Machine learning (ML) integrated with density functional theory (DFT) calculations have recently been used to accelerate the design and discovery of single-atom catalysts (SACs) by establishing deep structure–activity relationships. The traditional ML models are always difficult to identify the structural differences among the single-atom systems with different modification methods, leading to the limitation of the potential application range. Aiming to the structural properties of several typical two-dimensional MA₂Z₄-based single-atom systems (bare MA₂Z₄ and metal single-atom doped/supported MA₂Z₄), an improved crystal graph convolutional neural network (CGCNN) classification model was employed, instead of the traditional machine learning regression model, to address the challenge of incompatibility in the studied systems. The CGCNN model was optimized using crystal graph representation in which the geometric configuration was divided into active layer, surface layer, and bulk layer (ASB-GCNN). Through ML and DFT calculations, five potential single-atom hydrogen evolution reaction (HER) catalysts were screened from chemical space of 600 MA₂Z₄-based materials, especially V₁/HfSn₂N₄(S) with high stability and activity (ΔG_H* is 0.06 eV). Further projected density of states (pDOS) analysis in combination with the wave function analysis of the SAC-H bond revealed that the SAC-dz² orbital coincided with the H-s orbital around the energy level of −2.50 eV, and orbital analysis confirmed the formation of σ bonds. This study provides an efficient multistep screening design framework of metal single-atom catalyst for HER systems with similar two-dimensional supports but different geometric configurations.

Electrocatalytic two-electron oxygen reduction reaction (2e⁻ ORR) is a promising method for producing green and sustainable H₂O₂ but lacks high selectivity and yields electrocatalysts. And it is critical to develop catalysts that meet industrial demands. Herein, we report the different ratios of Bi⁰/Bi³⁺ supported on a phosphorus, nitrogen, and carbon nanosheet (Bi/PNC), which can reduce O₂ to H₂O₂ with high selectivity (up to 97.75% at 0.4 V_RHE) in 0.1 M KOH electrolyte and retain 97% selectivity even after 100 h electrolysis. Then a homemade flow-cell system was built for electrocatalytic production of H₂O₂ under an O₂ atmosphere using an improved gas diffusion electrode. The Bi/PNC-4 can achieve a high H₂O₂ yield of 2.76 mol·g_catalyst⁻¹·h⁻¹ (alkaline), 5.29 mol·g_catalyst⁻¹·h⁻¹ (neutral), and 3.50 mol·g_catalyst⁻¹·h⁻¹ (acid) in universal pH conditions. The in-situ generated H₂O₂ can function as a degradation agent for efficiently degrading pesticides and antibiotics. The outstanding selectivity and activities are attributed to the synergistic effects of Bi⁰ and Bi³⁺ that promote proton-coupled reduction of O₂ to OOH* (∆G_OOH* = 4.27 eV), and the formation of H₂O₂. The fast yield of H₂O₂ on Bi/PNC catalysts in flow-cell provides a promising path of electrocatalytic 2e⁻ ORR for practical H₂O₂ production.

Electrochemical oxygen reduction reaction (ORR) for preparing hydrogen peroxide (H₂O₂) is a promising way to replace the anthraquinone method. The key to H₂O₂ production is the development of catalysts to regulate the oxygen reduction reaction pathway. Here, nitrogen-doped Nb₂CT_x was prepared by NH₃ annealing method. Compared with precursor Nb₂AlC (67.01%) and pure Nb₂CT_x (75.70%), nitrogen-doped Nb₂CT_x exhibited excellent performance for 2e⁻ ORR with > 90% H₂O₂ selectivity (at 0.4 V vs. reversible hydrogen electrode (RHE)). Faradic efficiency of nitrogen-doped Nb₂CT_x reached 80.75%, whereas those for Nb₂AlC and Nb₂CT_x were 60.35% and 39.27%, respectively. A desirable catalytic stability for 50 h was observed. Density functional theory (DFT) calculations indicated excellent activity of the nitrogen-doped Nb₂CT_x was attributed to the introduction of N. This excellent activity was conducive to the adsorption of oxygen and promoted the formation of the OOH intermediate. This work can serve as an important reference for regulating the electronic structure of MXene to expand the application area in the electrochemical field.

Active-phase engineering is regularly utilized to tune the selectivity of metal nanoparticles (NPs) in heterogeneous catalysis. However, the lack of understanding of the active phase in electrocatalysis has hampered the development of efficient catalysts for CO₂ electroreduction. Herein, we report the systematic engineering of active phases of Pd NPs, which are exploited to select reaction pathways for CO₂ electroreduction. In situ X-ray absorption spectroscopy, in situ attenuated total reflection-infrared spectroscopy, and density functional theory calculations suggest that the formation of a hydrogen-adsorbed Pd surface on a mixture of the α- and β-phases of a palladium-hydride core (α+β PdH_x@PdH_x) above -0.2 V (vs. a reversible hydrogen electrode) facilitates formate production via the HCOO^* intermediate, whereas the formation of a metallic Pd surface on the β-phase Pd hydride core (β PdH_x@Pd) below -0.5 V promotes CO production via the COOH^* intermediate. The main product, which is either formate or CO, can be selectively produced with high Faradaic efficiencies (> 90%) and mass activities in the potential window of 0.05 to -0.9 V with scalable application demonstration.