Subgroup Discovery Points to the Prominent Role of Charge Transfer in Breaking Nitrogen Scaling Relations at Single-Atom Catalysts on VS2

Electron Sponge Effect by Dynamic-Regulated Electron Self-Flow toward Coupled Electrochemical Ammonia Synthesis

A dynamic-regulated Pd-Fe-N electrocatalyst was effectively constructed with electron-donating and back-donating effects, which serves as an efficient engineering strategy to optimize the electrocatalytic activity. The designed PdFe3/FeN features a comprehensive electrocatalytic performance toward the nitrogen reduction reaction (NRR, yield rate of 29.94 μg h-1 mgcat-1 and FE of 38.43% at -0.2 V vs RHE) and oxygen evolution reaction (OER, 308 mV at 100 mA cm-2). Combining in situ ATR-FTIR, XAS, and DFT results, the role of the interstitial-N-dopant-induced electron sponge effect has been significantly elucidated in strengthening the electrocatalytic NRR process. Specifically, the introduction of a N dopant, an electron acceptor, initiates the generation of robust Lewis-acidic Fe sites, facilitating free N2 capture and bonding. Simultaneously, after NH3 adsorption, the N dopant can back-donate electrons to Fe sites, strengthening the NH3 deportation through weakening the Lewis acidity of Fe centers. Besides, the electron-deficient Fe sites contribute to the reconstruction of FeOOH, the real active species during the OER, which accelerates the four-electron reaction kinetics. This research offers a perspective on electrocatalyst design, potentially facilitating the evolution of advanced material engineering for efficient electrocatalytic synthesis and energy storage.

Strategies Toward High Selectivity, Activity, and Stability of Single-Atom Catalysts

Single-atom catalysts (SACs) hold immense promise in facilitating the rational use of metal resources and achieving atomic economy due to their exceptional atom-utilization efficiency and distinct characteristics. Despite the growing interest in SACs, only limited reviews have holistically summarized their advancements centering on performance metrics. In this review, first, a thorough overview on the research progress in SACs is presented from a performance perspective and the strategies, advancements, and intriguing approaches employed to enhance the critical attributes in SACs are discussed. Subsequently, a comprehensive summary and critical analysis of the electrochemical applications of SACs are provided, with a particular focus on their efficacy in the oxygen reduction reaction , oxygen evolution reaction, hydrogen evolution reaction , CO2 reduction reaction, and N2 reduction reaction . Finally, the outline future research directions on SACs by concentrating on performance-driven investigation, where potential areas for improvement are identified and promising avenues for further study are highlighted, addressing challenges to unlock the full potential of SACs as high-performance catalysts.

Design of Single-Atom Catalysts for E lectrocatalytic Nitrogen Fixation

The Electrochemical nitrogen reduction reaction (ENRR) can be used to solve environmental problems as well as energy shortage. However, ENRR still faces the problems of low NH3 yield and low selectivity. The NH3 yield and selectivity in ENRR are affected by multiple factors such as electrolytic cells, electrolytes, and catalysts, etc. Among these catalysts are at the core of ENRR research. Single-atom catalysts (SACs) with intrinsic activity have become an emerging technology for numerous energy regeneration, including ENRR. In particular, regulating the microenvironment of SACs (hydrogen evolution reaction inhibition, carrier engineering, metal-carrier interaction, etc.) can break through the limitation of intrinsic activity of SACs. Therefore, this Review first introduces the basic principles of NRR and outlines the key factors affecting ENRR. Then a comprehensive summary is given of the progress of SACs (precious metals, non-precious metals, non-metallic) and diatomic catalysts (DACs) in ENRR. The impact of SACs microenvironmental regulation on ENRR is highlighted. Finally, further research directions for SACs in ENRR are discussed.

Breaking linear scaling relations by strain engineering on MXene for boosting N2 electroreduction

The development of N2 reduction reaction (NRR) electrocatalysts with excellent activity and selectivity is of great significance, but adsorption-energy linear scaling relations between reaction intermediates severely hamper the realization of this aspiration. Here, we propose an elegant strain engineering strategy to break the linear relations in NRR to promote catalytic activity and selectivity. Our results show that the N-N bond lengths of adsorbed N2 with side-on and end-on configurations exhibit opposite variations under strains, which is illuminated by establishing two different N2 activation mechanisms of "P-P" (Pull-Pull) and "E-E" (Electron-Electron). Then, we highlight that strain engineering can break the linear scaling relations in NRR, selectively optimizing the adsorption of key NH2NH2** and NH2* intermediates to realize a lower limiting potential (UL). Particularly, the catalytic activity-selectivity trade-off of NRR on MXene can be circumvented, resulting in a low UL of -0.25 V and high Faraday efficiency (FE), which is further elucidated to originate from the strain-modulated electronic structures. Last but not least, the catalytic sustainability of MXene under strain has been guaranteed. This work not only provides fundamental insights into the strain effect on catalysis but also pioneers a new avenue toward the rational design of superior NRR catalysts.

Theoretical study of highly efficient VS2-based single-atom catalysts for lithium-sulfur batteries

Lithium-sulfur (Li-S) batteries have become a research hotspot due to their high energy density. However, they also have certain disadvantages and limitations. To enhance the performance of Li-S batteries, this study focuses on the utilization of transition metal (TM)-embedded vanadium disulfide (VS2) materials as cathode catalysts. Using density functional theory (DFT), comprehensive calculations and atomic-level screening of ten TM atoms were conducted to understand the underlying mechanisms and explore the potential of TM@VS2 catalysts for enhancing battery performance. The computational results indicate that five selected catalysts possess sufficient bonding strength towards high-order lithium polysulfide intermediates by the formation of a significant covalent bond between S atoms in Li2Sn and TM atoms, thereby effectively suppressing the shuttle effect. The Ni@VS2 catalyst can effectively decrease the decomposition energy barrier of Li2S in the charge reaction and can have an optimal Gibbs free energy at the rate-determining step among TM@VS2 catalysts for the discharge reaction. This study elucidates the mechanism of VS2-based transition-metal single-atom catalysts and provides an effective reference for the anchoring of TM atoms on other materials.

Electrocatalytic Urea Synthesis via N2 Dimerization and Universal Descriptor

Electrocatalytic urea synthesis through N2 + CO2 coreduction and C-N coupling is a promising and sustainable alternative to harsh industrial processes. Despite considerable efforts, limited progress has been made due to the challenges of breaking inert N≡N bonds for C-N coupling, competing side reactions, and the absence of theoretical principles guiding catalyst design. In this study, we propose a mechanism for highly electrocatalytic urea synthesis using two adsorbed N2 molecules and CO as nitrogen and carbon sources, respectively. This mechanism circumvents the challenging step of N≡N bond breaking and selective CO2 to CO reduction, as the free CO molecule inserts into dimerized *N2 and binds concurrently with two N atoms, forming a specific urea precursor *NNCONN* with both thermodynamic and kinetic feasibility. Through the proposed mechanism, Ti2@C4N3 and V2@C4N3 are identified as highly active catalysts for electrocatalytic urea formation, exhibiting low onset potentials of -0.741 and -0.738 V, respectively. Importantly, taking transition metal atoms anchored on porous graphite-like carbonitride (TM2@C4N3) as prototypes, we introduce a simple descriptor, namely, effective d electron number (Φ), to quantitatively describe the structure-activity relationships for urea formation. This descriptor incorporates inherent atomic properties of the catalyst, such as the number of d electrons, the electronegativity of the metal atoms, and the generalized electronegativity of the substrate atoms, making it potentially applicable to other urea catalysts. Our work advances the comprehension of mechanisms and provides a universal guiding principle for catalyst design in urea electrochemical synthesis.

Machine Learning Confirms the Formation Mechanism of a Single-Atom Catalyst via Infrared Spectroscopic Analysis

Single-atom catalysts (SACs) offer significant potential across various applications, yet our understanding of their formation mechanism remains limited. Notably, the pyrolysis of zeolitic imidazolate frameworks (ZIFs) stands as a pivotal avenue for SAC synthesis, of which the mechanism can be assessed through infrared (IR) spectroscopy. However, the prevailing analysis techniques still rely on manual interpretation. Here, we report a machine learning (ML)-driven analysis of the IR spectroscopy to unravel the pyrolysis process of Pt-doped ZIF-67 to synthesize Pt-Co3O4 SAC. Demonstrating a total Pearson correlation exceeding 0.7 with experimental data, the algorithm provides correlation coefficients for the selected structures, thereby confirming crucial structural changes with time and temperature, including the decomposition of ZIF and formation of Pt-O bonds. These findings reveal and confirm the formation mechanism of SACs. As demonstrated, the integration of ML algorithms, theoretical simulations, and experimental spectral analysis introduces an approach to deciphering experimental characterization data, implying its potential for broader adoption.

A simple descriptor for the nitrogen reduction reaction over single atom catalysts

The performance of supported catalysts is largely decided by metal-support interactions, which is of great significance for the rational design of catalysts. However, how to quantify the structure-activity relationship of supported catalysts remains a great challenge. In this work, taking MoS₂ and WS₂ supported single atom catalysts (SACs) as prototypes, a simple descriptor, namely, effective d electron number (labeled as Φ), is constructed to quantitatively describe the effect of metal-support interaction on the nitrogen reduction reaction (NRR) activity. This descriptor merely consists of intrinsic properties of the catalyst (including the number of d electrons, electronegativity of the metal atoms and generalized electronegativity of the substrate atoms) and can accurately predict the limiting potential (U_L) for the NRR, with no need for any density functional theory calculations. Moreover, this descriptor possesses superb expansibility that can be applied to other materials, including other metal dichalcogenide (MoSe₂, MoTe₂, WSe₂, WTe₂ and NbS₂) and even MXene (V₂CO₂, Ti₂CO₂ and Nb₂CO₂)-supported SACs. On this basis, a fast screening of excellent NRR catalysts among these systems is performed and three promising NRR catalysts (i.e. Mo@WTe₂, Mo@V₂CO₂ and Re@NbS₂) are successfully selected with U_L as low as -0.32, -0.24 and -0.31 V, respectively. This work offers new opportunities for advancing the rapid discovery of high-efficiency NRR catalysts, and the design principle is expected to be widely applicable to other catalytic systems and beyond.

Machine Learning: A New Paradigm in Computational Electrocatalysis

Designing and screening novel electrocatalysts, understanding electrocatalytic mechanisms at an atomic level, and uncovering scientific insights lie at the center of the development of electrocatalysis. Despite certain success in experiments and computations, it is still difficult to achieve the above objectives due to the complexity of electrocatalytic systems and the vastness of the chemical space for candidate electrocatalysts. With the advantage of machine learning (ML) and increasing interest in electrocatalysis for energy conversion and storage, data-driven scientific research motivated by artificial intelligence (AI) has provided new opportunities to discover promising electrocatalysts, investigate dynamic reaction processes, and extract knowledge from huge data. In this Perspective, we summarize the recent applications of ML in electrocatalysis, including the screening of electrocatalysts and simulation of electrocatalytic processes. Furthermore, interpretable machine learning methods for electrocatalysis are discussed to accelerate knowledge generation. Finally, the blueprint of machine learning is envisaged for future development of electrocatalysis.

Fe-VS2 Electrocatalyst with Organic Matrix-Mediated Electron Transfer for Highly Efficient Nitrogen Fixation

Electrochemical N₂ fixation is considered to be a promising alternative to Haber-Bosch technology. Inspired by the composition and structure of natural nitrogenase, Fe-doped VS₂ nanosheets were prepared via one-step solvothermal method. The electron transfer system mediated by organic conductive polymer (1-AAQ-PA) was constructed to promote the electron transfer between Fe-VS₂ nanosheets and the electrode in electrocatalytic N₂ reduction reaction (NRR). The obtained 1-AAQ-PA-Fe-VS₂ electrode converted N₂ to NH₃ with a yield of 31.6 μg h^-1  mg^-1 at -0.35 V vs. reversible hydrogen electrode and high faradaic efficiency of 23.5 %. The introduction of Fe dopants favored N₂ adsorption and activation, while the Li-S bond between Fe-VS₂ and Li₂ SO₄ effectively inhibited hydrogen evolution. The highly efficient electron utilization in the electrocatalytic NRR process was realized using the 1-AAQ-PA as the electron transfer medium. Density functional theory calculations showed that N₂ was preferentially adsorbed on Fe and reduced to NH₃ via both distal and alternating mechanism.

Computational screening of single-atom catalysts supported by VS2 monolayers for electrocatalytic oxygen reduction/evolution reactions

The development of highly efficient bifunctional electrocatalysts to boost oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is highly desirable for energy conversion and storage devices. Herein, by means of comprehensive first-principles computations, we systematically explored the catalytic activities of a series of single transition metal atoms anchored on two-dimensional VS₂ monolayers (TM@VS₂) for ORR/OER. Our results revealed that Ni@VS₂ exhibits low overpotentials for both ORR (0.45 V) and OER (0.31 V), suggesting its great potential as a bifunctional catalyst, which is mainly induced by its moderate interaction with oxygenated intermediates according to the established scaling relationship and volcano plot. Interestingly, the substituted doping of nitrogen heteroatoms into the VS₂ substrate can further effectively improve the ORR/OER activity of the active metal atom to achieve more eligible ORR/OER bifunctional catalysts. Our results not only propose a new class of potential bifunctional oxygen catalysts but also offer a feasible strategy for further tuning their catalytic activity.

Termination-Accelerated Electrochemical Nitrogen Fixation on Single-Atom Catalysts Supported by MXenes

The synthesis of ammonia (NH₃) from nitrogen (N₂) under ambient conditions is of great significance but hindered by the lack of highly efficient catalysts. By performing first-principles calculations, we have investigated the feasibility for employing a transition metal (TM) atom, supported on Ti₃C₂T₂ MXene with O/OH terminations, as a single-atom catalyst (SAC) for electrochemical nitrogen reduction. The potential catalytic performance of TM single atoms is evaluated by their adsorption behavior on the MXene, together with their ability to bind N₂ and to desorb NH₃ molecules. Of importance, the OH terminations on Ti₃C₂T₂ MXene can effectively enhance the N₂ adsorption and decrease the NH₃ adsorption for single atoms. Based on proposed criteria for promising SACs, our calculations further demonstrate that the Ni/Ti₃C₂O_0.19(OH)_1.81 exhibits reasonable thermodynamics and kinetics toward electrochemical nitrogen reduction.

Synergistic Effects of Crystal Phase and Strain for N2 Dissociation on Ru(0001) Surfaces with Multilayered Hexagonal Close-Packed Structures

The synergistic effects of strain and crystal phase on the reaction activity of nitrogen molecule dissociation have been studied using density functional theory calculations on Ru(0001) surfaces with multilayered hexagonal close-packed structures. The phase transformation from hexagonal close-packed phase (2H) to face-centered cubic (3C) phase or unconventional phases (4H, DHCP, 6H1, and 6H2) would occur under the uniaxial tensile strain loaded along the c axis. The close-packed surfaces of unconventional crystal phases show an enhanced chemical reactivity for N adsorption due to the upshifted d-band center of Ru. However, the N2 adsorption energy is almost independent of the applied strain and crystal phase. The optimized catalytic activity of Ru(0001) surfaces with the unconventional phases is found for the N2 dissociation through breaking the scaling relationships between the reaction barrier and reaction energy. Our results indicate that the strain-induced phase transformation is an effective method to improve the catalytic activity of noble metal catalysts toward the N2 dissociation reaction.

Low-dimensional heterostructures for advanced electrocatalysis: an experimental and computational perspective

Low dimensional electrocatalytic heterostructures have recently attracted significant attention in the catalysis community due to their highly tuneable interfaces and exciting electronic features, opening up new possibilities for effective nanometric control of both the charge carriers and energetic states of several intermediate catalytic species. In-depth understanding of electrocatalytic routes at the interface between two or more low-dimensional nanostructures has triggered the development of heterostructure nanocatalysts with extraordinary properties for water splitting reactions, NRR and CO₂RR. This tutorial review provides an overview of the most recent advances in synthetic strategies for 0D-1D, 0D-2D, and 2D-2D nanoheterostructures, discussing key aspects of their electrocatalytic performances from experimental and computational perspectives as well as their applications towards the development of overall water splitting and Zn-air battery devices.