of the physisorbed O₂ molecule. Moreover, by comparing the reaction pathways in a vacuum with the ones on free-standing graphene and on the graphene/Ir(111) system, we find that the main role of graphene is to arrange the H atoms in geometrical positions, which facilitates the activation of the O=O double bond.

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.

A unique Co@CoO catalyst for hydrogenolysis of biomass-derived 5-hydroxymethylfurfural to 2,5-dimethylfuran

The development of precious-metal-free catalysts to promote the sustainable production of fuels and chemicals from biomass remains an important and challenging target. Here, we report the efficient hydrogenolysis of biomass-derived 5-hydroxymethylfurfural to 2,5-dimethylfuran over a unique core-shell structured catalyst, Co@CoO that affords the highest productivity among all catalysts, including noble-metal-based catalysts, reported to date. Surprisingly, we find that the catalytically active sites reside on the shell of CoO with oxygen vacancies rather than the metallic Co. The combination of various spectroscopic experiments and computational modelling reveals that the CoO shell incorporating oxygen vacancies not only drives the heterolytic cleavage, but also the homolytic cleavage of H₂ to yield more active H^δ− species, resulting in the exceptional catalytic activity. Co@CoO also exhibits excellent activity toward the direct hydrodeoxygenation of lignin model compounds. This study unlocks, for the first time, the potential of simple metal-oxide-based catalysts for the hydrodeoxygenation of renewable biomass to chemical feedstocks.

The development of precious-metal-free catalysts to promote the sustainable production of fuels and chemicals from biomass challenging. Here the authors report a unique core-shell structured Co@CoO catalyst which exhibits excellent performance in the hydrogenolysis of biomass-derived compounds.

A Universal Descriptor for Complicated Interfacial Effects on Electrochemical Reduction Reactions

Supported catalysts have exhibited excellent performance in various reactions. However, the rational design of supported catalysts with high activity and certain selectivity remains a great challenge because of the complicated interfacial effects. Using recently emerged two-dimensional materials supported dual-atom catalysts (DACs@2D) as a prototype, we propose a simple and universal descriptor based on inherent atomic properties (electronegativity, electron type, and number), which can well evaluate the complicated interfacial effects on the electrochemical reduction reactions (i.e., CO₂, O₂, and N₂ reduction reactions). Based on this descriptor, activity and selectivity trends in CO₂ reduction reaction are successfully elucidated, in good agreement with available experimental data. Moreover, several potential catalysts with superior activity and selectivity for target products are predicted, such as CuCr/g-C₃N₄ for CH₄ and CuSn/N-BN for HCOOH. More importantly, this descriptor can also be extended to evaluate the activity of DACs@2D for O₂ and N₂ reduction reactions, with very small errors between the prediction and reported experimental/computational results. This work provides feasible principles for the rational design of advanced electrocatalysts and the construction of universal descriptors based on inherent atomic properties.

Towards the rational design of Pt-based alloy catalysts for the low-temperature water-gas shift reaction: from extended surfaces to single atom alloys

The rational design of Pt-based catalysts for the low-temperature water-gas-shift (LT-WGS) reaction is an active research field because of its important role played in the fuel cell-based hydrogen economy, especially in mobile applications. Previous theoretical analyses have suggested that Pt alloys, leading to a weaker CO binding affinity than the Pt metal, could help alleviate CO poisoning and thus should be promising catalysts of the LT-WGS reaction. However, experimental research along this line was rather ineffective in the past decade. In the present work, we employed the state-of-the-art kinetic Monte Carlo (KMC) simulations to examine the influences of the electronic effect by introducing sub-surface alloys and/or core–shell structures, and the synergetic effect by introducing single atom alloys on the catalytic performance of Pt-alloy catalysts. Our KMC simulations have highlighted the importance of the OH binding affinity on the catalyst surfaces to reduce the barrier of water dissociation as the rate determining step, instead of the CO binding affinity as has been emphasized before in conventional mean-field kinetic models. Along this new direction of catalyst design, we found that Pt–Ru synergetic effects can significantly increase the activity of the Pt metal, leading to Ru_1–3@Pt alloys with a tetrahedron site of one surface-three subsurface Ru atoms on the Pt host, showing a turnover frequency of about five orders of magnitude higher than the Pt metal.

KMC simulations show that decreasing the barrier of H₂O decomposition is more beneficial than decreasing the CO binding affinity in LT-WGS, while the latter was overemphasized by MF-MKM. Here Ru_1–3@Pt alloy is proposed as a promising catalyst.

Applications of Machine Learning in Alloy Catalysts: Rational Selection and Future Development of Descriptors

At present, alloys have broad application prospects in heterogeneous catalysis, due to their various catalytic active sites produced by their vast element combinations and complex geometric structures. However, it is the diverse variables of alloys that lead to the difficulty in understanding the structure-property relationship for conventional experimental and theoretical methods. Fortunately, machine learning methods are helpful to address the issue. Machine learning can not only deal with a large number of data rapidly, but also help establish the physical picture of reactions in multidimensional heterogeneous catalysis. The key challenge in machine learning is the exploration of suitable general descriptors to accurately describe various types of alloy catalysts, which help reasonably design catalysts and efficiently screen candidates. In this review, several kinds of machine learning methods commonly used in the design of alloy catalysts is introduced, and the applications of various reactivity descriptors corresponding to different alloy systems is summarized. Importantly, this work clarifies the existing understanding of physical picture of heterogeneous catalysis, and emphasize the significance of rational selection of universal descriptors. Finally, the development of heterogeneous catalytic descriptors for machine learning are presented.

CO2—A Crisis or Novel Functionalization Opportunity?

The growing emission of carbon dioxide (CO2), combined with its ecotoxicity, is the reason for the intensification of research on the new technology of CO2 management. Currently, it is believed that it is not possible to eliminate whole CO2 emissions. However, a sustainable balance sheet is possible. The solution is technologies that use carbon dioxide as a raw material. Many of these methods are based on CO2 methanation, for example, projects such as Power-to-Gas, production of fuels, or polymers. This article presents the concept of using CO2 as a raw material, the catalytic conversion of carbon dioxide to methane, and consideration on CO2 methanation catalysts and their design.

Insights into reaction mechanisms of ethanol electrooxidation at the Pt/Au(111) interfaces using density functional theory

Understanding ethanol electrooxidation reaction kinetics is fundamental to the development of direct ethanol fuel cells.