A Universal Descriptor for the Screening of Electrode Materials for Multiple-Electron Processes: Beyond the Thermodynamic Overpotential

Hierarchical Modeling of the Local Reaction Environment in Electrocatalysis

ConspectusElectrocatalytic reactions, such as oxygen reduction/evolution reactions and CO2 reduction reaction that are pivotal for the energy transition, are multistep processes that occur in a nanoscale electric double layer (EDL) at a solid-liquid interface. Conventional analyses based on the Sabatier principle, using binding energies or effective electronic structure properties such as the d-band center as descriptors, are able to grasp overall trends in catalytic activity in specific groups of catalysts. However, thermodynamic approaches often fail to account for electrolyte effects that arise in the EDL, including pH, cation, and anion effects. These effects exert strong impacts on electrocatalytic reactions. There is growing consensus that the local reaction environment (LRE) prevailing in the EDL is the key to deciphering these complex and hitherto perplexing electrolyte effects. Increasing attention is thus paid to designing electrolyte properties, positioning the LRE at center stage. To this end, unraveling the LRE is becoming essential for designing electrocatalysts with specifically tailored properties, which could enable much needed breakthroughs in electrochemical energy science.Theory and modeling are getting more and more important and powerful in addressing this multifaceted problem that involves physical phenomena at different scales and interacting in a multidimensional parametric space. Theoretical models developed for this purpose should treat intrinsic multistep kinetics of electrocatalytic reactions, EDL effects from subnm scale to the scale of 10 nm, and mass transport phenomena bridging scales from <0.1 to 100 μm. Given the diverse physical phenomena and scales involved, it is evident that the challenge at hand surpasses the capabilities of any single theoretical or computational approach.In this Account, we present a hierarchical theoretical framework to address the above challenge. It seamlessly integrates several modules: (i) microkinetic modeling that accounts for various reaction pathways; (ii) an LRE model that describes the interfacial region extending from the nanometric EDL continuously to the solution bulk; (iii) first-principles calculations that provide parameters, e.g., adsorption energies, activation barriers and EDL parameters. The microkinetic model considers all elementary steps without designating an a priori rate-determining step. The kinetics of these elementary steps are expressed in terms of local concentrations, potential and electric field that are codetermined by EDL charging and mass transport in the LRE model. Vital insights on electrode kinetic phenomena, i.e., potential-dependent Tafel slopes, cation effects, and pH effects, obtained from this hierarchical framework are then reviewed. Finally, an outlook on further improvement of the model framework is presented, in view of recent developments in first-principles based simulation of electrocatalysis, observations of dynamic reconstruction of catalysts, and machine-learning assisted computational simulations.

Recent Advances in Revealing the Electrocatalytic Mechanism for Hydrogen Energy Conversion System

In light of the intensifying global energy crisis and the mounting demand for environmental protection, it is of vital importance to develop advanced hydrogen energy conversion systems. Electrolysis cells for hydrogen production and fuel cell devices for hydrogen utilization are indispensable in hydrogen energy conversion. As one of the electrolysis cells, water splitting involves two electrochemical reactions, hydrogen evolution reaction and oxygen evolution reaction. And oxygen reduction reaction coupled with hydrogen oxidation reaction, represent the core electrocatalytic reactions in fuel cell devices. However, the inherent complexity and the lack of a clear understanding of the structure-performance relationship of these electrocatalytic reactions, have posed significant challenges to the advancement of research in this field. In this work, the recent development in revealing the mechanism of electrocatalytic reactions in hydrogen energy conversion systems is reviewed, including in situ characterization and theoretical calculation. First, the working principles and applications of operando measurements in unveiling the reaction mechanism are systematically introduced. Then the application of theoretical calculations in the design of catalysts and the investigation of the reaction mechanism are discussed. Furthermore, the challenges and opportunities are also summarized and discussed for paving the development of hydrogen energy conversion systems.

Emerging Atomistic Modeling Methods for Heterogeneous Electrocatalysis

Heterogeneous electrocatalysis lies at the center of various technologies that could help enable a sustainable future. However, its complexity makes it challenging to accurately and efficiently model at an atomic level. Here, we review emerging atomistic methods to simulate the electrocatalytic interface with special attention devoted to the components/effects that have been challenging to model, such as solvation, electrolyte ions, electrode potential, reaction kinetics, and pH. Additionally, we review relevant computational spectroscopy methods. Then, we showcase several examples of applying these methods to understand and design catalysts relevant to green hydrogen. We also offer experimental views on how to bridge the gap between theory and experiments. Finally, we provide some perspectives on opportunities to advance the field.

Four Generations of Volcano Plots for the Oxygen Evolution Reaction: Beyond Proton-Coupled Electron Transfer Steps?

ConspectusDue to its importance for electrolyzers or metal-air batteries for energy conversion or storage, there is huge interest in the development of high-performance materials for the oxygen evolution reaction (OER). Theoretical investigations have aided the search for active material motifs through the construction of volcano plots for the kinetically sluggish OER, which involves the transfer of four proton-electron pairs to form a single oxygen molecule. The theory-driven volcano approach has gained unprecedented popularity in the catalysis and energy communities, largely due to its simplicity, as adsorption free energies can be used to approximate the electrocatalytic activity by heuristic descriptors.In the last two decades, the binding-energy-based volcano method has witnessed a renaissance with special concepts being developed to incorporate missing factors into the analysis. To this end, this Account summarizes and discusses the different generations of volcano plots for the example of the OER. While first-generation methods relied on the assessment of the thermodynamic information for the OER reaction intermediates by means of scaling relations, the second and third generations developed strategies to include overpotential and kinetic effects into the analysis of activity trends. Finally, the fourth generation of volcano approaches allowed the incorporation of various mechanistic pathways into the volcano methodology, thus paving the path toward data- and mechanistic-driven volcano plots in electrocatalysis.Although the concept of volcano plots has been significantly expanded in recent years, further research activities are discussed by challenging one of the main paradigms of the volcano concept. To date, the evaluation of activity trends relies on the assumption of proton-coupled electron transfer steps (CPET), even though there is experimental evidence of sequential proton-electron transfer (SPET) steps. While the computational assessment of SPET for solid-state electrodes is ambitious, it is strongly suggested to comprehend their importance in energy conversion and storage processes, including the OER. This can be achieved by knowledge transfer from homogeneous to heterogeneous electrocatalysis and by focusing on the material class of single-atom catalysts in which the active center is well defined. The derived concept of how to analyze the importance of SPET for mechanistic pathways in the OER over solid-state electrodes could further shape our understanding of the proton-electron transfer steps at electrified solid/liquid interfaces, which is crucial for further progress toward sustainable energy and climate neutrality.

Why efficient bifunctional hydrogen electrocatalysis requires a change in the reaction mechanism

Hydrogen evolution reaction (HER) and hydrogen oxidation reaction (HOR) are both two-electron processes that culminate in the formation or consumption of gaseous hydrogen in an electrolyzer or a fuel cell, respectively. Unitized regenerative proton exchange membrane fuel cells merge these two functionalities into one device, allowing to switch between the two modes of operation. This prompts the quest for efficient bifunctional electrode materials catalyzing the HER and HOR with reasonable reaction rates at low overpotentials. In the present study using a data-driven framework, we identify a general criterion for efficient bifunctional performance in the hydrogen electrocatalysis, which refers to a change in the reaction mechanism when switching from cathodic to anodic working conditions. The obtained insight can be used in future studies based on density functional theory to pave the design of efficient HER and HOR catalysts by a dedicated consideration of the kinetics in the analysis of reaction mechanisms.

Two-Dimensional Tetragonal Transition Metal Chalcogenides for High Performance Oxygen Evolution and Reduction: A DFT Study

The pursuit of high-performance bifunctional catalysts for oxygen evolution/reduction (OER/ORR) has gained significant attention in the field of electrochemical water splitting and fuel cells. In this study, we employed density functional theory (DFT) calculations to investigate a series of 2D tetragonal TMX (TM=transition metal, X=S, Se, Te) monolayers as potential bifunctional electrocatalysts for OER/ORR. To evaluate the overall performance of OER electrocatalysts, we introduced a descriptor, Gmax. The Gmax values obtained for tetragonal CdS, CdSe, FeSe, NiSe, and NiTe monolayers were all below 1.0 V, indicative of their superior catalytic activity and selectivity. Moreover, NiSe displayed remarkable ORR capability with an overpotential (ηORR ) of 0.53 V. Based on the bifunctional index (BI), the catalytic activity ranking for the bifunctional catalysts is as follows: NiSe>NiTe>FeSe>CdS>CdSe>NiS>TiSe>ZnTe. These findings provide an insightful understanding of the electrocatalytic properties of 2D tetragonal TMX monolayers for OER/ORR, opening avenues for the future development of efficient bifunctional electrocatalysts based on 2D tetragonal transition metal chalcogenides.

Importance of the Walden Inversion for the Activity Volcano Plot of Oxygen Evolution

Since the birth of the computational hydrogen electrode approach, it is considered that activity trends of electrocatalysts in a homologous series can be quantified by the construction of volcano plots. This method aims to steer materials discovery by the identification of catalysts with an improved reaction kinetics, though evaluated by means of thermodynamic descriptors. The conventional approach for the volcano plot of the oxygen evolution reaction (OER) relies on the assumption of the mononuclear mechanism, comprising the * OH, * O, and * OOH intermediates. In the present manuscript, two new mechanistic pathways, comprising the idea of the Walden inversion in that bond-breaking and bond-making occurs simultaneously, are factored into a potential-dependent OER activity volcano plot. Surprisingly, it turns out that the Walden inversion plays an important role since the activity volcano is governed by mechanistic pathways comprising Walden steps rather than by the traditionally assumed reaction mechanisms under typical OER conditions.

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.

On the mechanistic complexity of oxygen evolution: potential-dependent switching of the mechanism at the volcano apex

The anodic four-electron oxygen evolution reaction (OER) corresponds to the limiting process in acidic or alkaline electrolyzers to produce gaseous hydrogen at the cathode of the device. In the last decade, tremendous efforts have been dedicated to the identification of active OER materials by electronic structure calculations in the density functional theory approximation. Most of these works rely on the assumption that the mononuclear mechanism, comprising the *OH, *O, and *OOH intermediates, is operative under OER conditions, and that a single elementary reaction step (most likely *OOH formation) governs the kinetics. In the present manuscript, six different OER mechanisms are analyzed, and potential-dependent volcano curves are constructed to comprehend the electrocatalytic activity of these pathways in the approximation of the descriptor G_max(U), a potential-dependent activity measure based on the notion of the free-energy span model. While the mononuclear description mainly describes the legs of the volcano plot, corresponding to electrocatalysts with low intrinsic activity, it is demonstrated that the preferred pathway at the volcano apex is a strong function of the applied electrode potential. The observed mechanistic complexity including a switch of the favored pathway with increasing overpotential sets previous investigations aiming at the identification of reaction mechanisms and limiting steps into question since the entire breadth of OER pathways was not accounted for. A prerequisite for future atomic-scale studies on highly active OER catalysts refers to the evaluation of several mechanistic pathways so that neither important mechanistic features are overlooked nor limiting steps are incorrectly determined.

Importance of broken geometric symmetry of single-atom Pt sites for efficient electrocatalysis

Platinum single-atom catalysts hold promise as a new frontier in heterogeneous electrocatalysis. However, the exact chemical nature of active Pt sites is highly elusive, arousing many hypotheses to compensate for the significant discrepancies between experiments and theories. Here, we identify the stabilization of low-coordinated Pt^II species on carbon-based Pt single-atom catalysts, which have rarely been found as reaction intermediates of homogeneous Pt^II catalysts but have often been proposed as catalytic sites for Pt single-atom catalysts from theory. Advanced online spectroscopic studies reveal multiple identities of Pt^II moieties on the single-atom catalysts beyond ideally four-coordinated Pt^II-N₄. Notably, decreasing Pt content to 0.15 wt.% enables the differentiation of low-coordinated Pt^II species from the four-coordinated ones, demonstrating their critical role in the chlorine evolution reaction. This study may afford general guidelines for achieving a high electrocatalytic performance of carbon-based single-atom catalysts based on other d⁸ metal ions.

Magnetic Moment Is an Effective Descriptor for Electrocatalytic Nitrogen Reduction Reaction on Two-Dimensional Organometallic Nanosheets

Electrocatalytic reduction of nitrogen to ammonia (eNRR) under ambient condition is a potential sustainable and promising alternative to the traditional Haber-Bosch process. However, this electrochemical transformation is limited by the high overpotential, poor selectivity, low efficiency, and low yield. Herein, a new class of two-dimensional (2D) organometallic nanosheets c-TM-TCNE (c = cross motif, TM = 3d/4d/5d transition metals, TCNE = tetracyanoethylene) were comprehensively investigated as potential electrocatalysts for eNRR through high-throughput screening combined with spin-polarized density functional theory computations. After a multistep screening and follow-up systematic evaluation, c-Mo-TCNE and c-Nb-TCNE were selected as eligible catalysts, and c-Mo-TCNE showed the lowest limiting potential of -0.35 V via a distal pathway, displaying high catalytic performance. In addition, the desorption of NH₃ from the surface of c-Mo-TCNE catalyst is also easy, with the free energy being 0.34 eV. Furthermore, the stability, metallicity, and eNRR selectivity are preeminent, making c-Mo-TCNE a promising catalyst. Unexpectedly, the magnetic moment of the transition metal shows a strong correlation with the catalytic activity (limiting potential), i.e., the larger the magnetic moment of the transition metal, the smaller the limiting potential of the electrocatalyst. The Mo atom has the largest magnetic moment and the c-Mo-TCNE catalyst features the smallest magnitude of limiting potential. Thus, the magnetic moment can be used as an effective descriptor for eNRR on c-TM-TCNE catalysts. The present study opens a way toward the rational design of highly efficient electrocatalysts for eNRR with novel two-dimensional functional materials. This work will promote further experimental efforts in this field.

Electrosynthesis of chlorine from seawater-like solution through single-atom catalysts

The chlor-alkali process plays an essential and irreplaceable role in the modern chemical industry due to the wide-ranging applications of chlorine gas. However, the large overpotential and low selectivity of current chlorine evolution reaction (CER) electrocatalysts result in significant energy consumption during chlorine production. Herein, we report a highly active oxygen-coordinated ruthenium single-atom catalyst for the electrosynthesis of chlorine in seawater-like solutions. As a result, the as-prepared single-atom catalyst with Ru-O₄ moiety (Ru-O₄ SAM) exhibits an overpotential of only ~30 mV to achieve a current density of 10 mA cm^-2 in an acidic medium (pH = 1) containing 1 M NaCl. Impressively, the flow cell equipped with Ru-O₄ SAM electrode displays excellent stability and Cl₂ selectivity over 1000 h continuous electrocatalysis at a high current density of 1000 mA cm^-2. Operando characterizations and computational analysis reveal that compared with the benchmark RuO₂ electrode, chloride ions preferentially adsorb directly onto the surface of Ru atoms on Ru-O₄ SAM, thereby leading to a reduction in Gibbs free-energy barrier and an improvement in Cl₂ selectivity during CER. This finding not only offers fundamental insights into the mechanisms of electrocatalysis but also provides a promising avenue for the electrochemical synthesis of chlorine from seawater electrocatalysis.

Expediting Oxygen Evolution by Optimizing Cation and Anion Complexity in Electrocatalysts Based on Metal Phosphorous Trichalcogenides

Purposely changing the rate-determining step (RDS) of oxygen evolution reaction (OER) remains a major challenge for enhancing the energy efficiency of electrochemical splitting of water. Here we show that the OER RDS can be regulated by simply varying the cation and anion complexity in a family of the metal phosphorous trichalcogenide electrocatalysts (MPT₃ , where M=Fe, Ni; T=S, Se), achieving an exceptionally high OER activity in (Ni,Fe)P(S,Se)₃ , as demonstrated by its ultra-low Tafel slope (34 mV dec^-1 ) and a very low overpotential compared to many relevant OER catalysts. This is strongly supported by density functional theory calculations, which showed that this catalyst has a nearly optimal OER activity descriptor value of ΔG(O*)-ΔG(OH*)=1.5 eV. We also found that the activity descriptor is proportional to a newly proposed cation/anion complexity index that consists of pairwise contributions from cation-anion bonds in a catalyst compound, revealing the pivotal role of the cation-anion interactions in determining the catalyst performance and providing a simple way for predicting catalytic activities.

How machine learning can accelerate electrocatalysis discovery and optimization

Advances in machine learning (ML) provide the means to bypass bottlenecks in the discovery of new electrocatalysts using traditional approaches. In this review, we highlight the currently achieved work in ML-accelerated discovery and optimization of electrocatalysts via a tight collaboration between computational models and experiments. First, the applicability of available methods for constructing machine-learned potentials (MLPs), which provide accurate energies and forces for atomistic simulations, are discussed. Meanwhile, the current challenges for MLPs in the context of electrocatalysis are highlighted. Then, we review the recent progress in predicting catalytic activities using surrogate models, including microkinetic simulations and more global proxies thereof. Several typical applications of using ML to rationalize thermodynamic proxies and predict the adsorption and activation energies are also discussed. Next, recent developments of ML-assisted experiments for catalyst characterization, synthesis optimization and reaction condition optimization are illustrated. In particular, the applications in ML-enhanced spectra analysis and the use of ML to interpret experimental kinetic data are highlighted. Additionally, we also show how robotics are applied to high-throughput synthesis, characterization and testing of electrocatalysts to accelerate the materials exploration process and how this equipment can be assembled into self-driven laboratories.

Steering Selectivity in the Four-Electron and Two-Electron Oxygen Reduction Reactions: On the Importance of the Volcano Slope

In the last decade, trends for competing electrocatalytic processes have been largely captured by volcano plots, which can be constructed by the analysis of adsorption free energies as derived from electronic structure theory in the density functional theory approximation. One prototypical example refers to the four-electron and two-electron oxygen reduction reactions (ORRs), resulting in the formation of water and hydrogen peroxide, respectively. The conventional thermodynamic volcano curve illustrates that the four-electron and two-electron ORRs reveal the same slopes at the volcano legs. This finding is related to two facts, namely, that only a single mechanistic description is considered in the model, and electrocatalytic activity is assessed by the concept of the limiting potential, a simple thermodynamic descriptor evaluated at the equilibrium potential. In the present contribution, the selectivity challenge of the four-electron and two-electron ORRs is analyzed, thereby accounting for two major expansions. First, different reaction mechanisms are included into the analysis, and second, G _max(U), a potential-dependent activity measure that factors overpotential and kinetic effects into the evaluation of adsorption free energies, is applied for approximation of electrocatalytic activity. It is illustrated that the slope of the four-electron ORR is not constant at the volcano legs but rather is prone to change as soon as another mechanistic pathway is energetically preferred or another elementary step becomes the limiting one. Due to the varying slope of the four-electron ORR volcano, a trade-off between activity and selectivity for hydrogen peroxide formation is observed. It is demonstrated that the two-electron ORR is energetically preferred at the left and right volcano legs, thus opening a new strategy for the selective formation of H₂O₂ by an environmentally benign route.

Materials Screening by the Descriptor G max(η): The Free-Energy Span Model in Electrocatalysis

To move from fossil-based energy resources to a society based on renewables, electrode materials free of precious noble metals are required to efficiently catalyze electrochemical processes in fuel cells, batteries, or electrolyzers. Materials screening operating at minimal computational cost is a powerful method to assess the performance of potential electrode compositions based on heuristic concepts. While the thermodynamic overpotential in combination with the volcano concept refers to the most popular descriptor-based analysis in the literature, this notion cannot reproduce experimental trends reasonably well. About two years ago, the concept of G _max(η), based on the idea of the free-energy span model, has been proposed as a universal approach for the screening of electrocatalysts. In contrast to other available descriptor-based methods, G _max(η) factors overpotential and kinetic effects by a dedicated evacuation scheme of adsorption free energies into an analysis of trends. In the present perspective, we discuss the application of G _max(η) to different electrocatalytic processes, including the oxygen evolution and reduction reactions, the nitrogen reduction reaction, and the selectivity problem of the competing oxygen evolution and peroxide formation reactions, and we outline the advantages of this screening approach over previous investigations.

Machine-Learning-Assisted Discovery of High-Efficient Oxygen Evolution Electrocatalysts

Iridium oxide (IrO₂) is the predominant electrocatalyst for the oxygen evolution reaction (OER), but its low efficiency and high cost limit its applications. In this work, we have developed a strategy by combination of high-throughput density functional theory (DFT) and machine learning (ML) techniques for material discovery on IrO₂-based electrocatalysts with enhanced OER activity. A total of 36 kinds of metal dopants are considered to substitute for Ir to form binary and ternary metal oxides, and the most stable surface structures are selected from a total of 4648 structures for OER activity evaluation. Utilizing the neural network language model (NNLM), we associate the atomic environment with the formation energies of crystals and free energies of OER intermediates, and finally a series of potential candidates have been screened as the superior OER catalysts. Our strategy could efficiently explore promising electrocatalysts, especially for evaluating complex multi-metallic compounds.

Heterostructured Core-Shell Ni-Co@Fe-Co Nanoboxes of Prussian Blue Analogues for Efficient Electrocatalytic Hydrogen Evolution from Alkaline Seawater

The rational construction of efficient and low-cost electrocatalysts for the hydrogen evolution reaction (HER) is critical to seawater electrolysis. Herein, trimetallic heterostructured core-shell nanoboxes based on Prussian blue analogues (Ni-Co@Fe-Co PBA) were synthesized using an iterative coprecipitation strategy. The same coprecipitation procedure was used for the preparation of the PBA core and shell, with the synthesis of the shell involving chemical etching during the introduction of ferrous ions. Due to its unique structure and composition, the optimized trimetallic Ni-Co@Fe-Co PBA possesses more active interfacial sites and a high specific surface area. As a result, the developed Ni-Co@Fe-Co PBA electrocatalyst exhibits remarkable electrocatalytic HER performance with small overpotentials of 43 and 183 mV to drive a current density of 10 mA cm^-2 in alkaline freshwater and simulated seawater, respectively. Operando Raman spectroscopy demonstrates the evolution of Co²⁺ from Co³⁺ in the catalyst during HER. Density functional theory simulations reveal that the H*-N adsorption sites lower the barrier energy of the rate-limiting step, and the introduced Fe species improve the electron mobility of Ni-Co@Fe-Co PBA. The charge transfer at the core-shell interface leads to the generation of H* intermediates, thereby enhancing the HER activity. By pairing this HER catalyst (Ni-Co@Fe-Co PBA) with another core-shell PBA OER catalyst (NiCo@A-NiCo-PBA-AA) reported by our group, the fabricated two-electrode electrolyzer was found to achieve high output current densities of 44 and 30 mA cm^-2 at a low voltage of 1.6 V in alkaline freshwater and simulated seawater, respectively, exhibiting remarkable durability over a 100 h test.

Microkinetic Analysis of the Oxygen Evolution Performance at Different Stages of Iridium Oxide Degradation

The microkinetics of the electrocatalytic oxygen evolution reaction substantially determines the performance in proton-exchange membrane water electrolysis. State-of-the-art nanoparticulated rutile IrO₂ electrocatalysts present an excellent trade-off between activity and stability due to the efficient formation of intermediate surface species. To reveal and analyze the interaction of individual surface processes, a detailed dynamic microkinetic model approach is established and validated using cyclic voltammetry. We show that the interaction of three different processes, which are the adsorption of water, one potential-driven deprotonation step, and the detachment of oxygen, limits the overall reaction turnover. During the reaction, the active IrO₂ surface is covered mainly by *O, *OOH, and *OO adsorbed species with a share dependent on the applied potential and of 44, 28, and 20% at an overpotential of 350 mV, respectively. In contrast to state-of-the-art calculations of ideal catalyst surfaces, this novel model-based methodology allows for experimental identification of the microkinetics as well as thermodynamic energy values of real pristine and degraded nanoparticles. We show that the loss in electrocatalytic activity during degradation is correlated to an increase in the activation energy of deprotonation processes, whereas reaction energies were marginally affected. As the effect of electrolyte-related parameters does not cause such a decrease, the model-based analysis demonstrates that material changes trigger the performance loss. These insights into the degradation of IrO₂ and its effect on the surface processes provide the basis for a deeper understanding of degrading active sites for the optimization of the oxygen evolution performance.

Selectively anchoring single atoms on specific sites of supports for improved oxygen evolution

The homogeneity of single-atom catalysts is only to the first-order approximation when all isolated metal centers interact identically with the support. Since the realistic support with various topologies or defects offers diverse coordination environments, realizing real homogeneity requires precise control over the anchoring sites. In this work, we selectively anchor Ir single atoms onto the three-fold hollow sites (Ir₁/T_O–CoOOH) and oxygen vacancies (Ir₁/V_O–CoOOH) on defective CoOOH surface to investigate how the anchoring sites modulate catalytic performance. The oxygen evolution activities of Ir₁/T_O–CoOOH and Ir₁/V_O–CoOOH are improved relative to CoOOH through different mechanisms. For Ir₁/T_O–CoOOH, the strong electronic interaction between single-atom Ir and the support modifies the electronic structure of the active center for stronger electronic affinity to intermediates. For Ir₁/V_O–CoOOH, a hydrogen bonding is formed between the coordinated oxygen of single-atom Ir center and the oxygenated intermediates, which stabilizes the intermediates and lowers the energy barrier of the rate-determining step.

While single-atom catalysts offer well-defined structures, the homogeneity of the active sites is determined by localized coordination environments. Here, authors anchor Ir single atoms onto different sites on CoOOH and show how their distinct coordinations activate oxygen-evolving electrocatalysis

A Self-Reconstructed Bifunctional Electrocatalyst of Pseudo-Amorphous Nickel Carbide @ Iron Oxide Network for Seawater Splitting

Here, a sol-gel method is used to prepare a Prussian blue analogue (NiFe-PBA) precursor with a 2D network, which is further annealed to an Fe₃ O₄ /NiC_x composite (NiFe-PBA-gel-cal), inheriting the ultrahigh specific surface area of the parent structure. When the composite is used as both anode and cathode catalyst for overall water splitting, it requires low voltages of 1.57 and 1.66 V to provide a current density of 100 mA cm^-2 in alkaline freshwater and simulated seawater, respectively, exhibiting no obvious attenuation over a 50 h test. Operando Raman spectroscopy and X-ray photoelectron spectroscopy indicate that NiOOH_2-x active species containing high-valence Ni³⁺ /Ni⁴⁺ are in situ generated from NiC_x during the water oxidation. Density functional theory calculations combined with ligand field theory reveal that the role of high valence states of Ni is to trigger the production of localized O 2p electron holes, acting as electrophilic centers for the activation of redox reactions for oxygen evolution reaction. After hydrogen evolution reaction, a series of ex situ and in situ investigations indicate the reduction from Fe³⁺ to Fe²⁺ and the evolution of Ni(OH)₂ are the origin of the high activity.

The electrochemical-step asymmetry index

The development of oxygen-evolution reaction (OER) electrocatalysts has been spurred by thermodynamic considerations on the free-energy landscape. Most commonly, electrocatalytic activity is approximated by the analysis of the free-energy changes among the mechanistic description, thereby taking only reaction steps with weak-binding adsorbates into account. Herein, a new method, denoted as the electrochemical-step asymmetry index (ESAI), is presented, which approximates electrocatalytic activity by penalizing both too strong as well as too weak bonding of intermediate states in order to mimic the well-known Sabatier principle.•

The electrochemical-step asymmetry index (ESAI) is a descriptor to approximate electrocatalytic activity based on the analysis of the free-energy changes for a given mechanistic description, exemplified by the oxygen evolution reaction (OER).

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The concept of the ESAI is based on the assumption that the optimum free-energy landscape has an asymmetric shape because this may factor overpotential and kinetic effects in the analysis, and the ESAI penalizes both too strong as well as too weak bonding of intermediate states to render a thorough representation of the Sabatier principle feasible.

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The ESAI is a conceptual development of the earlier proposed electrochemical-step symmetry index (ESSI), which relies on a symmetric distribution of the free-energy changes as thermodynamic optimum and which takes only weak-binding adsorbates into account.

Mo3(C6O6)2 monolayer as a promising electrocatalyst for the CO2 reduction reaction: a first-principles study

Mo3(C6O6)2 monolayers are potential electrocatalysts for CO2 reduction reaction (CRR). The electrochemical performances can be further improved by coordinating with hydroxyl groups, which show improved performance for the production of methane.

Designing of Efficient Bifunctional ORR/OER Pt Single-Atom Catalysts Based on O-Terminated MXenes by First-Principles Calculations

MXenes have been used as substrate materials for single-atom catalysts (SACs) due to their unique two-dimensional (2D) structure, high surface area, and high electronic conductivity. Oxygen is the primary terminating group of MXenes; however, all of the reported Pt SACs till now are fabricated with F-terminated MXenes. According to the first-principles calculations of this work, the failure of using O-terminated MXenes as substrates is due to the low charge density around Pt and C, which weakens the catalytic activity of Pt. By adjusting the electronic structure of M2C using a second submetal with a lower work function than M, 18 potential bifunctional Pt SACs are constructed based on O-terminated bimetal MXenes. After further consideration of some important practical application factors such as overpotential, solvation effect, and reaction barriers, only four of them, i.e., Cr2Nb2C3O2-VO-Pt, Cr2Ta2C3O2-VO-Pt, Cr2NbC2O2-VO-Pt, and Cr2TaC2O2-VO-Pt, are screened as bifunctional oxygen reduction reaction/oxygen evolution reaction (ORR/OER) catalysts. All of these screened SACs are originated from Cr-based MXenes, implying the significance of Cr-based MXenes in designing bifunctional Pt SACs.

Boride-derived oxygen-evolution catalysts

Metal borides/borates have been considered promising as oxygen evolution reaction catalysts; however, to date, there is a dearth of evidence of long-term stability at practical current densities. Here we report a phase composition modulation approach to fabricate effective borides/borates-based catalysts. We find that metal borides in-situ formed metal borates are responsible for their high activity. This knowledge prompts us to synthesize NiFe-Boride, and to use it as a templating precursor to form an active NiFe-Borate catalyst. This boride-derived oxide catalyzes oxygen evolution with an overpotential of 167 mV at 10 mA/cm² in 1 M KOH electrolyte and requires a record-low overpotential of 460 mV to maintain water splitting performance for over 400 h at current density of 1 A/cm². We couple the catalyst with CO reduction in an alkaline membrane electrode assembly electrolyser, reporting stable C₂H₄ electrosynthesis at current density 200 mA/cm² for over 80 h.

Main Descriptors To Correlate Structures with the Performances of Electrocatalysts

Traditional trial and error approaches to search for hydrogen/oxygen redox catalysts with high activity and stability are typically tedious and inefficient. There is an urgent need to identify the most important parameters that determine the catalytic performance and so enable the development of design strategies for catalysts. In the past decades, several descriptors have been developed to unravel structure-performance relationships. This Minireview summarizes reactivity descriptors in electrocatalysis including adsorption energy descriptors involving reaction intermediates, electronic descriptors represented by a d-band center, structural descriptors, and universal descriptors, and discusses their merits/limitations. Understanding the trends in electrocatalytic performance and predicting promising catalytic materials using reactivity descriptors should enable the rational construction of catalysts. Artificial intelligence and machine learning have also been adopted to discover new and advanced descriptors. Finally, linear scaling relationships are analyzed and several strategies proposed to circumvent the established scaling relationships and overcome the constraints imposed on the catalytic performance.

Electrokinetic and in situ spectroscopic investigations of CO electrochemical reduction on copper

Rigorous electrokinetic results are key to understanding the reaction mechanisms in the electrochemical CO reduction reaction (CORR), however, most reported results are compromised by the CO mass transport limitation. In this work, we determined mass transport-free CORR kinetics by employing a gas-diffusion type electrode and identified dependence of catalyst surface speciation on the electrolyte pH using in-situ surface enhanced vibrational spectroscopies. Based on the measured Tafel slopes and reaction orders, we demonstrate that the formation rates of C₂₊ products are most likely limited by the dimerization of CO adsorbate. CH₄ production is limited by the CO hydrogenation step via a proton coupled electron transfer and a chemical hydrogenation step of CO by adsorbed hydrogen atom in weakly (7 < pH < 11) and strongly (pH > 11) alkaline electrolytes, respectively. Further, CH₄ and C₂₊ products are likely formed on distinct types of active sites.

Electrokinetic results are key to understanding the mechanisms in electrochemical CO reduction reaction. Here, the authors determine mass transport free kinetics using a gas-diffusion electrode and identified dependence of copper surface speciation on the electrolyte pH using in situ surface enhanced spectroscopies.

Intrinsic Electrocatalytic Activity for Oxygen Evolution of Crystalline 3d-Transition Metal Layered Double Hydroxides

Layered double hydroxides (LDHs) are among the most active and studied catalysts for the oxygen evolution reaction (OER) in alkaline electrolytes. However, previous studies have generally either focused on a small number of LDHs, applied synthetic routes with limited structural control, or used non-intrinsic activity metrics, thus hampering the construction of consistent structure-activity-relations. Herein, by employing new individually developed synthesis strategies with atomic structural control, we obtained a broad series of crystalline α-M_A (II)M_B (III) LDH and β-M_A (OH)₂ electrocatalysts (M_A =Ni, Co, and M_B =Co, Fe, Mn). We further derived their intrinsic activity through electrochemical active surface area normalization, yielding the trend NiFe LDH > CoFe LDH > Fe-free Co-containing catalysts > Fe-Co-free Ni-based catalysts. Our theoretical reactivity analysis revealed that these intrinsic activity trends originate from the dual-metal-site nature of the reaction centers, which lead to composition-dependent synergies and diverse scaling relationships that may be used to design catalysts with improved performance.

Circumventing Scaling Relations in Oxygen Electrochemistry Using Metal-Organic Frameworks

It has been well-established that unfavorable scaling relationships between *OOH, *OH, and *O are responsible for the high overpotentials associated with oxygen electrochemistry. A number of strategies have been proposed for breaking these linear constraints for traditional electrocatalysts (e.g., metals, alloys, metal-doped carbons); such approaches have not yet been validated experimentally for heterogeneous catalysts. Development of a new class of catalysts capable of circumventing such scaling relations remains an ongoing challenge in the field. In this work, we use density functional theory (DFT) calculations to demonstrate that bimetallic porphyrin-based MOFs (PMOFs) are an ideal materials platform for rationally designing the 3-D active site environments for oxygen reduction reaction (ORR). Specifically, we show that the *OOH binding energy and the theoretical limiting potential can be optimized by appropriately tuning the transition metal active site, the oxophilic spectator, and the MOF topology. Our calculations predict theoretical limiting potentials as high as 1.07 V for Fe/Cr-PMOF-Al, which exceeds the Pt/C benchmark for 4e ORR. More broadly, by highlighting their unique characteristics, this work aims to establish bimetallic porphyrin-based MOFs as a viable materials platform for future experimental and theoretical ORR studies.