From the Sabatier principle to a predictive theory of transition-metal heterogeneous catalysis

A critical review of research progress for metal alloy materials in hydrogen evolution and oxygen evolution reaction

Hydrogen produced by electrolyzing water has attracted extensive attention as an effective way to generate and store new energy by using renewable energy. Electrocatalytic hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) were the core reactions in the process of hydrogen production by water electrolysis, however, due to the low efficiency of the electrolytic device caused by its slow kinetic reaction and the dependence on noble metal catalysts (platinum and iridium/ruthenium (oxide)), which limited its wide application. The preparation of high-efficiency catalysts with high catalytic activity, stability, low cost and scalability played a vital role in promoting the development of hydrogen production technology from electrolytic water and has become a current research hotspot. Metal alloy catalysts have been widely studied as high-efficiency electrocatalysts. This study introduced and analyzed the mechanism and application of metal alloy catalyst in hydrogen and oxygen evolution reaction, summarized and discussed the progress in the design, preparation and application of metal alloy electrocatalysts. Finally, the strategy and prospect of new high-efficiency electrocatalysts were proposed.

Clear-Box Machine Learning for Virtual Screening of 2D Nanozymes to Target Tumor Hydrogen Peroxide

Targeting tumor hydrogen peroxide (H₂ O₂ ) with catalytic materials has provided a novel chemotherapy strategy against solid tumors. Because numerous materials have been fabricated so far, there is an urgent need for an efficient in silico method, which can automatically screen out appropriate candidates from materials libraries for further therapeutic evaluation. In this work, adsorption-energy-based descriptors and criteria are developed for the catalase-like activities of materials surfaces. The result enables a comprehensive prediction of H₂ O₂ -targeted catalytic activities of materials by density functional theory (DFT) calculations. To expedite the prediction, machine learning models, which efficiently calculate the adsorption energies for 2D materials without DFT, are further developed. The finally obtained method takes advantage of both interpretability of physics model and high efficiency of machine learning. It provides an efficient approach for in silico screening of 2D materials toward tumor catalytic therapy, and it will greatly promote the development of catalytic nanomaterials for medical applications.

An Atom-Pair Design Strategy for Optimizing the Synergistic Electron Effects of Catalytic Sites in NO Selective Reduction

Effective adsorption and speedy surface reactions are vital requirements for efficient active sites in catalysis, but it remains challenging to maximize these two functions simultaneously. We present a solution to this issue by designing a series of atom-pair catalytic sites with tunable electronic interactions. As a case study, NO selective reduction occurring on V₁ -W₁ /TiO₂ is chosen. Experimental and theoretical results reveal that the synergistic electron effect present between the paired atoms enriches high-energy spin charge around the Fermi level, simultaneously rendering reactant (NH₃ or O₂ ) adsorption more effective and subsequent surface reactions speedier as compared with single V or W atom alone, and hence higher reaction rates. This strategy enables us to rationally design a high-performance V₁ -Mo₁ /TiO₂ catalyst with optimized vanadium(IV)-molybdenum(V) electronic interactions, which has exceptional activity significantly higher than the commercial or reported catalysts.

In situ identification of surface sites in Cu-Pt bimetallic catalysts: Gas-induced metal segregation

The effect of gases on the surface composition of Cu-Pt bimetallic catalysts has been tested by in situ infrared (IR) and x-ray absorption spectroscopies. Diffusion of Pt atoms within the Cu-Pt nanoparticles was observed both in vacuum and under gaseous atmospheres. Vacuum IR spectra of CO adsorbed on CuPt_x/SBA-15 catalysts (x = 0-∞) at 125 K showed no bonding on Pt regardless of Pt content, but reversible Pt segregation to the surface was seen with the high-Pt-content (x ≥ 0.2) samples upon heating to 225 K. In situ IR spectra in CO atmospheres also highlighted the reversible segregation of Pt to the surface and its diffusion back into the bulk when cycling the temperature from 295 to 495 K and back, most evidently for diluted single-atom alloy catalysts (x ≤ 0.01). Similar behavior was possibly observed under H₂ using small amounts of CO as a probe molecule. In situ x-ray absorption near-edge structure data obtained for CuPt_0.2/SBA-15 under both CO and He pointed to the metallic nature of the Pt atoms irrespective of gas or temperature, but analysis of the extended x-ray absorption fine structure identified a change in coordination environment around the Pt atoms, from a (Pt-Cu):(Pt-Pt) coordination number ratio of ∼6:6 at or below 445 K to 8:4 at 495 K. The main conclusion is that Cu-Pt bimetallic catalysts are dynamic, with the composition of their surfaces being dependent on temperature in gaseous environments.

Identifying Descriptors for Promoted Rhodium-Based Catalysts for Higher Alcohol Synthesis via Machine Learning

Rhodium-based catalysts offer remarkable selectivities toward higher alcohols, specifically ethanol, via syngas conversion. However, the addition of metal promoters is required to increase reactivity, augmenting the complexity of the system. Herein, we present an interpretable machine learning (ML) approach to predict and rationalize the performance of Rh-Mn-P/SiO2 catalysts (P = 19 promoters) using the open-source dataset on Rh-catalyzed higher alcohol synthesis (HAS) from Pacific Northwest National Laboratory (PNNL). A random forest model trained on this dataset comprising 19 alkali, transition, post-transition metals, and metalloid promoters, using catalytic descriptors and reaction conditions, predicts the higher alcohols space-time yield (STYHA) with an accuracy of R 2 = 0.76. The promoter's cohesive energy and alloy formation energy with Rh are revealed as significant descriptors during posterior feature-importance analysis. Their interplay is captured as a dimensionless property, coined promoter affinity index (PAI), which exhibits volcano correlations for space-time yield. Based on this descriptor, we develop guidelines for the rational selection of promoters in designing improved Rh-Mn-P/SiO2 catalysts. This study highlights ML as a tool for computational screening and performance prediction of unseen catalysts and simultaneously draws insights into the property-performance relations of complex catalytic systems.

Iron carbide nanoparticles supported on an N-doped carbon porous framework as a bifunctional material for electrocatalytic oxygen reduction and supercapacitors

Highly active and durable bifunctional materials are of pivotal importance for energy conversion and storage devices, yet a comprehensive understanding of their geometric and electronic influence on electrochemical activity is urgently needed. Fe-N-C materials with physical and chemical structural merits are considered as one of the promising candidates for efficient oxygen reduction reaction electrocatalysts and supercapacitor electrodes. Herein, Fe₃C nanoparticles supported on a porous N-doped carbon framework (denoted as Fe₃C/PNCF) were readily prepared by one-step chemical vapor deposition under the assistance of a NaCl salt template. The experiment results revealed that the as-synthesized Fe₃C/PNCF nanocomposites successfully displayed attractive electrocatalytic oxygen reduction reaction (ORR) activity comparable to that of the Pt/C catalyst (E_1/2 of 0.84 V and 0.83 V, respectively), and a superior capacitance of 385.3 F g^-1 under 1 A g^-1 for a supercapacitor. It's proposed that the increased pyridinic and graphitic N coordination on the hydrophilic porous framework provides more electrochemical active surface area for the storage and transport of electrolyte ions. Additionally, an appropriate d-band center created by the optimized adsorption function endows Fe₃C/PNCF with excellent electrochemical properties. The results confirmed that the integration strategy of porous heterogeneous structure and accessible active sites balanced the complex relationship between geometry, electronic structure, and electrochemical activity. Our research provides a facile approach for fabricating multi-functional nanomaterials applicable in both ORR and supercapacitors in the future.

Wireless electrochemical light emission in ultrathin 2D nanoconfinements

Spatial confinement of chemical reactions or physical effects may lead to original phenomena and new properties. Here, the generation of electrochemiluminescence (ECL) in confined free-standing 2D spaces, exemplified by surfactant-based air bubbles is reported. For this, the ultrathin walls of the bubbles (typically in the range of 100-700 nm) are chosen as a host where graphene sheets, acting as bipolar ECL-emitting electrodes, are trapped and dispersed. The proposed system demonstrates that the required potential for the generation of ECL is up to three orders of magnitude smaller compared to conventional systems, due to the nanoconfinement of the potential drop. This proof-of-concept study demonstrates the key advantages of a 2D environment, allowing a wireless activation of ECL at rather low potentials, compatible with (bio)analytical systems.

Electronic Modification by Transitional Metal Dopants to Tune the Oxidation Activity of Pt-CeO2-Based Catalysts

While utilization of transitional metals as a promoter has been extensively studied to enhance the activity of Pt-based catalysts for the oxidation of formaldehyde (HCHO), there is still a lack of well elucidated property-function relationship for the rational selection of a promoter in catalyst design. Herein, we modified a Pt/CeO₂ catalyst with two transitional metal dopants (i.e., Mn and Cu) that showed negligible influence on the physical structure of the Pt-CeO₂ matrix but distinct effects on the activity of the catalyst. Complementary characterizations combined with density functional theory modeling revealed that the transitional metal dopants significantly modified the electronic structure of the catalyst and shifted the d-band of Pt to higher energy with different extents, which may tune the bonding strength of HCHO/intermediates with the Pt-CeO₂ interface domain. The catalyst with moderate bonding strength (i.e., Pt-Mn/CeO₂) displayed the highest reactivity under the ambient condition, while Pt-Cu/CeO₂ with the highest bonding strength showed a dramatically decreased activity. No correlation was observed between the abundancy of the active oxygen and catalytic activity, likely due to the oxygen supply having a much higher rate than the rate-determining step. This work contributes to the elucidation about the property-function relationship of a transitional metal dopant in Pt-based catalysts for the oxidation of HCHO.

Intelligent route to design efficient CO2 reduction electrocatalysts using ANFIS optimized by GA and PSO

Recently, electrochemical reduction of CO₂ into value-added fuels has been noticed as a promising process to decrease CO₂ emissions. The development of such technology is strongly depended upon tuning the surface properties of the applied electrocatalysts. Considering the high cost and time-consuming experimental investigations, computational methods, particularly machine learning algorithms, can be the appropriate approach for efficiently screening the metal alloys as the electrocatalysts. In doing so, to represent the surface properties of the electrocatalysts numerically, d-band theory-based electronic features and intrinsic properties obtained from density functional theory (DFT) calculations were used as descriptors. Accordingly, a dataset containg 258 data points was extracted from the DFT method to use in machine learning method. The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. The developed ANFIS-PSO and ANFIS-GA showed excellent performance with RMSE of 0.0411 and 0.0383, respectively, the minimum errors reported so far in this field. Additionally, the sensitivity analysis showed that the center and the filling of the d-band are the most determining parameters for the electrocatalyst surface reactivity. The present study conveniently indicates the potential and value of machine learning in directing the experimental efforts in alloy system electrocatalysts for CO₂ reduction.

Efficient catalyst screening using graph neural networks to predict strain effects on adsorption energy

Small-molecule adsorption energies correlate with energy barriers of catalyzed intermediate reaction steps, determining the dominant microkinetic mechanism. Straining the catalyst can alter adsorption energies and break scaling relationships that inhibit reaction engineering, but identifying desirable strain patterns using density functional theory is intractable because of the high-dimensional search space. We train a graph neural network to predict the adsorption energy response of a catalyst/adsorbate system under a proposed surface strain pattern. The training data are generated by randomly straining and relaxing Cu-based binary alloy catalyst complexes taken from the Open Catalyst Project. The trained model successfully predicts the adsorption energy response for 85% of strains in unseen test data, outperforming ensemble linear baselines. Using ammonia synthesis as an example, we identify Cu-S alloy catalysts as promising candidates for strain engineering. Our approach can locate strain patterns that break adsorption energy scaling relations to improve catalyst performance.

Single-Atom Low-Valent Alkaline-Earth-Metal Catalysts for Electrochemical Nitrogen Reduction with an Acceptance-Backdonation Mechanism

Single-atom catalysts (SACs) have drawn great attention in developing highly active and low-cost catalysts for electrocatalytic nitrogen reduction reaction (NRR) in ammonia synthesis, but the atomic metal centers are mainly limited to transition metals. Here, four stable alkaline-earth-metal (AEM)-based SACs are proposed by anchoring AEM on nitrogen-doped graphene nanoribbons, based on first-principles calculations. All SACs exhibit excellent NRR performance with competitive limiting potentials compared to stepped Ru (0001), and Ca-based SAC achieves optimal activity with a potential of -0.716 V. It is revealed that the low oxidation state of AEM is crucial for the activation of N₂ through an acceptance-backdonation mechanism. The antibonding 2π* orbital of N₂ can accept residual s electrons of low-valent AEM and backdonate electrons to the empty d orbitals of AEM, resulting in activation of N₂ molecules. In particular, the activation degree of N₂ and NRR activity is linearly associated with the charge states of AEMs. Our work reveals the underlying mechanism of AEMs for N₂ activation and reduction and presents the potential of AEM SACs as efficient electrochemical NRR catalysts.

Tailoring of Active Sites from Single to Dual Atom Sites for Highly Efficient Electrocatalysis

Single atom catalysts (SACs) have been attracting extensive attention in electrocatalysis because of their unusual structure and extreme atom utilization, but the low metal loading and unified single site induced scaling relations may limit their activity and practical application. Tailoring of active sites at the atomic level is a sensible approach to break the existing limits in SACs. In this review, SACs were first discussed regarding carbon or non-carbon supports. Then, five tailoring strategies were elaborated toward improving the electrocatalytic activity of SACs, namely strain engineering, spin-state tuning engineering, axial functionalization engineering, ligand engineering, and porosity engineering, so as to optimize the electronic state of active sites, tune d orbitals of transition metals, adjust adsorption strength of intermediates, enhance electron transfer, and elevate mass transport efficiency. Afterward, from the angle of inducing electron redistribution and optimizing the adsorption nature of active centers, the synergistic effect from adjacent atoms and recent advances in tailoring strategies on active sites with binuclear configuration which include simple, homonuclear, and heteronuclear dual atom catalysts (DACs) were summarized. Finally, a summary and some perspectives for achieving efficient and sustainable electrocatalysis were presented based on tailoring strategies, design of active sites, and in situ characterization.

A Systematic Theoretical Study on Electronic Interaction in Cu-based Single-Atom Alloys

A meticulous understanding of the electronic structure of catalysts may provide new insight into catalytic performances. Here, we present a d-d interaction model to systematically study the electronic interaction in Cu-based single-atom alloys. We refine three types of electronic interactions according to the position of the antibonding state relative to the Fermi level. Moreover, we also find a special phenomenon in Mn-doped single-atom alloys in which no obvious electronic interaction is found, and the doped Mn metal seems to be a free atom. Then, taking Hf/Mn-doped single-atom alloys as an example, we discuss the electronic structure based on the density of states, charge transfer, crystal orbital Hamilton population, and wavefunctions. To support the proposed model and help analyze the data, we perform an energetic analysis of water dissociation in the water-gas shift reaction. The calculation results well confirm the d-d interaction model, where alloys with the position of the antibonding state close to the Fermi level exhibit excellent water dissociation ability in the water-gas shift reaction. However, the catalytic performance of the Mn-doped alloy is unsatisfactory, which is caused by its own special phenomenon.

Transition metal oxides with perovskite and spinel structures for electrochemical energy production applications

Transition metal oxide-based materials are an interesting alternative to substitute noble-metal based catalyst in energy conversion devices designed for oxygen reduction (ORR), oxygen evolution (OER) and hydrogen evolution reactions (HER). Perovskite (ABO₃) and spinel (AB₂O₄) oxides stand out against other structures due to the possibility of tailoring their chemical composition and, consequently, their properties. Particularly, the electrocatalytic performance of these materials depends on features such as chemical composition, crystal structure, nanostructure, cation substitution level, e_g orbital filling or oxygen vacancies. However, they suffer from low electrical conductivity and surface area, which affects the catalytic response. To mitigate these drawbacks, they have been combined with carbon materials (e.g. carbon black, carbon nanotubes, activated carbon, and graphene) that positively influence the overall catalytic activity. This review provides an overview on tunable perovskites (mainly lanthanum-based) and spinels featuring 3d metal cations such as Mn, Fe, Co, Ni and Cu on octahedral sites, which are known to be active for the electrochemical energy conversion.

Modeling Interfacial Interaction between Gas Molecules and Semiconductor Metal Oxides: A New View Angle on Gas Sensing

With the development of internet of things and artificial intelligence electronics, metal oxide semiconductor (MOS)-based sensing materials have attracted increasing attention from both fundamental research and practical applications. MOS materials possess intrinsic physicochemical properties, tunable compositions, and electronic structure, and are particularly suitable for integration and miniaturization in developing chemiresistive gas sensors. During sensing processes, the dynamic gas-solid interface interactions play crucial roles in improving sensors' performance, and most studies emphasize the gas-MOS chemical reactions. Herein, from a new view angle focusing more on physical gas-solid interactions during gas sensing, basic theory overview and latest progress for the dynamic process of gas molecules including adsorption, desorption, and diffusion, are systematically summarized and elucidated. The unique electronic sensing mechanisms are also discussed from various aspects including molecular interaction models, gas diffusion mechanism, and interfacial reaction behaviors, where structure-activity relationship and diffusion behavior are overviewed in detail. Especially, the surface adsorption-desorption dynamics are discussed and evaluated, and their potential effects on sensing performance are elucidated from the gas-solid interfacial regulation perspective. Finally, the prospect for further research directions in improving gas dynamic processes in MOS gas sensors is discussed, aiming to supplement the approaches for the development of high-performance MOS gas sensors.

Design of a Metal/Oxide/Carbon Interface for Highly Active and Selective Electrocatalysis

Sustainable energy-conversion and chemical-production require catalysts with high activity, durability, and product-selectivity. Metal/oxide hybrid structure has been intensively investigated to achieve promising catalytic performance, especially in neutral or alkaline electrocatalysis where water dissociation is promoted near the oxide surface for (de)protonation of intermediates. Although catalytic promise of the hybrid structure is demonstrated, it is still challenging to precisely modulate metal/oxide interfacial interactions on the nanoscale. Herein, we report an effective strategy to construct rich metal/oxide nano-interfaces on conductive carbon supports in a surfactant-free and self-terminated way. When compared to the physically mixed Pd/CeO₂ system, a much higher degree of interface formation was identified with largely improved hydrogen oxidation reaction (HOR) kinetics. The benefits of the rich metal-CeO₂ interface were further generalized to Pd alloys for optimized adsorption energy, where the Pd₃Ni/CeO₂/C catalyst shows superior performance with HOR selectivity against CO poisoning and shows long-term stability. We believe this work highlights the importance of controlling the interfacial junctions of the electrocatalyst in simultaneously achieving enhanced activity, selectivity, and stability.

Pt nanoparticles under oxidizing conditions - implications of particle size, adsorption sites and oxygen coverage on stability

Platinum nanoparticles are efficient catalysts for different reactions, such as oxidation of carbon and nitrogen monoxides. Adsorption and interaction of oxygen with the nanoparticle surface, taking place under reaction conditions, determine not only the catalytic efficiency but also the stability of the nanoparticles against oxidation. In this study, platinum nanoparticles in oxygen environment are investigated by systematic screening of initial nanoparticle-oxygen configurations and employing density functional theory and a thermodynamics-based approach. The structures formed at low oxygen coverages are described by adsorption of atomic oxygen on the nanoparticles whereas at high coverages oxide-like species are formed. The relative stability of adsorption configurations at different oxygen coverages, including the phase of fully oxidized nanoparticles, is investigated by constructing p-T phase diagrams for the studied systems.

Direct identification of the charge state in a single platinum nanoparticle on titanium oxide

A goal in the characterization of supported metal catalysts is to achieve particle-by-particle analysis of the charge state strongly correlated with the catalytic activity. Here, we demonstrate the direct identification of the charge state of individual platinum nanoparticles (NPs) supported on titanium dioxide using ultrahigh sensitivity and precision electron holography. Sophisticated phase-shift analysis for the part of the NPs protruding into the vacuum visualized slight potential changes around individual platinum NPs. The analysis revealed the number (only one to six electrons) and sense (positive or negative) of the charge per platinum NP. The underlying mechanism of platinum charging is explained by the work function differences between platinum and titanium dioxide (depending on the orientation relationship and lattice distortion) and by first-principles calculations in terms of the charge transfer processes.

MoSe2 -VSe2 -NbSe2 Ternary Alloy Nanosheets to Boost Electrocatalytic Hydrogen Evolution Reaction

Alloying of transition metal dichalcogenides (TMDs) is a pioneering method for engineering electronic structures with expanded applications. In this study, MoSe₂ -VSe₂ -NbSe₂ ternary alloy nanosheets are synthesized via a colloidal reaction. The composition is successfully tuned over a wide range to adjust the 2H-1T phase transition. The alloy nanosheets consist of miscible atomic structures at all compositions, which is distinct from immiscible binary alloys. Compared to each binary alloy, the ternary alloys display higher electrocatalytic activity toward the hydrogen evolution reaction (HER) in an acidic electrolyte. The HER performance exhibits a volcano-type composition dependence, which is correlated with the experimental d-band center (ε_d ). Spin-polarized density functional theory (DFT) calculations consistently predict the homogenous atomic distributions. The Gibbs free energy of H adsorption (ΔG_H* ) and the activation barrier (E_a ) support that miscible ternary alloying greatly enhances the HER performance.

Engineering 3d-2p-4f Gradient Orbital Coupling to Enhance Electrocatalytic Oxygen Reduction

The development of highly efficient and economical materials for the oxygen reduction reaction (ORR) plays a key role in practical energy conversion technologies. However, the intrinsic scaling relations exert thermodynamic inhibition on realizing highly active ORR electrocatalysts. Herein, a novel and feasible gradient orbital coupling strategy for tuning the ORR performance through the construction of Co 3d-O 2p-Eu 4f unit sites on the Eu₂ O₃ -Co model is proposed. Through the gradient orbital coupling, the pristine ionic property between Eu and O atoms is assigned with increased covalency, which optimizes the e_g occupancy of Co sites, and weakens the OO bond, thus ultimately breaking the scaling relation between *OOH and *OH at Co-O-Eu unit sites. The optimized model catalyst displays onset and half-wave potential of 1.007 and 0.887 V versus reversible hydrogen electrode, respectively, which are higher than those of commercial Pt/C and most Co-based catalysts ever reported. In addition, the catalyst is found to possess superior selectivity and durability. It also reveals better cell performance than commercial noble-metal catalysts in Zn-air batteries in terms of high power/energy densities and long cycle life. This study provides a new perspective for electronic modulation strategy by the construction of gradient 3d-2p-4f orbital coupling.

Catalysis of Alloys: Classification, Principles, and Design for a Variety of Materials and Reactions

Alloying has long been used as a promising methodology to improve the catalytic performance of metallic materials. In recent years, the field of alloy catalysis has made remarkable progress with the emergence of a variety of novel alloy materials and their functions. Therefore, a comprehensive disciplinary framework for catalytic chemistry of alloys that provides a cross-sectional understanding of the broad research field is in high demand. In this review, we provide a comprehensive classification of various alloy materials based on metallurgy, thermodynamics, and inorganic chemistry and summarize the roles of alloying in catalysis and its principles with a brief introduction of the historical background of this research field. Furthermore, we explain how each type of alloy can be used as a catalyst material and how to design a functional catalyst for the target reaction by introducing representative case studies. This review includes two approaches, namely, from materials and reactions, to provide a better understanding of the catalytic chemistry of alloys. Our review offers a perspective on this research field and can be used encyclopedically according to the readers' individual interests.

Nanoparticle/metal-organic framework hybrid catalysts: elucidating the role of the MOF

Hybrid materials of metal-organic frameworks (MOFs) and nanoparticles (NPs) have attracted significant attention because of the wide variety of attractive properties derived from the two components. In the last decade, the development of synthesis techniques for NP/MOF composites was particularly significant. In the field of catalysis in particular, various synergistic effects that make the composites attractive catalysts have been reported. However, the role of MOFs in the composite catalysts is still not well understood and is being elucidated. In this feature article, we focus on recent progress in NP/MOF composite catalysts, concentrating on the analysis of the interaction between NPs and MOFs and the reaction mechanisms, together with the synthetic techniques used for NP/MOF hybrid materials.

Non-Noble Metal Catalysts in Cathodic Oxygen Reduction Reaction of Proton Exchange Membrane Fuel Cells: Recent Advances

The oxygen reduction reaction (ORR) is one of the crucial energy conversion reactions in proton exchange membrane fuel cells (PEMFCs). Low price and remarkable catalyst performance are very important for the cathode ORR of PEMFCs. Among the various explored ORR catalysts, non-noble metals (transition metal: Fe, Co, Mn, etc.) and N co-doped C (M-N-C) ORR catalysts have drawn increasing attention due to the abundance of these resources and their low price. In this paper, the recent advances of single-atom catalysts (SACs) and double-atom catalysts (DACs) in the cathode ORR of PEMFCs is reviewed systematically, with emphasis on the synthesis methods and ORR performance of the catalysts. Finally, challenges and prospects are provided for further advancing non-noble metal catalysts in PEMFCs.

Facet and d-band center engineering of CuNi nanocrystals for efficient nitrate electroreduction to ammonia

Electrocatalytic nitrate reduction offers a sustainable route to ammonia synthesis and wastewater treatment. However, the nitrate-to-ammonia conversion remains inefficient due to the sluggish kinetics and diverse side reactions. Herein, well-faceted CuNi nanocrystals with Ni-rich surfaces and favorable d-band centres were synthesized with the assistance of γ-cyclodextrin via a solvothermal process. When used as catalysts for nitrate electroreduction, they delivered an ammonia yield of 1.374 mmol h^-1 mg^-1 (0.5496 mmol h^-1 cm^-2) at -0.3 V with the faradaic efficiency and selectivity reaching 94.5% and 65.0%, respectively, surpassing pure Cu or Ni nanocrystals and most reported catalysts. Such excellent performances originated from the optimal geometric and electronic structures and special element distribution, which optimized the adsorption behaviors and accelerated the reaction kinetics. A NO₃^--NO₂^--NH₃ pathway was proposed with the chemical process following the initial electron transfer process as the rate-determining step. This work sheds light on the design of efficient catalysts to achieve carbon neutrality through simultaneous geometric and electronic structure modulation.

Reprogramming thermodynamic-limiting oxidation cycle in NiFe-based oxygen evolution electrocatalyst through Mo doping induced surface reconstruction

Engineering of robust nonprecious electrocatalysts toward anodic oxygen evolution reaction (OER) is of great significance for lowering the cost and energy consumption for renewable fuel production. Herein, we report NiFeMoO_x nanosheets as high-performance OER electrocatalyst through promoting the thermodynamic-limiting oxidation cycle process in NiFe oxyhydroxide via high-valence Mo doping. The NiFeMoO_x nanosheets are prepared by an elaborate in-situ solvothermal etching-depositing process with NiFe alloy framework as substrate and metal precursors. The resultant nanosheets exhibit outstanding alkaline OER activity, requires only 235/282/327 mV overpotentials to achieve current density of 10/100/300 mA cm^-2, respectively, with a good long-term stability at 20 mA cm^-2 for 72 h. Besides, the Tafel slope low to 28.1 mV dec^-1 indicates a favorable OER kinetics. The superior catalytic activity of NiFeMoO_x nanosheets should be attributed to the lower oxidation states of Ni and Fe induced by high-valence dopant, leading to easier surface reconstruction at low charge oxidation cycling during OER, thereby effectively reducing the overpotential. The synergy between the electronic effect among multimetallic sites and the unique morphology is expected to inspire the development of robust OER electrocatalyst for industrial application.

Breaking the Linear Relation in the Dissociation of Nitrogen on Iron Surfaces

Current industrial ammonia synthesis depends on the Haber-Bosch process, in which the activity of the catalyst is limited by the Brønsted-Evans-Polanyi (BEP) principle and Fe is used as a commercial catalyst. Herein, we found that the dissociation barriers of N2 on Fe(111), Fe(211), Fe(110), and Fe(100) surfaces do not follow the widely accepted BEP principle. N2 dissociation on Fe(111) surface has the smallest adsorption energy and the lowest energetic barrier. Such an abnormal phenomenon can be attributed to charge transfer from Fe surfaces to the anti-bonding orbital (π*) of the absorbed N2 . More charges transferred from the Fe surface to π* of N2 leads to a weaker N≡N triple bond and a lower adsorption energy of N atoms. However, the hydrogenation of N atoms and desorption of NH3 on the four Fe surfaces follow the BEP principle. Therefore, Fe(111) is found to be the most active surface to promote ammonia synthesis, and such a conclusion is also applicable to Ni and Mo surfaces.

Photochemistry Journey to Multielectron and Multiproton Chemical Transformation

The odyssey of photochemistry is accompanied by the journey to manipulate "electrons" and "protons" in time, in space, and in energy. Over the past decades, single-electron (1e^-) photochemical transformations have brought marvelous achievements. However, as each photon absorption typically generates only one exciton pair, it is exponentially challenging to accomplish multielectron and proton photochemical transformations. The multistep differences in thermodynamics and kinetics urgently require us to optimize light harvesting, expedite consecutive electron transfer, manipulate the interaction of catalysts with substrates, and coordinate proton transfer kinetics to furnish selective bond formations. Tandem catalysis enables orchestrating different photochemical events and catalytic transformations from subpicoseconds to seconds, which facilitates multielectron redox chemistries and brings consecutive, value-added reactivities. Joint efforts in molecular and material design, mechanistic understanding, and theoretical modeling will bring multielectron and proton synthetic opportunities for fuels, fertilizers, and chemicals with enhanced versatility, efficiency, selectivity, and scalability, thus taking better advantage of photons (i.e., sunlight) for our sustainable society.

Impact of Gas-Solid Reaction Thermodynamics on the Performance of a Chemical Looping Ammonia Synthesis Process

Novel ammonia catalysts seek to achieve high reaction rates under milder conditions, which translate into lower costs and energy requirements. Alkali and alkaline earth metal hydrides have been shown to possess such favorable kinetics when employed in a chemical looping process. The materials act as nitrogen carriers and form ammonia by alternating between pure nitrogen and hydrogen feeds in a two-stage chemical looping reaction. However, the thermodynamics of the novel reaction route in question are only partially available. Here, a chemical looping process was designed and simulated to evaluate the sensitivity of the energy and economic performance of the processes toward the appropriate gas-solid reaction thermodynamics. Thermodynamic parameters, such as reaction pressure and especially equilibrium ammonia yields, influenced the performance of the system. In comparison to a commercial ammonia synthesis unit with a 28% yield at 150 bar, the chemical looping process requires a yield greater than 38% to achieve similar energy consumptions and a yield greater than 26% to achieve similar costs at a given temperature and 150 bar. Entropies and enthalpies of formation of the following pairs were estimated and compared: LiH/Li₂NH, MgH₂/MgNH, CaH₂/CaNH, SrH₂/SrNH, and BaH₂/BaNH. Only the LiH/Li₂NH pair has satisfied the given criteria, and initial estimates suggest that a 62% yield is obtainable.