Computational screening of highly selective and active electrocatalytic nitrogen reduction on single-atom-embedded artificial holey SnN3 monolayers

Machine learning-driven shortening the screening process towards high-performance nitrogen reduction reaction electrocatalysts with four-step screening strategy

The urgent need to prepare clean energy by environmentally friendly and efficient methods, which has led to widespread attention on electrocatalytic nitrogen reduction reaction (NRR) for ammonia production. At present, single atom catalytic nitrogen reduction has become the earliest promising method for industrial production due to its high atomic utilization rate, high selectivity, high controllability, and high stability. However, how to quickly screen catalysts with high catalytic efficiency and selectivity in single-atom catalysts (SACs) remains a challenge. Herein, the 29 SACs are constructed from C6N2 nanosheets doped with transition metals (TM@C6N2), which are analyzed for stability, adsorption performance, NRR catalytic activity, electronic properties, and competitiveness using first-principles calculations. The results show that Mo@C6N2 and Re@C6N2 exhibit the most outstanding catalytic performances, with limiting potentials (UL) of -0.29 and -0.31 V, respectively, in the solvent model. Machine learning is used to derive descriptors from the intrinsic features to predict the free energy changes for the potential-determining step. The importance of features is calculated, with the first ionisation energy (IE1) being the most significant influencing factor. Based on the guidance of machine learning and considering that IE1 is related to the ability of metal atoms to donate electrons, a four-step screening strategy using the Integrated Crystal Orbital Hamilton Populations (ICOHP) to screen catalysts instead of the traditional five-step screening not only improves the screening efficiency but also obtains completely consistent screening results. This work presents a new approach to predicting the catalytic performance of SACs and provides new insights into the influence of intrinsic properties on catalytic activity.

Advancing electrocatalytic reactions through mapping key intermediates to active sites via descriptors

Descriptors play a crucial role in electrocatalysis as they can provide valuable insights into the electrochemical performance of energy conversion and storage processes. They allow for the understanding of different catalytic activities and enable the prediction of better catalysts without relying on the time-consuming trial-and-error approaches. Hence, this comprehensive review focuses on highlighting the significant advancements in commonly used descriptors for critical electrocatalytic reactions. First, the fundamental reaction processes and key intermediates involved in several electrocatalytic reactions are summarized. Subsequently, three types of descriptors are classified and introduced based on different reactions and catalysts. These include d-band center descriptors, readily accessible intrinsic property descriptors, and spin-related descriptors, all of which contribute to a profound understanding of catalytic behavior. Furthermore, multi-type descriptors that collectively determine the catalytic performance are also summarized. Finally, we discuss the future of descriptors, envisioning their potential to integrate multiple factors, broaden application scopes, and synergize with artificial intelligence for more efficient catalyst design and discovery.

Transition Metal Functionalized C30N12S6 as High-Performance Trifunctional Catalysts with Integrated Descriptors toward Hydrogen Evolution, Oxygen Evolution, and Oxygen Reduction Reactions: A Case of High-Throughput First-Principles Screening within the Framework of TM-N2@C30N10S6

In energy conversion and storage technologies, the design of highly efficient trifunctional electrocatalysts integrating with the high hydrogen evolution reaction (HER) and oxygen evolution/reduction reaction (OER/ORR) activities is highly desirable. Herein, utilizing first-principles computations, a novel periodically ordered macropore C30N12S6 monolayer was proposed, and the stability analysis attests to its good stability. Single transition metal (TM) atom anchored onto this newly proposed C30N12S6 monolayer to form single-atom catalysts, as achieved by TM-N2@C30N10S6, among which the Co-N2@C30N10S6 is the most promising multifunctional catalyst toward HER/OER/ORR with low overpotential of 0.01/0.59/0.3 V; meanwhile, the Rh-N2@C30N10S6 can be used as a bifunctional OER/ORR catalyst with low overpotential of 0.37/0.44 V, overmatching the landmark Pt (111) and IrO2/RuO2 catalysts. Particularly, the TM-d orbital in TM@CNS is remarkably hybridized with the O-p orbital of oxygenated intermediates, so that the lone electrons initially located at the antibonding orbital pair up and fill the downward bonding orbital, allowing OH* to be suitably adsorbed on TM@CNS, enhancing the catalytic performance. The relevant attributes, such as good stabilities and metallic features, ensured their applications in ambient conditions. Moreover, multilevel descriptors were constructed to clarify the origin of activity on TM@CNS, such as ΔGOH* (Gibbs free energy of OH*), εd (d-band center), COHP (crystal orbital Hamilton population), Nd/Nd + s (number of d/d + s electrons) and φ (descriptor), among which the filling of outer d-electrons of TM atom significantly affects the value of ΔGOH* that can determine the overpotential and, thus, become a key descriptor.

Transition metals anchored on two-dimensional p-BN support with center-coordination scaling relationship descriptor for spontaneous visible-light-driven photocatalytic nitrogen reduction

Solar energy has the potential to revolutionize the production of ammonia, as it could provide a reliable and uninterrupted source of energy for the chemical reaction involved. However, improving the catalytic performance of catalysts often leads to a reduction in their band gaps, which results in insufficient photogenerated electron potential to realize the nitrogen reduction reaction (NRR), and thus the development of NRR efficient photocatalysts remains a great challenge. Herein, based on the density functional theory (DFT), a series of single-atom photocatalysts with transition metals (TMs) doped on porous boron nitride (p-BN) nanosheet are proposed for NRR. Among them, Re-B3@p-BN could effectively catalyze gas-phase N2 through the corresponding pathways with limiting potentials of 0.31 V. Meanwhile, it exhibits excellent light absorption efficiency under illumination and could spontaneously catalyse nitrogen fixation reactions due to the suitable forbidden band and high photogenerated electron potential. Moreover, a linear relationship descriptor based on the intrinsic properties has been established, using a machine learning approach by considering the combined effects of the central metal atom and the coordination atoms. This descriptor could help accelerate the development of rational and improved 2D NRR photocatalysts with high catalytic activity and high selectivity.

Electrochemical nitrogen fixation on single metal atom catalysts

The electrochemical reduction of nitrogen (eNRR) offers a promising alternative to the Haber-Bosch (H-B) process for producing ammonia under moderate conditions. However, the inertness of dinitrogen and the competing hydrogen evolution reaction pose significant challenges for eNRR. Thus, developing more efficient electrocatalysts requires a deeper understanding of the underlying mechanistic reactions and electrocatalytic activity. Single atom catalysts, which offer tunable catalytic properties and increased selectivity, have emerged as a promising avenue for eNRR. Carbon and metal-based substrates have proven effective for dispersing highly active single atoms that can enhance eNRR activity. In this review, we explore the use of atomically dispersed single atoms on different substrates for eNRR from both conceptual and experimental perspectives. The review is divided into four sections: the first section describes eNRR mechanistic pathways, the second section focuses on single metal atom catalysts (SMACs) with metal atoms dispersed on carbon substrates for eNRR, the third section covers SMACs with metal atoms dispersed on non-carbon substrates for eNRR, and the final section summarizes the remaining challenges and future scope of eNRR for green ammonia production.

A High-Throughput Screening toward Efficient Nitrogen Fixation: Transition Metal Single-Atom Catalysts Anchored on an Emerging π-π Conjugated Graphitic Carbon Nitride (g-C10N3) Substrate with Dirac Dispersion

TM-N_x is becoming a comforting catalytic center for sustainable and green ammonia synthesis under ambient conditions, resulting in increasing interest in single-atom catalysts (SACs) for the electrochemical nitrogen reduction reaction (NRR). However, given the poor activity and unsatisfactory selectivity of existing catalysts, it remains a long-standing challenge to design efficient catalysts for nitrogen fixation. Currently, the two-dimensional (2D) graphitic carbon-nitride substrate provides abundant and evenly distributed holes for stably supporting transition-metal atoms, which presents a fascinating prospect for overcoming this challenge and promoting single-atom NRR. An emerging holey graphitic carbon-nitride skeleton with a C₁₀N₃ stoichiometric ratio (g-C₁₀N₃) from a supercell of graphene is constructed, which provides outstanding electric conductivity for achieving high-efficiency NRR due to the Dirac band dispersion. Herein, a high-throughput first-principles calculation is carried out to evaluate the feasibility of π-d conjugated SACs resulting from a single TM atom anchored on g-C₁₀N₃ (TM = Sc-Au) for NRR. We find that W metal embedded in g-C₁₀N₃ (W@g-C₁₀N₃) can compromise the ability to adsorb the key target reaction species (N₂H and NH₂), hence acquiring an optimal NRR behavior among 27 TM-candidates. Our calculations demonstrate that W@g-C₁₀N₃ shows a well-suppressed HER ability and, impressively, a low energy cost of -0.46 V. Additionally, all-around descriptors are proposed to uncover the fundamental mechanism of NRR activity, among which a 3D volcano plot (limiting potential, screening strategy, and electron origin) uncovers the NRR activity trend, achieving a quick and high-efficiency prescreening for numerous candidates. Overall, the strategy of the structure- and activity-based TM-N_x-containing unit design will offer useful insight for further theoretical and experimental attempts.