Single-atom catalysts (SACs) have attracted considerable interest for sustainable electrocatalysis because isolated metal centers maximize atom utilization while providing tunable electronic structures and coordination environments. These characteristics make SACs promising candidates for key electrochemical reactions, including the hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), and carbon dioxide reduction reaction (CO₂RR). However, catalyst performance depends on complex interactions among metal identity, support structure, coordination environment, reaction intermediates, and operating conditions, making rational catalyst design challenging. Artificial intelligence (AI) and machine learning (ML) have emerged as valuable tools for accelerating catalyst discovery through descriptor identification, materials screening, surrogate modeling, and data-driven prediction. This review examines recent advances in AI-guided SAC electrocatalysis from a reaction-specific and sustainability-aware perspective. It discusses adsorption, electronic, and coordination descriptors used in catalyst design, together with challenges related to data quality and model reliability. Interpretable machine-learning methods such as SHAP and SISSO are also discussed, along with recent developments in graph learning, Bayesian optimization, reinforcement learning, and generative modeling. The review further discusses how operando characterization, catalyst stability, and dynamic active-site evolution influence the interpretation, transferability of AI-driven predictions, current opportunities and limitations in AI-assisted SAC discovery. The discussion emphasizes the need for catalyst-design strategies that combine predictive capability with mechanistic understanding, experimental validation, and long-term sustainability considerations.
The hydroformylation of olefins represents one of the most important industrial routes for the synthesis of aldehydes, which serve as key intermediates in the production of fine chemicals, plasticizers, and surfactants. Compared with homogeneous catalytic systems, heterogeneous transition-metal catalysts have attracted considerable attention owing to their significant advantages in catalyst recovery, recyclability, and facile product separation. In this review, heterogeneous catalytic materials for olefin hydroformylation are systematically classified according to the intrinsic properties and functionalities of the supports, such as porous organic polymers, inorganic oxides, metal–organic frameworks, zeolites. The synthetic strategies, structural features, physicochemical properties, and recent advances in the application of these materials are comprehensively surveyed. Furthermore, the influence of heterogenization strategies including the immobilization of metal active centers, surface modification of supports, confinement effects, and synergistic interactions-on catalytic activity, regioselectivity, and stability is discussed in detail. The comparative analysis reveals that porous organic polymer-supported Rh catalysts exhibit excellent activity and regioselectivity owing to their high-density phosphine ligands and atomically dispersed Rh species. Oxide-supported single-atom catalysts offer a versatile and low-cost platform, while MOF-supported catalysts benefit from tunable pore environments. Zeolite-supported systems, with shape-selective micropores, are particularly effective for light olefin conversion. Nevertheless, several challenges remain unresolved, including the dynamic evolution of active sites during catalysis, the rational design of bimetallic and dual-site catalysts, and the lack of standardized protocols for evaluating leaching and sintering.
Oxygen vacancies in spinel Co3O4 are key defects that regulate surface adsorption, redox properties and catalytic activity in oxidation reactions. This Perspective systematically examines the formation mechanisms of oxygen vacancies in Co3O4, together with a comprehensive evaluation of their characterization by FT-IR, Raman spectroscopy, electron paramagnetic resonance (EPR), X-ray photoelectron spectroscopy (XPS), and H2-temperature-programmed reduction (H2-TPR). Oxygen vacancies originate from charge-compensated removal of lattice oxygen, which is accompanied by the partial reduction of Co3+ to Co2+. By correlating spectroscopic fingerprints with redox behavior, the role of lattice distortion, Co-O bond weakening, and surface reduction in identifying OV-related structural and electronic changes is clarified. The advantages and limitations of different characterization techniques are critically evaluated, providing practical guidelines for defect engineering and reliable identification of oxygen vacancies in Co3O4-based catalysts.
The efficient removal of carbon monoxide from industrial and vehicular emissions has become a pressing practical challenge, driven by tightening emission standards and growing concerns over ambient air quality. Noble metal catalysts, despite their excellent low-temperature activity, face persistent barriers to large‑scale deployment, including high and volatile raw material costs, limited global reserves, and a strong tendency to deactivate through sintering and poisoning. Transition metal oxides-especially those based on Mn, Cu, Co, Ce, and Fe, present a viable path forward because they offer a wide range of accessible oxidation states, high concentrations of surface oxygen vacancies, and a cost structure that is suited to large‑volume applications. Single-metal oxides, composite systems, and supported architectures each present distinct active-site chemistries, yet their comparative performance in realistic feeds remains poorly mapped. Particular attention is devoted to the fundamental roles of physicochemical properties-crystal structure, morphology, metal valence distribution, and oxygen vacancy concentration-in dictating catalytic performance. Furthermore, the classical reaction mechanisms-Langmuir–Hinshelwood (L–H), Eley–Rideal (E–R), and Mars-van Krevelen (MvK)-as well as emerging theoretical insights such as the termolecular Eley–Rideal and water-mediated MvK pathways, are analyzed in detail. In response to the persistent deactivation challenges encountered in complex industrial atmospheres (especially moisture and SO2 poisoning), effective optimization strategies are summarized, including heteroatom doping, facet engineering, and metal-support interface regulation. Finally, the current bottlenecks in catalyst stability and scalability are discussed.
The aim of this work is to study the influence of the structural type of zeolites (MOR, ZSM-5) on the selectivity of 4,4-dimethyl-1,3-dioxane (DMD) via the Prins reaction in a continuous-flow reactor. For the first time, the stabilization energies of the transition state of the 1,3-dioxane formation reaction in the cavities of MOR and ZSM-5 zeolites were calculated using the semi-empirical PM6-D3H4 approximation. According to the prediction, the greatest effect on the reaction should be expected in the case of MOR zeolites. The influence of the structural type of zeolites (MOR, ZSM-5) and their cationic forms (Na+, H+) on DMD selectivity in the Prins reaction involving formaldehyde and isobutylene in a continuous-flow reactor was studied. The results demonstrated the influence of the features of the zeolite’s porous structure on DMD selectivity. The experimental data are in good agreement with the results of theoretical predictions. The role of the Brønsted acid sites of zeolites in the conversion of formaldehyde was also demonstrated. The maximum selectivity for DMD (74
