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

Evans-Polanyi-like Formulations for Rapidly Predicting Key Depolymerization Barriers in Xylopyranoses: Toward the Faster Development of Kinetic Models for Hemicellulose Pyrolysis

This work elucidates Evans-Polanyi-like (EPL) relations to rapidly estimate the standard activation enthalpy of three ubiquitous reaction classes playing a central role in hemicellulose pyrolysis: ring-opening, ring contraction, and elimination. These models bypass computing the reaction enthalpy by leveraging computationally cheap local and global electron-density-based chemical reactivity descriptors, such as Fukui's functions (f), electron population of C-O bonds (N), and the gross intrinsic strength bond index (Δgpair), evaluated for reactants solely. More than 270 reactions observed in twenty-eight functionalized β-d-xylopyranoses, the hemicellulose building block, are used under the 20-80% partition scheme for validating-deriving purposes. By using multilinear regression analysis, four EPL equations are proposed for informing barriers at the M06-2X/6-311++G(d,p), CBS-QB3, G4, and DLPNO-CCSD(T)-F12/cc-pVTZ-F12//M06-2X/6-311++G(d,p) levels. An adjusted coefficient of determination of 0.80 characterizes these parametric polynomials. Moreover, MAE and RMSE of ≈3.3 and ≈4.1 kcal mol-1 describe the performance of the best-fitting models at DFT and G4. Conversely, the highest values, MAE = 3.6 and RMSE = 4.7 kcal mol-1, are associated with the CBS-QB3 level. The benchmarking of the computed activation enthalpies at 298 K yields simple functions for high-level estimations from low levels of theory with R2 ranging from 0.94 to 0.98. Extrapolating the DPLNO barriers to the complete basis set limit tends to lower them by 0.63 kcal mol-1. EPL expressions are tailored to facilitate the development of chemical kinetic models for hemicellulose pyrolysis, as the reactant structure is the only input required.

Stable Ni(II) sites in Prussian blue analogue for selective, ampere-level ethylene glycol electrooxidation

The industrial implementation of coupled electrochemical hydrogen production systems necessitates high power density and high product selectivity for economic viability and safety. However, for organic nucleophiles (e.g., methanol, urea, and amine) electrooxidation in the anode, most catalytic materials undergo unavoidable reconstruction to generate high-valent metal sites under harsh operation conditions, resulting in competition with oxygen evolution reaction. Here, we present unique Ni(II) sites in Prussian blue analogue (NiFe-sc-PBA) that serve as stable, efficient and selective active sites for ethylene glycol (EG) electrooxidation to formic acid, particularly at ampere-level current densities. Our in situ/operando characterizations demonstrate the robustness of Ni(II) sites during EG electrooxidation. Molecular dynamics simulations further illustrate that EG molecule tends to accumulate on the NiFe-sc-PBA surface, preventing hydroxyl-induced reconstruction in alkaline solutions. The stable Ni(II) sites in NiFe-sc-PBA anodes exhibit efficient and selective EG electrooxidation performance in a coupled electrochemical hydrogen production flow cell, producing high-value formic acid compared to traditional alkaline water splitting. The coupled system can continuously operate at stepwise ampere-level current densities (switchable 1.0 or 1.5 A cm-2) for over 500 hours without performance degradation.

Cu supraparticles with enhanced mass transfer and abundant C-C coupling sites achieving ampere-level CO2-to-C2+ electrosynthesis

The efficient electrochemical CO2 reduction to C2+ products at high current densities remains a significant challenge. Here we show inherently hydrophobic and hierarchically porous Cu supraparticles comprising sub-10 nm Cu constituent particles for ampere-level CO2-to-C2+ electrosynthesis. These supraparticles feature abundant grain boundaries for high C2+ selectivity, coupled with interconnected mesopores and interparticle macropore cavities to enhance the accessibility of the active sites and mass transfer, breaking the trade-off between activity and mass transfer in Cu-based catalysts. Moreover, the intrinsic hydrophobicity of the supraparticles mitigates the water-flooding issue of catalytic layer in flow cells, improving the stability at high current densities. Consequently, the Cu supraparticles achieve ampere-level CO2 electrolysis up to 3.2 A cm-2 with a C2+ Faradaic efficiency of 74.9% (compared to 1.21 A cm-2 and 55.4% for Cu nanoparticles) and maintain stability at 1 A cm-2 for over 100 h. This work provides profound insights into the effect of the coupling of mass transfer and catalytic reaction under a high current and presents a corresponding solution by superstructure design.

Isotopic labelling of water reveals the hydrogen transfer route in electrochemical CO2 reduction

Understanding the hydrogenation pathway in electrochemical CO2 reduction is important for controlling product selectivity. The Eley-Rideal mechanism involving proton-coupled electron transfer directly from solvent water is often considered to be the primary hydrogen transfer route. However, in principle, hydrogenation can also occur via the Langmuir-Hinshelwood mechanism using surface-adsorbed *H. Here, by performing CO2 reduction with Cu in H2O-D2O mixtures, we present evidence that the Langmuir-Hinshelwood mechanism is probably the dominant hydrogenation route. From this, we estimate the extent to which each mechanism contributes towards the formation of six important CO2 reduction products. Through computational simulations, we find that the formation of C-H bonds and O-H bonds is governed by the Langmuir-Hinshelwood and Eley-Rideal mechanism, respectively. We also show that promoting the Eley-Rideal pathway could be crucial towards selective multicarbon product formation and suppressing hydrogen evolution. These findings introduce important considerations for the theoretical modelling of CO2 reduction pathways and electrocatalyst design.

Inherent strain and kinetic coupling determine the kinetics of ammonia synthesis over Ru nanoparticles

The large-scale ammonia synthesis using the Haber-Bosch process is crucial in modern society and the reaction is known to be facile over Ru-based catalysts. Herein, first-principles kinetic Monte Carlo (kMC) simulations are utilized to explore the reaction kinetics on Ru nanoparticles (NPs), extending the current knowledge that is mainly based on calculations of single crystal surfaces. It is only by accounting for the effects of kinetic couplings between different sites and inherent strain in the NPs that experimental turnover frequencies (TOFs) can be reproduced. The enhanced activity of inherently strained NPs is attributed to the co-existence of sites with both tensile and compressive strain, which simultaneously promotes N2 dissociation and NHx (x = 0, 1 and 2) hydrogenation. We propose that kinetic couplings on Ru NPs with tailored strain-patterns offer a strategy to break the limitations of linear scaling relations in the design of ammonia synthesis catalysts.

A technique for analyzing the variability of activation thermodynamic and solvent model parameters

The fundamental thermodynamic equation of chemical kinetics has recently been used to analyze rate data from the hydrolysis reaction of tert-butyl chloride in the acetonitrile/water solvent system. Although this study showcased the deeper level of insight afforded from the fundamental equation, at the time of the publication no technique had been developed for analyzing the functional dependencies of the activation thermodynamic and solvent model parameters. We have since developed a three-step technique briefly described as follows. The first step includes conducting a linear regression analysis using a linearized form of the fundamental equation to determine if the parameters are constant. The second step includes a technique for evaluating the functional forms of the parameters if they are not constant, and the third step includes a technique for constructing parameter grid equations. The three-step analysis has been applied to some of the rate data from our studies on the tert-butyl chloride hydrolysis reaction. The results show the intrinsic activation entropy and Kirkwood-Onsager parameter depend on the electrostatic environment of the bulk solvent and the close-range interactions associated with the solvation shell. Auxiliary topics also presented in this article include an analysis showing mathematical expressions for intrinsic parameters cannot be evaluated, a discussion on the modeling benefits of the fundamental equation, and presentation of an empirical expression that correlates the solvent mole fraction term with the effect of the solvation shell.

Transition-Metal-Doped CeO2 for the Reverse Water-Gas Shift Reaction: An Experimental and Theoretical Study on CO2 Adsorption and Surface Vacancy Effects

Transition metal-doped ceria (M-CeO2) catalysts (M=Fe, Co, Ni and Cu) with multiple loadings were experimentally investigated for reverse water gas shift (RWGS) reaction. Density functional theory (DFT) calculations were performed to benchmark the properties that impact catalytic activity of CO2 reduction. Temperature-programmed desorption (TPD) was conducted to study the CO2 binding strength on doped CeO2 surfaces; the trend of the energy along increasing metal loading agrees with the DFT calculations. Notably, CO2 dissociative adsorption energy and oxygen vacancy (OV) formation energy are key descriptors obtained from both DFT and experiments, which can be used to evaluate catalytic performance. Results show the effectiveness of transition metal doping in enhancing CO2 adsorption and reducibility of the surfaces, with Fe showing particularly promising results, i. e., CO2 conversion higher than 56 % at 600 °C and 100 % selectivity to CO. Cu exhibits 100 % selectivity to CO but low CO2 conversion, while Co and Ni showed notable ability of methanation, particularly at high loadings. This study finds that an effective CeO2 based RWGS catalyst corresponds to OV sites that have low OV formation energies for surface reduction, and moderate CO2 adsorption energies for strong interaction with the surface to promote C-O bond scission.

Tackling the Activity Trend of Metal-Loaded Metal Nitride Catalysts for NH3 Synthesis by a First-Principles Microkinetic Study

Ammonia (NH3) is one of the most widely produced chemicals globally, primarily synthesized through the Haber-Bosch process, which requires high temperatures and pressures. Dual-site catalysts can activate N2 and H2 at spatially separated sites, enabling efficient NH3 synthesis under milder conditions. Despite the rapid experimental progress of the dual-site catalysts (e.g., Ni-LaN), the feasibility and design of dual-site catalysts are challenged recently. Herein, the different metal-loaded metal nitride catalyst models are employed, and their activity map for NH3 synthesis is explored by the first-principles microkinetic simulation. The optimum active region of this type of dual-site catalyst is identified in terms of the formation energy (Ev) of nitrogen vacancy (Nvac) on metal nitride and the adsorption energy (EH) of hydrogen atom on metal cluster, with Ev and EH ideally located around ≈1.50 and ≈-0.30 eV, respectively. This offers a framework for designing effective metal-loaded metal nitride catalysts for NH3 synthesis. Importantly, this trend aligns with and rationalizes the current experimental observations of metal-loaded metal nitride reported for NH3 synthesis. This theoretical work provides significant insights into NH3 synthesis on dual-site mechanism, and provides a rational direction for designing metal-loaded metal nitride catalysts.

First-principles-based microkinetic modeling of methanol steam reforming over Cu(111) and Cu(211): structure sensitive activity and selectivity

The development of hydrogen energy is widely recognized as a key approach to addressing the energy and carbon emission challenges. Methanol steam reforming is a promising hydrogen production scheme that can provide high-purity hydrogen. In this work, we studied the primary reaction mechanisms of methanol steam reforming over the Cu(111) and Cu(211) surfaces using density functional theory (DFT) calculations and microkinetic simulations. A detailed kinetic perspective on the reaction mechanism, which is often overlooked in previous research that relies solely on DFT calculations, is provided in the current work. Our findings reveal that under typical experimental conditions, the dominant mechanism on the Cu(111) surface is the methyl formate mechanism, while the H2COO dehydrogenation mechanism is dominant on Cu(211). The activity over the Cu(111) surface was slightly higher than that over Cu(211). Based on the degree of rate control analysis results, a reaction rate equation was derived to quantitatively explain the trend of activity under different operating conditions. It was also found that CO2 selectivity was significantly higher over Cu(211) than over the Cu(111) surface. Furthermore, based on the Wulff construction scheme, copper nanoparticle models with different sizes were constructed, and a detailed structure sensitivity study was executed. This comprehensive investigation sheds light on the mechanisms of methanol steam reforming reactions over the Cu(111) and Cu(211) surfaces, providing essential insights for the design of high-performance catalysts for hydrogen production.

Mechanistic insights into NH3-assisted selective reduction of NO on CeO2: a first-principles microkinetic study on selectivity and activity

To understand the activity- and selectivity-limiting factors of selective catalytic reduction of NO with NH3 (NH3-SCR) catalyzed by CeO2-based oxides, a molecular-level mechanistic exploration was performed on CeO2(110) using a first-principles microkinetic study. Herein, the favored reaction pathway for N2 formation on CeO2(110) is unveiled, which includes three key subprocesses. (i) NH3 adsorbs on the Cecus site and dissociates into *NH2 assisted by Olat; (ii) *NH2 preferentially couples with NO adsorbed on Olat (ONO#), forming *NH2NO on the Cecus site; (iii) *NH2NO undergoes dehydrogenation into *NHNO, which can be easily anchored by Ovac and can then decompose into N2. The quantitative microkinetic results show that the transfer of NHNO from Cecus to Ovac, rather than the further conversion of N2O to N2 on Ovac, emerges as the N2 selectivity-determining step on CeO2, in which Ovac plays a key role. The number of Ovac is an important factor determining the N2 selectivity of CeO2-based catalysts. The sensitivity analysis reveals that NH2NO formation, i.e., *NH2 + ONO# → *NH2NO + O#, is the rate-determining step for NH3-SCR on the CeO2 catalyst; accordingly, enhancing NH3 adsorption could be an effective strategy to boost the catalytic activity of CeO2 for NH3-SCR. In general, creating Ovac on CeO2 and introducing components (e.g., WO3) with strong NH3 adsorption would be efficient for designing CeO2-based catalysts with superior N2 selectivity and activity. These results could provide a consolidated theoretical basis for understanding and optimizing CeO2-based catalysts for NH3-SCR.

Bringing Molecules Together: Synergistic Coadsorption at Dopant Sites of Single Atom Alloys

Bringing molecules together on a catalytic surface is a prerequisite for bimolecular and recombination reactions. However, in the absence of attractive interactions between reactants, such as hydrogen bonds, this poses a challenge. In contrast, based on density functional theory, we show that coadsorption at active sites of single-atom alloys (SAAs) is favored and that coadsorption is a general phenomenon observed for catalytically relevant adsorbates on a broad range of SAAs under temperature and pressure conditions commonly employed for catalysis. Dopants located in both terrace sites and in step edge defects exhibit a preference for coadsorption, displaying similar periodic trends. Using kinetic Monte Carlo simulations, we compare the reactivity of a model reaction on both a pure metal and an SAA and show that the preference for coadsorption significantly alters the overall reaction energy profile, even when the barriers for the rate-determining elementary step are identical. In our models, the coadsorption preference enhances the catalytic activity of the SAA surface by several orders of magnitude compared to the pure metal. We also report infrared (IR) spectroscopic signatures of coadsorption, which facilitate experimental detection. Analysis reveals that in these systems repulsive lateral interactions between nearby molecules are more than compensated for by the enhanced binding at dopant sites. Among the broad range of systems considered, SAAs containing early transition metals (TMs) exhibit the strongest coadsorption preference, which can be rationalized by assuming the existence of an optimal number of electrons involved in binding. The strong coadsorption preference, together with facile product desorption from early TMs, renders these systems attractive candidates for catalysis. Moreover, these SAAs could open new routes for reduction reactions because coadsorption with hydrogen is favored.

Interpretable Data-Driven Descriptors for Establishing the Structure-Activity Relationship of Metal-Organic Frameworks Toward Oxygen Evolution Reaction

The development of readily accessible and interpretable descriptors is pivotal yet challenging in the rational design of metal-organic framework (MOF) catalysts. This study presents a straightforward and physically interpretable activity descriptor for the oxygen evolution reaction (OER), derived from a dataset of bimetallic Ni-based MOFs. Through an artificial-intelligence (AI) data-mining subgroup discovery (SGD) approach, a combination of the d-band center and number of missing electrons in eg states of Ni, as well as the first ionization energy and number of electrons in eg states of the substituents, is revealed as a gene of a superior OER catalyst. The found descriptor, obtained from the AI analysis of a dataset of MOFs containing 3-5d transition metals and 13 organic linkers, has been demonstrated to facilitate in-depth understanding of structure-activity relationship at the molecular orbital level. The descriptor is validated experimentally for 11 Ni-based MOFs. Combining SGD with physical insights and experimental verification, our work offers a highly efficient approach for screening MOF-based OER catalysts, simultaneously providing comprehensive understanding of the catalytic mechanism.

Atomically Engineered Chlorine Coordination of Iron in Active Centers for Selectively Catalytic H2O2 Decomposition Toward Efficient Antitumor-Specific Therapy

The intervention of endogenous H2O2 via nanozymes provides a potential antitumor-specific therapy; however, the role of the nanozyme structure in relation to the selective decomposition of H2O2 to hydroxyl radicals (•OH) is yet to be fully understood, which limits the development of this therapeutic approaches. Herein, an iron single-atom nanozyme (Fe─N2Cl2─C SAzyme) is reported, which is prepared through precise Fe─Cl coordination based on the construction of a characteristic Fe-containing molecule. Fe─N2Cl2─C exhibits efficient catalytic H2O2 decomposition (2.19 × 106 mm-1 s-1), which is the highest among reported SAzymes. More importantly, it is found that H2O2 selectively decomposed into •OH on the Fe─N2Cl2─C surface, which is attributable to the d orbitals of the Fe active center matching the O-2p electrons of the adsorbed hydroxide (*OH) intermediate. Fe─N2Cl2─C is strongly cytotoxic toward a variety of cancer-cell lines in vitro but not to normal cells. Furthermore, Fe─N2Cl2─C shows an outstanding specific therapeutic effect in vivo; it efficiently destroys solid malignant tumors without injuring normal tissue. Altogether, these findings highlight the selective catalytic decomposition of H2O2 to •OH, which is achieved by engineering the active center on the atomic level, thereby providing an avenue for the development of specific nanomedicines with efficient antitumor activities.

Mechanistic insights into CO2 hydrogenation to methanol on Cu(110): unveiling energy linear relationships and enhancing performance strategies

The study of energy correlations in catalytic reactions plays a pivotal role in guiding catalyst development. This paper focuses on the investigation of energy linear relationships in methanol synthesis from CO2 hydrogenation on copper surfaces, systematically exploring energy parameters including activation energy, reaction energy and adsorption energy. A comparative analysis of the adsorption characteristics and reaction parameters in the formate, formic acid and reverse water-gas shift pathways is conducted, laying the data foundation for subsequent linear studies. Then, descriptors are extracted from electronic, energetic and structural information and further integrated using the sure independence screening and sparsifying operator (SISSO) method to establish an energy description paradigm characterized by interpretability and accuracy. Additionally, reactions are further categorized based on hydrogenation types to mitigate the adverse effects of redundant data points. Finally, the summarized reaction descriptors are extended to Cu-based alloy systems to highlight the rationality and transferability of the developed descriptors.

Optimizing the Lattice Nitrogen Coordination to Break the Performance Limitation of Metal Nitrides for Electrocatalytic Nitrogen Reduction

Metal nitrides (MNs) are attracting enormous attention in the electrocatalytic nitrogen reduction reaction (NRR) because of their rich lattice nitrogen (Nlat) and the unique ability of Nlat vacancies to activate N2. However, continuing controversy exists on whether MNs are catalytically active for NRR or produce NH3 via the reductive decomposition of Nlat without N2 activation in the in situ electrochemical conditions, let alone the rational design of high-performance MN catalysts. Herein, we focus on the common rocksalt-type MN(100) catalysts and establish a quantitative theoretical framework based on the first-principles microkinetic simulations to resolve these puzzles. The results show that the Mars-van Krevelen mechanism is kinetically more favorable to drive the NRR on a majority of MNs, in which Nlat plays a pivotal role in achieving the Volmer process and N2 activation. In terms of stability, activity, and selectivity, we find that MN(100) with moderate formation energy of Nlat vacancy (E vac) can achieve maximum activity and maintain electrochemical stability, while low- or high-E vac ones are either unstable or catalytically less active. Unfortunately, owing to the five-coordinate structural feature of Nlat on rocksalt-type MN(100), this maximum activity is limited to a yield of NH3 of only ∼10-15 mol s-1 cm-2. Intriguingly, we identify a volcano-type activity-regulating role of the local structural features of Nlat and show that the four-coordinate Nlat can exhibit optimal activity and overcome the performance limitation, while less coordinated Nlat fails. This work provides, arguably for the first time, an in-depth theoretical insight into the activity and stability paradox of MNs for NRR and underlines the importance of reaction kinetic assessment in comparison with the prevailing simple thermodynamic analysis.

Toward Realistic Models of the Electrocatalytic Oxygen Evolution Reaction

The electrocatalytic oxygen evolution reaction (OER) supplies the protons and electrons needed to transform renewable electricity into chemicals and fuels. However, the OER is kinetically sluggish; it operates at significant rates only when the applied potential far exceeds the reversible voltage. The origin of this overpotential is hidden in a complex mechanism involving multiple electron transfers and chemical bond making/breaking steps. Our desire to improve catalytic performance has then made mechanistic studies of the OER an area of major scientific inquiry, though the complexity of the reaction has made understanding difficult. While historically, mechanistic studies have relied solely on experiment and phenomenological models, over the past twenty years ab initio simulation has been playing an increasingly important role in developing our understanding of the electrocatalytic OER and its reaction mechanisms. In this Review we cover advances in our mechanistic understanding of the OER, organized by increasing complexity in the way through which the OER is modeled. We begin with phenomenological models built using experimental data before reviewing early efforts to incorporate ab initio methods into mechanistic studies. We go on to cover how the assumptions in these early ab initio simulations─no electric field, electrolyte, or explicit kinetics─have been relaxed. Through comparison with experimental literature, we explore the veracity of these different assumptions. We summarize by discussing the most critical open challenges in developing models to understand the mechanisms of the OER.

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 %.

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.

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.