Predicting Catalysis: Understanding Ammonia Synthesis from First-Principles Calculations

Electrocatalysts for Urea Synthesis from CO2 and Nitrogenous Species: From CO2 and N2/NOx Reduction to urea synthesis

The traditional industrial synthesis of urea relies on the energy-intensive and polluting process, namely the Haber-Bosch method for ammonia production, followed by the Bosch-Meiser process for urea synthesis. In contrast, electrocatalytic C-N coupling from carbon dioxide (CO2) and nitrogenous species presents a promising alternative for direct urea synthesis under ambient conditions, bypassing the need for ammonia production. This review provides an overview of recent progress in the electrocatalytic coupling of CO2 and nitrogen sources for urea synthesis. It focuses on the role of intermediate species and active site structures in promoting urea synthesis, drawing from insights into reactants' adsorption behavior and interactions with catalysts tailored for CO2 reduction, nitrogen reduction, and nitrate reduction. Advanced electrocatalyst design strategies for urea synthesis from CO2 and nitrogenous species under ambient conditions are explored, providing insights for efficient catalyst design. Key challenges and prospective directions are presented in the conclusion. Mechanistic studies elucidating the C-N coupling reaction and future development directions are discussed. The review aims to inspire further research and development in electrocatalysts for electrochemical urea synthesis.

Assessing Exchange-Correlation Functionals for Heterogeneous Catalysis of Nitrogen Species

Increasing interest in the sustainable synthesis of ammonia, nitrates, and urea has led to an increase in studies of catalytic conversion between nitrogen-containing compounds using heterogeneous catalysts. Density functional theory (DFT) is commonly employed to obtain molecular-scale insight into these reactions, but there have been relatively few assessments of the exchange-correlation functionals that are best suited for heterogeneous catalysis of nitrogen compounds. Here, we assess a range of functionals ranging from the generalized gradient approximation (GGA) to the random phase approximation (RPA) for the formation energies of gas-phase nitrogen species, the lattice constants of representative solids from several common classes of catalysts (metals, oxides, and metal-organic frameworks (MOFs)), and the adsorption energies of a range of nitrogen-containing intermediates on these materials. The results reveal that the choice of exchange-correlation functional and van der Waals correction can have a surprisingly large effect and that increasing the level of theory does not always improve the accuracy for nitrogen-containing compounds. This suggests that the selection of functionals should be carefully evaluated on the basis of the specific reaction and material being studied.

First-principles surface reaction rates by ring polymer molecular dynamics and neural network potential: role of anharmonicity and lattice motion

Elementary gas-surface processes are essential steps in heterogeneous catalysis. A predictive understanding of catalytic mechanisms remains challenging due largely to difficulties in accurately characterizing the kinetics of such steps. Experimentally, thermal rates for elementary surface reactions can now be measured using a novel velocity imaging technique, providing a stringent testing ground for ab initio rate theories. Here, we propose to combine ring polymer molecular dynamics (RPMD) rate theory with state-of-the-art first-principles-determined neural network potential to calculate surface reaction rates. Taking NO desorption from Pd(111) as an example, we show that the harmonic approximation and the neglect of lattice motion in the commonly-used transition state theory overestimates and underestimates the entropy change during the desorption process, respectively, leading to opposite errors in rate coefficient predictions and artificial error cancellations. Including anharmonicity and lattice motion, our results reveal a generally neglected surface entropy change due to significant local structural change during desorption and obtain the right answer for the right reasons. Although quantum effects are found to be less important in this system, the proposed approach establishes a more reliable theoretical benchmark for accurately predicting the kinetics of elementary gas-surface processes.

Achieving volatile potassium promoted ammonia synthesis via mechanochemistry

Potassium oxide (K₂O) is used as a promotor in industrial ammonia synthesis, although metallic potassium (K) is better in theory. The reason K₂O is used is because metallic K, which volatilizes around 400 °C, separates from the catalyst in the harsh ammonia synthesis conditions of the Haber-Bosch process. To maximize the efficiency of ammonia synthesis, using metallic K with low temperature reaction below 400 °C is prerequisite. Here, we synthesize ammonia using metallic K and Fe as a catalyst via mechanochemical process near ambient conditions (45 °C, 1 bar). The final ammonia concentration reaches as high as 94.5 vol%, which was extraordinarily higher than that of the Haber-Bosch process (25.0 vol%, 450 °C, 200 bar) and our previous work (82.5 vol%, 45 °C, 1 bar).

Finite-Size Error Cancellation in Diffusion Monte Carlo Calculations of Surface Chemistry

The accurate prediction of reaction mechanisms in heterogeneous (surface) catalysis is one of the central challenges in computational chemistry. Quantum Monte Carlo methods─Diffusion Monte Carlo (DMC) in particular─are being recognized as higher-accuracy, albeit more computationally expensive, alternatives to Density Functional Theory (DFT) for energy predictions of catalytic systems. A major computational bottleneck in the broader adoption of DMC for catalysis is the need to perform finite-size extrapolations by simulating increasingly large periodic cells (supercells) to eliminate many-body finite-size effects and obtain energies in the thermodynamic limit. Here, we show that it is possible to significantly reduce this computational cost by leveraging the cancellation of many-body finite-size errors that accompanies the evaluation of energy differences when calculating quantities like adsorption (binding) energies and mapping potential energy surfaces. We analyze the cancellation and convergence of many-body finite-size errors in two well-known adsorbate/slab systems, H₂O/LiH(001) and CO/Pt(111). Based on this analysis, we identify strategies for obtaining binding energies in the thermodynamic limit that optimally utilize error cancellation to balance accuracy and computational efficiency. Using one such strategy, we then predict the correct order of adsorption site preference on CO/Pt(111), a challenging problem for a wide range of density functionals. Our accurate and inexpensive DMC calculations are found to unambiguously recover the top > bridge > hollow site order, in agreement with experimental observations. We proceed to use this DMC method to map the potential energy surface of CO hopping between Pt(111) adsorption sites. This reveals the existence of an L-shaped top-bridge-hollow diffusion trajectory characterized by energy barriers that provide an additional kinetic justification for experimental observations of CO/Pt(111) adsorption. Overall, this work demonstrates that it is routinely possible to achieve order-of-magnitude speedups and memory savings in DMC calculations by taking advantage of error cancellation in the calculation of energy differences that are ubiquitous in heterogeneous catalysis and surface chemistry more broadly.

Deep Learning-Assisted Investigation of Electric Field-Dipole Effects on Catalytic Ammonia Synthesis

External electric fields can modify binding energies of reactive surface species and enhance catalytic performance of heterogeneously catalyzed reactions. In this work, we used density functional theory (DFT) calculations-assisted and accelerated by a deep learning algorithm-to investigate the extent to which ruthenium-catalyzed ammonia synthesis would benefit from application of such external electric fields. This strategy allows us to determine which electronic properties control a molecule's degree of interaction with external electric fields. Our results show that (1) field-dependent adsorption/reaction energies are closely correlated to the dipole moments of intermediates over the surface, (2) a positive field promotes ammonia synthesis by lowering the overall energetics and decreasing the activation barriers of the potential rate-limiting steps (e.g., NH2 hydrogenation) over Ru, (3) a positive field (>0.6 V/Å) favors the reaction mechanism by avoiding kinetically unfavorable N≡N bond dissociation over Ru(1013), and (4) local adsorption environments (i.e., dipole moments of the intermediates in the gas phase, surface defects, and surface coverage of intermediates) influence the resulting surface adsorbates' dipole moments and further modify field-dependent reaction energetics. The deep learning algorithm developed here accelerates field-dependent energy predictions with acceptable accuracies by five orders of magnitudes compared to DFT alone and has the capacity of transferability, which can predict field-dependent energetics of other catalytic surfaces with high-quality performance using little training data.

A review on sensing and catalytic activity of nano-catalyst for synthesis of one-step ammonia and urea: Challenges and perspectives

One of the most significant chemical operations in the past century was the Haber-Bosch catalytic synthesis of ammonia, a fertilizer vital to human life. Many catalysts are developed for effective route of ammonia synthesis. The major challenges are to reduce temperature and pressure of process and to improve conversion of reactants produce green ammonia. The present review, briefly discusses the evolution of ammonia synthesis and current advances in nanocatalyst development. There are promising new ammonia synthesis catalysts of different morphology as well as magnetic nanoparticles and nanowires that could replace conventional Fused-Fe and Promoted-Ru catalysts in existing ammonia synthesis plants. These magnetic nanocatalyst could be basis for the production of magnetically induced one-step green ammonia and urea synthesis processes in future.

Autonomous Reaction Network Exploration in Homogeneous and Heterogeneous Catalysis

Autonomous computations that rely on automated reaction network elucidation algorithms may pave the way to make computational catalysis on a par with experimental research in the field. Several advantages of this approach are key to catalysis: (i) automation allows one to consider orders of magnitude more structures in a systematic and open-ended fashion than what would be accessible by manual inspection. Eventually, full resolution in terms of structural varieties and conformations as well as with respect to the type and number of potentially important elementary reaction steps (including decomposition reactions that determine turnover numbers) may be achieved. (ii) Fast electronic structure methods with uncertainty quantification warrant high efficiency and reliability in order to not only deliver results quickly, but also to allow for predictive work. (iii) A high degree of autonomy reduces the amount of manual human work, processing errors, and human bias. Although being inherently unbiased, it is still steerable with respect to specific regions of an emerging network and with respect to the addition of new reactant species. This allows for a high fidelity of the formalization of some catalytic process and for surprising in silico discoveries. In this work, we first review the state of the art in computational catalysis to embed autonomous explorations into the general field from which it draws its ingredients. We then elaborate on the specific conceptual issues that arise in the context of autonomous computational procedures, some of which we discuss at an example catalytic system.

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SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11244-021-01543-9.

Comprehensive Understanding of the Thriving Ambient Electrochemical Nitrogen Reduction Reaction

The electrochemical method of combining N₂ and H₂ O to produce ammonia (i.e., the electrochemical nitrogen reduction reaction [E-NRR]) continues to draw attention as it is both environmentally friendly and well suited for a progressively distributed farm economy. Despite the multitude of recent works on the E-NRR, further progress in this field faces a bottleneck. On the one hand, despite the extensive exploration and trial-and-error evaluation of E-NRR catalysts, no study has stood out to become the stage protagonist. On the other hand, the current level of ammonia production (microgram-scale) is an almost insurmountable obstacle for its qualitative and quantitative determination, hindering the discrimination between true activity and contamination. Herein i) the popular theory and mechanism of the NRR are introduced; ii) a comprehensive summary of the recent progress in the field of the E-NRR and related catalysts is provided; iii) the operational procedures of the E-NRR are addressed, including the acquisition of key metrics, the challenges faced, and the most suitable solutions; iv) the guiding principles and standardized recommendations for the E-NRR are emphasized and future research directions and prospects are provided.

Polarizability of atomic Pt, Pt+, and Pt. J Chem Phys 2021;154:174302. [PMID: 34241047 DOI: 10.1063/5.0044996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Electrostatic properties are important for understanding and modeling many phenomena, such as the adsorption of a catalytic metal upon an oxide support. The charge transfer between the metal and the support can lead to positive or negative charges on the metal. Here, the static dipole polarizability is computed for atomic platinum in charge states 0, +1, and -1 in several low-lying electronic terms and levels. Core pseudopotentials are used along with coupled-cluster theory. The best results are estimates for the coupled-cluster CCSDTQ/q-aug-cc-pwCV∞Z-PP values for atomic terms, combined with compositional data from spin-orbit configuration interaction. The polarizability of the anion Pt^- is especially challenging for the theory with wildly varying results from different coupled-cluster perturbative approximations such as CCSD(T). For atomic mercury (Hg), selected as a nearby experimental value, our polarizability volume is larger than experiment by 0.8 bohrs³ (or 0.12 × 10^-30 m³). For the ground level of neutral platinum, Pt(³D₃), we find α₀ = (41.2 ± 1.1) bohrs³ or (6.10 ± 0.16) × 10^-30 m³. A handful of density functional theory methods are tested and found generally within 10% of our best values.

Dinitrogen Insertion and Cleavage by a Metal-Metal Bonded Tricobalt(I) Cluster

Reduction of a tricobalt(II) tri(bromide) cluster supported by a tris(β-diketiminate) cyclophane results in halide loss, ligand compression, and metal-metal bond formation to yield a 48-electron Co^I₃ cluster, Co₃L^Et/Me (2). Upon reaction of 2 with dinitrogen, all metal-metal bonds are broken, steric conflicts are relaxed, and dinitrogen is incorporated within the internal cavity to yield a formally (μ₃-η¹:η²:η¹-dinitrogen)tricobalt(I) complex, 3. Broken symmetry DFT calculations (PBE0/def2-tzvp/D3) support an N-N bond order of 2.1 in the bound N₂ with the calculated N-N stretching frequency (1743 cm^-1) comparable to the experimental value (1752 cm^-1). Reduction of 3 under Ar in the presence of Me₃SiBr results in N₂ scission with tris(trimethylsilyl)amine afforded in good yield.

The Key Role of Active Sites in the Development of Selective Metal Oxide Sensor Materials

Development of sensor materials based on metal oxide semiconductors (MOS) for selective gas sensors is challenging for the tasks of air quality monitoring, early fire detection, gas leaks search, breath analysis, etc. An extensive range of sensor materials has been elaborated, but no consistent guidelines can be found for choosing a material composition targeting the selective detection of specific gases. Fundamental relations between material composition and sensing behavior have not been unambiguously established. In the present review, we summarize our recent works on the research of active sites and gas sensing behavior of n-type semiconductor metal oxides with different composition (simple oxides ZnO, In₂O₃, SnO₂, WO₃; mixed-metal oxides BaSnO₃, Bi₂WO₆), and functionalized by catalytic noble metals (Ru, Pd, Au). The materials were variously characterized. The composition, metal-oxygen bonding, microstructure, active sites, sensing behavior, and interaction routes with gases (CO, NH₃, SO₂, VOC, NO₂) were examined. The key role of active sites in determining the selectivity of sensor materials is substantiated. It was shown that the metal-oxygen bond energy of the MOS correlates with the surface acidity and the concentration of surface oxygen species and oxygen vacancies, which control the adsorption and redox conversion of analyte gas molecules. The effects of cations in mixed-metal oxides on the sensitivity and selectivity of BaSnO₃ and Bi₂WO₆ to SO₂ and VOCs, respectively, are rationalized. The determining role of catalytic noble metals in oxidation of reducing analyte gases and the impact of acid sites of MOS to gas adsorption are demonstrated.

Synthetic ferripyrophyllite: preparation, characterization and catalytic application

Sheet silicates, also known as phyllosilicates, contain parallel sheets of tetrahedral silicate built up by [Si₂O₅]^2- entities connected through intermediate metal-oxygen octahedral layers. The well-known minerals talc and pyrophyllite are belonging to this group based on magnesium and aluminium, respectively. Surprisingly, the ferric analogue rarely occurs in nature and is found in mixtures and conglomerates with other materials only. While partial incorporation of iron into pyrophyllites has been achieved, no synthetic protocol for purely iron-based pyrophyllite has been published yet. Here we report about the first artificial synthesis of ferripyrophyllite under exceptional mild conditions. A similar ultrathin two-dimensional (2D) nanosheet morphology is obtained as in talc or pyrophyllite but with iron(iii) as a central metal. The high surface material exhibits a remarkably high thermostability. It shows some catalytic activity in ammonia synthesis and can serve as catalyst support material for noble metal nanoparticles.

Photochemical activation of carbon dioxide in Mg+(CO2)(H2O)0,1

We combine multi-reference ab initio calculations with UV-VIS action spectroscopy to study photochemical activation of CO2 on a singly charged magnesium ion, [MgCO2(H2O)0,1]+, as a model system for the metal/ligand interactions relevant in CO2 photochemistry. For the non-hydrated species, two separated Mg+ 3s-3p bands are observed within 5.0 eV. The low-energy band splits upon hydration with one water molecule. [Mg(CO2)]+ decomposes highly state-selectively, predominantly via multiphoton processes. Within the low-energy band, CO2 is exclusively lost within the excited state manifold. For the high-energy band, an additional pathway becomes accessible: the CO2 ligand is activated via a charge transfer, with photochemistry taking place on the CO2 - moiety eventually leading to a loss of CO after absorption of a second photon. Upon hydration, already excitation into the first and second excited state leads to CO2 activation in the excited state minimum; however, CO2 predominantly evaporates upon fluorescence or absorption of another photon.

Setting benchmarks for modelling gas-surface interactions using coherent control of rotational orientation states

The coherent evolution of a molecular quantum state during a molecule-surface collision is a detailed descriptor of the interaction potential which was so far inaccessible to measurements. Here we use a magnetically controlled molecular beam technique to study the collision of rotationally oriented ground state hydrogen molecules with a lithium fluoride surface. The coherent control nature of the technique allows us to measure the changes in the complex amplitudes of the rotational projection quantum states, and express them using a scattering matrix formalism. The quantum state-to-state transition probabilities we extract reveal a strong dependency of the molecule-surface interaction on the rotational orientation of the molecules, and a remarkably high probability of the collision flipping the rotational orientation. The scattering matrix we obtain from the experimental data delivers an ultra-sensitive benchmark for theory to reproduce, guiding the development of accurate theoretical models for the interaction of H₂ with a solid surface.

A fundamental and predictive understanding of molecule-surface interactions is challenging to obtain. Here the authors report an experimental technique allowing direct measurement of the scattering matrix, which reports on the coherent evolution of quantum states of a molecule scattering from a surface.

Graphene Oxyhydride Catalysts in View of Spin Radical Chemistry

This article discusses carbocatalysis that are provided with amorphous carbons. The discussion is conducted from the standpoint of the spin chemistry of graphene molecules, in the framework of which the amorphous carbocatalysts are a conglomerate of graphene-oxynitrothiohydride stable radicals presenting the basic structure units (BSUs) of the species. The chemical activity of the BSUs atoms is reliably determined computationally, which allows mapping the distribution of active sites in these molecular catalysts. The presented maps reliably show the BSUs radicalization provided with carbon atoms only, the nonterminated edge part of which presents a set of active sites. Spin mapping of carbocatalysts active sites is suggested as the first step towards the spin carbocatalysis of the species.

Photoactive Earth-Abundant Iron Pyrite Catalysts for Electrocatalytic Nitrogen Reduction Reaction

The generation of ammonia, hydrogen production, and nitrogen purification are considered as energy intensive processes accompanied with large amounts of CO₂ emission. An electrochemical method assisted by photoenergy is widely utilized for the chemical energy conversion. In this work, earth-abundant iron pyrite (FeS₂ ) nanocrystals grown on carbon fiber paper (FeS₂ /CFP) are found to be an electrochemical and photoactive catalyst for nitrogen reduction reaction under ambient temperature and pressure. The electrochemical results reveal that FeS₂ /CFP achieves a high Faradaic efficiency (FE) of ≈14.14% and NH₃ yield rate of ≈0.096 µg min^-1 at -0.6 V versus RHE electrode in 0.25 m LiClO₄ . During the electrochemical catalytic reaction, the crystal structure of FeS₂ /CFP remains in the cubic pyrite phase, as analyzed by in situ X-ray diffraction measurements. With near-infrared laser irradiation (808 nm), the NH₃ yield rate of the FeS₂ /CFP catalyst can be slightly improved to 0.1 µg min^-1 with high FE of 14.57%. Furthermore, density functional theory calculations demonstrate that the N₂ molecule has strong chemical adsorption energy on the iron atom of FeS₂ . Overall, iron pyrite-based materials have proven to be a potential electrocatalyst with photoactive behavior for ammonia production in practical applications.

Quantum Tunneling Mediated Interfacial Synthesis of a Benzofuran Derivative

Reaction pathways involving quantum tunneling of protons are fundamental to chemistry and biology. They are responsible for essential aspects of interstellar synthesis, the degradation and isomerization of compounds, enzymatic activity, and protein dynamics. On-surface conditions have been demonstrated to open alternative routes for organic synthesis, often with intricate transformations not accessible in solution. Here, we investigate a hydroalkoxylation reaction of a molecular species adsorbed on a Ag(111) surface by scanning tunneling microscopy complemented by X-ray electron spectroscopy and density functional theory. The closure of the furan ring proceeds at low temperature (down to 150 K) and without detectable side reactions. We unravel a proton-tunneling-mediated pathway theoretically and confirm experimentally its dominant contribution through the kinetic isotope effect with the deuterated derivative.

Dinitrogen Activation and Functionalization using β-Diketiminate Iron Complexes

Iron catalysts are adept at breaking the N-N bond of N₂, as exemplified by the iron-catalyzed Haber-Bosch process and the iron-containing clusters at the active sites of nitrogenase enzymes. This Minireview summarizes recent work that has identified a well-characterized set of multi-iron complexes that are capable of breaking and functionalizing N₂, and are amenable to detailed mechanistic studies. We discuss the redox balancing, the potential intermediates during N₂ activation, the variation of alkali metal reductant, the reversibility of N₂ cleavage, and the formation of N-H and N-C bonds from N₂.

Enhancing Electrocatalytic Water Splitting by Strain Engineering

Electrochemical water splitting driven by sustainable energy such as solar, wind, and tide is attracting ever-increasing attention for sustainable production of clean hydrogen fuel from water. Leveraging these advances requires efficient and earth-abundant electrocatalysts to accelerate the kinetically sluggish hydrogen and oxygen evolution reactions (HER and OER). A large number of advanced water-splitting electrocatalysts have been developed through recent understanding of the electrochemical nature and engineering approaches. Specifically, strain engineering offers a novel route to promote the electrocatalytic HER/OER performances for efficient water splitting. Herein, the recent theoretical and experimental progress on applying strain to enhance heterogeneous electrocatalysts for both HER and OER are reviewed and future opportunities are discussed. A brief introduction of the fundamentals of water-splitting reactions, and the rationalization for utilizing mechanical strain to tune an electrocatalyst is given, followed by a discussion of the recent advances on strain-promoted HER and OER, with special emphasis given to combined theoretical and experimental approaches for determining the optimal straining effect for water electrolysis, along with experimental approaches for creating and characterizing strain in nanocatalysts, particularly emerging 2D nanomaterials. Finally, a vision for a future sustainable hydrogen fuel community based on strain-promoted water electrolysis is proposed.

Mechanism and kinetics for both thermal and electrochemical reduction of N2 catalysed by Ru(0001) based on quantum mechanics

QM calculations were used to predict the free energy surfaces for N₂ thermal and electrochemical reduction (N₂TR and N₂ER) on Ru(0001), to find the detailed atomistic mechanism and kinetics, and provide the basis for improving the efficiency of N₂ER.

Activity, Selectivity, and Durability of Ruthenium Nanoparticle Catalysts for Ammonia Synthesis by Reactive Molecular Dynamics Simulation: The Size Effect

We report a molecular dynamics (MD) simulation employing the reactive force field (ReaxFF), developed from various first-principles calculations in this study, on ammonia (NH₃) synthesis from nitrogen (N₂) and hydrogen (H₂) gases over Ru nanoparticle (NP) catalysts. Using ReaxFF-MD simulations, we predict not only the activities and selectivities but also the durabilities of the nanocatalysts and discuss the size effect and process conditions (temperature and pressure). Among the NPs (diameter = 3, 4, 5, and 10 nm) considered in this study, the 4 nm NPs show the highest activity, in contrast to our intuition that the smallest NP should provide the highest activity, as it has the highest surface area. In addition, the best selectivity is observed with the 10 nm NPs. The activity and selectivity are mainly determined by the hcp, fcc, and top sites on the Ru NP surface, which depend on the NP size. Moreover, the selectivity can be improved more significantly by increasing the H₂ pressure than by increasing the N₂ pressure. The durability of the NPs can be determined by the mean stress and the stress concentration, and these two factors have a trade-off relationship with the NP size. In other words, as the NP size increases, its mean stress decreases, whereas the stress concentration simultaneously increases. Because of these two effects, the best durability is found with the 5 nm NPs, which is also in contrast to our intuition that larger NPs should show better durability. We expect that ReaxFF-MD simulations, along with first-principles calculations, could be a useful tool in developing novel catalysts and understanding catalytic reactions.

A theoretical study of the effect of a non-aqueous proton donor on electrochemical ammonia synthesis

Ammonia synthesis is one of the most studied reactions in heterogeneous catalysis. To date, however, electrochemical N₂ reduction in aqueous systems has proven to be extremely difficult, mainly due to the competing hydrogen evolution reaction (HER). Recently, it has been shown that transition metal complexes based on molybdenum can reduce N₂ to ammonia at room temperature and ambient pressure in a non-aqueous system, with a relatively small amount of hydrogen output. We demonstrate that the non-aqueous proton donor they have chosen, 2,6-lutidinium (LutH⁺), is a viable substitute for hydronium in the electrochemical process at a solid surface, since this donor can suppress the HER rate. We also show that the presence of LutH⁺ can selectively stabilize the *NNH intermediate relative to *NH or *NH₂via the formation of hydrogen bonds, indicating that the use of non-aqueous solvents can break the scaling relationship between limiting potential and binding energies.

Metal-based heterogeneous electrocatalysts for reduction of carbon dioxide and nitrogen: mechanisms, recent advances and perspective

Recent progress in the development of metal-based heterogeneous electrocatalysts which have been used in the electrochemical reduction of carbon dioxide and nitrogen with superior performance is comprehensively and critically reviewed.

Accurate Neural Network Description of Surface Phonons in Reactive Gas-Surface Dynamics: N2 + Ru(0001)

Ab initio molecular dynamics (AIMD) simulations enable the accurate description of reactive molecule-surface scattering especially if energy transfer involving surface phonons is important. However, presently, the computational expense of AIMD rules out its application to systems where reaction probabilities are smaller than about 1%. Here we show that this problem can be overcome by a high-dimensional neural network fit of the molecule-surface interaction potential, which also incorporates the dependence on phonons by taking into account all degrees of freedom of the surface explicitly. As shown for N₂ + Ru(0001), which is a prototypical case for highly activated dissociative chemisorption, the method allows an accurate description of the coupling of molecular and surface atom motion and accurately accounts for vibrational properties of the employed slab model of Ru(0001). The neural network potential allows reaction probabilities as low as 10^-5 to be computed, showing good agreement with experimental results.

Dissociative adsorption dynamics of nitrogen on a Fe(111) surface

The dissociative adsorption dynamics of N₂ on clean Fe(111) surfaces is theoretically investigated by means of quasi-classical trajectory calculations based on a multidimensional potential energy surface built from density functional theory.