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

Cooperative Active Sites on Ag2Pt3TiS6 for Enhanced Low-Temperature Ammonia Fuel Cell Electrocatalysis

Ammonia has attracted considerable interest as a hydrogen carrier that can help decarbonize global energy networks. Key to realizing this is the development of low temperature ammonia fuel cells for the on-demand generation of electricity. However, the efficiency of such systems is significantly impaired by the sluggish ammonia oxidation reaction (AOR) and oxygen reduction reaction (ORR). Here, we report the design of a bifunctional Ag2Pt3TiS6 electrocatalyst that facilitates both reactions at mass activities exceeding that of commercial Pt/C. Through comprehensive density functional theory calculations, we identify that active site motifs composed of Pt and Ti atoms work cooperatively to catalyze ORR and AOR. Notably, in situ shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS) experiments indicate a decreased propensity for *NOx formation and hence an increased resistance toward catalyst poisoning for AOR. Employing Ag2Pt3TiS6 as both the cathode and anode, we constructed a low temperature ammonia fuel cell with a high peak power density of 8.71 mW cm-2 and low Pt loading of 0.45 mg cm-2. Our findings demonstrate a pathway towards the rational design of effective electrocatalysts with multi-element active sites that work cooperatively.

Design Criteria for Active and Selective Catalysts in the Nitrogen Oxidation Reaction

The direct conversion of dinitrogen to nitrate is a dream reaction to combine the Haber-Bosch and Ostwald processes as well as steam reforming using electrochemistry in a single process. Regrettably, the corresponding nitrogen oxidation (NOR) reaction is hampered by a selectivity problem, since the oxygen evolution reaction (OER) is both thermodynamically and kinetically favored in the same potential range. This opens the search for the identification of active and selective NOR catalysts to enable nitrate production under anodic reaction conditions. While theoretical considerations using the computational hydrogen electrode approach have helped in identifying potential material motifs for electrocatalytic reactions over the last decades, the inherent complexity of the NOR, which consists of ten proton-coupled electron transfer steps and thus at least nine intermediate states, poses a challenge for electronic structure theory calculations in the realm of materials screening. To this end, we present a different strategy to capture the competing NOR and OER at the atomic scale. Using a data-driven method, we provide a framework to derive generalized design criteria for materials with selectivity toward NOR. This leads to a significant reduction of the computational costs, since only two free-energy changes need to be evaluated to draw a first conclusion on NOR selectivity.

Screening of Silver-Based Single-Atom Alloy Catalysts for NO Electroreduction to NH3 by DFT Calculations and Machine Learning

Exploring NO reduction reaction (NORR) electrocatalysts with high activity and selectivity toward NH3 is essential for both NO removal and NH3 synthesis. Due to their superior electrocatalytic activities, single-atom alloy (SAA) catalysts have attracted considerable attention. However, the exploration of SAAs is hindered by a lack of fast yet reliable prediction of catalytic performance. To address this problem, we comprehensively screened a series of transition-metal atom doped Ag-based SAAs. This screening process involves regression machine learning (ML) algorithms and a compressed-sensing data-analytics approach parameterized with density-functional inputs. The results demonstrate that Cu/Ag and Zn/Ag can efficiently activate and hydrogenate NO with small Φmax(η), a grand-canonical adaptation of the Gmax(η) descriptor, and exhibit higher affinity to NO over H adatoms to suppress the competing hydrogen evolution reaction. The NH3 selectivity is mainly determined by the s orbitals of the doped single-atom near the Fermi level. The catalytic activity of SAAs is highly correlated with the local environment of the active site. We further quantified the relationship between the intrinsic features of these active sites and Φmax(η). Our work clarifies the mechanism of NORR to NH3 and offers a design principle to guide the screen of highly active SAA catalysts.

MXenes Spontaneously Form Active and Selective Single-Atom Centers under Anodic Polarization Conditions

Single-atom catalysts (SACs) have emerged as a new class of materials for the development of active and selective catalysts. These materials are commonly based on anchoring a noble transition metal to some kind of carrier. In the present work, we demonstrate that MXenes─two-dimensional materials with application in energy storage and conversion─spontaneously form SAC-like sites under anodic polarization conditions, using the applied electrode potential as a probe to form catalytically active surface sites reminiscent of a SAC-like structure. Combining ab initio molecular dynamics simulations and electronic structure calculations in the density functional theory framework, we demonstrate that only the SAC-like sites rather than the basal planes of MXenes are highly active and selective for the oxygen evolution or chlorine evolution reactions, respectively. Our findings may simplify synthetic routes toward the formation of active and selective SAC-like sites and could pave the way for the development of smart materials by incorporating fundamental principles from nature into material discovery: while the pristine form of the material is inactive, the application of an electrode potential activates the material by the formation of active and selective single-atom centers.

Error Awareness in the Volcano Plots of Oxygen Electroreduction to Hydrogen Peroxide

Electrocatalysis holds the key to the decentralized production of hydrogen peroxide via the two-electron oxygen reduction reaction (ORR, O2(g)+2H++2e-->H2O2(aq)). However, cost-effective, active, and selective catalysts are still sought after. While density functional theory (DFT) has already led to the discovery of various enhanced catalysts, it has a severe yet often unnoticed drawback: the ill description of O2 and H2O2. Here, we analyze the impact of the errors in those two species on the most widespread activity plots in the literature, namely free-energy diagrams and Sabatier-type volcano plots. Uncorrected or partially corrected gas-phase energies lead to appreciably different activity plots that may provide inaccurate predictions. Indeed, we show for a variety of electrocatalysts that only when the errors in O2 and H2O2 are corrected can DFT mimic the experiments. In sum, this work provides concrete guidelines to avoid a common pitfall of computational models for electrocatalytic hydrogen peroxide production.

Machine-Learning-Assisted Screening of Nanocluster Electrocatalysts: Mapping and Reshaping the Activity Volcano for the Oxygen Reduction Reaction

In computational heterogeneous catalysis, Sabatier's principle-based activity volcano plots provide an intuitive guide to catalyst design but impose a fundamental constraint on the maximum achievable catalytic performance. Recently, subnano clusters have emerged as an exciting platform, offering high noble metal utilization and superior performance for various reactions compared to extended surfaces, reflecting a complex structure-activity relationship in the non-scalable regime. However, understanding their non-monotonic catalytic activity, attributed to the large configurational space and their fluxional identity, poses a formidable challenge. Here, we present a machine learning (ML) framework that captures the non-monotonic trends in oxygen reduction reaction (ORR) activity at the subnanometer scale, attributed to their dynamic fluxional characteristics. We demonstrate a size-dependent shifting and reshaping of the ORR activity volcano, with Au replacing Pt at the peak. Leveraging only upon the non-ab initio geometric and electronic properties, our trained ML model accurately captures the site-specific adsorption energies of intermediates at the subnanometer regime. To account for the inconsistent trend in activity, we analyzed the correlation between electronic and geometric properties. Our findings reveal that the d-filling and coupling matrix of the neighboring metal atom significantly influences the intermediate adsorption on the local chemical environment compared to the d-band center. Following this analysis, we utilized ML to map the catalyst distribution in the activity volcano and identified the five best sub-nano electrocatalysts, demonstrating overpotential values lower than or comparable to the Pt(111) surface for the ORR. This study provides intuitive guidelines for the rational designing of highly efficient electrocatalysts for fuel cell applications while modifying the activity volcano plots for electrocatalysts at the subnanometer regime.

Tuning the product selectivity of single-atom catalysts for CO2 reduction beyond CO formation by orbital engineering

Electrochemical CO2 reduction (CO2R) is one of the promising strategies for developing sustainable energy resources. Single-atom catalysts (SACs) have emerged as efficient catalysts for CO2R. However, the efficiency of SACs for the formation of reduction products beyond two-step CO formation is low due to the lower binding strength of the CO intermediate. In this study, we present an orbital engineering strategy based on density functional theory calculations and the fragment molecular orbital approach to tune product selectivity for the CO2R reaction on macrocycle based molecular catalysts (porphyrin and phthalocyanine) and extended SACs (graphene and covalent organic frameworks) with Fe, Co, and Ni dopants. The introduction of neutral axial ligands such as imidazole, pyridine, and trimethyl phosphine to the metal dopants enhances the binding affinity of the CO intermediate. The stability of the catalysts is investigated through the thermodynamic binding energy of the axial ligands and ab initio molecular dynamics simulations (AIMD). The grand canonical potential method is used to determine the reaction free energy values. Using a unified activity volcano plot based on the reaction free energy values, we investigated the catalytic activity and product selectivity at an applied potential of -0.8 V vs. SHE and a pH of 6.8. We found that with the imidazole and pyridine axial ligands, the selectivity of Fe-doped SACs towards the formation of the methanol product is improved. The activity volcano plot for these SACs shows a similar activity to that of the Cu (211) surface. The catalytic activity is found to be directly proportional to the sigma-donating ability of the axial ligands.

Regulating Co-O covalency to manipulate mechanistic transformation for enhancing activity/durability in acidic water oxidation

Developing earth-abundant electrocatalysts with high activity and durability for acidic oxygen evolution reaction is essential for H2 production, yet it remains greatly challenging. Here, guided by theoretical calculations, the challenge of overcoming the balance between catalytic activity and dynamic durability for acidic OER in Co3O4 was effectively addressed via the preferential substitution of Ru for the Co2+ (Td) site of Co3O4. In situ characterization and DFT calculations show that the enhanced Co-O covalency after the introduction of Ru SAs facilitates the generation of OH* species and mitigates the unstable structure transformation via direct O-O coupling. The designed Ru SAs-CoO x catalyst (5.16 wt% Ru) exhibits enhanced OER activity (188 mV overpotential at 10 mA cm-2) and durability, outperforming most reported Co3O4-based and Ru-based electrocatalysts in acidic media.

Best practices of modeling complex materials in electrocatalysis, exemplified by oxygen evolution reaction on pentlandites

Pentlandites are natural ores with structural properties comparable to that of [FeNi] hydrogenases. While this class of transition-metal sulfide materials - (Fe,Ni)9S8 - with a variable Fe : Ni ratio has been proven to be an active electrode material for the hydrogen evolution reaction, it is also discussed as electrocatalyst for the alkaline oxygen evolution reaction (OER), corresponding to the bottleneck of anion exchange membrane electrolyzers for green hydrogen production. Despite the experimental evidence for the use of (Fe,Ni)9S8 as an OER catalyst, a detailed investigation of the elementary reaction steps, including consideration of adsorbate coverages and limiting steps under anodic polarizing conditions, is still missing. We address this gap in the present manuscript by gaining atomistic insights into the OER on an Fe4.5Ni4.5S8(111) surface through density functional theory calculations combined with a descriptor-based analysis. We use this system to introduce best practices for modeling this rather complex material by pointing out hidden pitfalls that can arise when using the popular computational hydrogen electrode approach to describe electrocatalytic processes at the electrified solid/liquid interface for energy conversion and storage.

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.

Computational chemistry for water-splitting electrocatalysis

Electrocatalytic water splitting driven by renewable electricity has attracted great interest in recent years for producing hydrogen with high-purity. However, the practical applications of this technology are limited by the development of electrocatalysts with high activity, low cost, and long durability. In the search for new electrocatalysts, computational chemistry has made outstanding contributions by providing fundamental laws that govern the electron behavior and enabling predictions of electrocatalyst performance. This review delves into theoretical studies on electrochemical water-splitting processes. Firstly, we introduce the fundamentals of electrochemical water electrolysis and subsequently discuss the current advancements in computational methods and models for electrocatalytic water splitting. Additionally, a comprehensive overview of benchmark descriptors is provided to aid in understanding intrinsic catalytic performance for water-splitting electrocatalysts. Finally, we critically evaluate the remaining challenges within this field.

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.

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.

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.

Extracting Features of Active Transition Metal Electrodes for NO Electroreduction with Catalytic Matrices

Electrocatalytic reduction of oxidized nitrogen compounds (NO_x) promises to help rebalance the nitrogen cycle. It is widely accepted that nitrate reduction to NH₄⁺/NH₃ involves NO as an intermediate, and NO hydrogenation is the potential-limiting step of NO reduction. Whether *NO hydrogenates to *NHO or *NOH is still a matter of debate, which makes it difficult to optimize catalysts for NO_x electroreduction. Here, "catalytic matrices" are used to swiftly extract features of active transition metal catalysts for NO electroreduction. The matrices show that active catalysts statistically stabilize *NHO over *NOH and have undercoordinated sites. Besides, square-symmetry active sites with Cu and other elements may prove active for NO electroreduction. Finally, multivariate regressions are able to reproduce the main features found by the matrices, which opens the door for more sophisticated machine-learning studies. In sum, catalytic matrices may ease the analysis of complex electrocatalytic reactions on multifaceted materials.