Journal of Fuel Chemistry and Technology•2026•DOI: 10.1016/S1872-5813(26)60743-8
Metal oxide catalysts have emerged as promising materials for CO2 cycloaddition reactions due to their tunable composition, facile separation, reusability, and low cost. However, systematic investigations remain limited, and a comprehensive understanding of reaction mechanisms is hindered by the lack of extensive, well-curated datasets. This study establishes a systematic dataset of 102 metal oxide catalysts, including layered double hydroxide (LDH) and ZnO, with variations in metal dopant type and ratio, defect characteristics, and crystal plane orientation. Using high-throughput first-principles calculations, we generated a multi-dimensional dataset containing elementary reaction energies, vibrational frequencies, Bader charges, and density of states. A rigorous two-tiered quality control protocol ensures data integrity. The dataset reveals structure-performance relationships linking catalyst structural features to electronic descriptors (e.g., Bader charge transfer, p-band centers of O atoms, d-band centers of metal atoms) and catalytic activity. This work provides a reliable foundation for exploring catalytic performance and reaction mechanisms, and demonstrates how high-throughput calculations can generate domain-specific, mechanistically explicit data. Future efforts will focus on developing feature extraction code for seamless integration with machine learning frameworks, and the dataset will be continuously enriched through experimental validation and remain openly accessible.
Journal of Fuel Chemistry and Technology•2026•DOI: 10.1016/S1872-5813(26)60688-3
Single-atom catalysts (SACs) exhibit near-100% atomic utilization, precisely tunable active sites, and superior catalytic performance, making them promising for ethane dehydrogenation (EDH). The nature of active metals, support properties, and coordination environments critically influence EDH performance. Graphene, with its excellent thermal stability and tunable coordination structure, serves as an ideal support. However, systematic understanding is lacking due to fragmented data. This work constructs a comprehensive database of heteroatom-doped graphene-supported SACs, encompassing five representative metal single atoms and 51 distinct coordination environments grouped into six major categories. High-throughput first-principles calculations yield multi-dimensional data including elementary reaction energies, vibrational frequencies, density of states, and Bader charges. A rigorous quality control system ensures reliability at both parameter-setting and computational result levels. The database provides complete raw calculation files, enabling in-depth analysis of catalytic performance, structure-performance relationships, and reaction mechanisms. Electronic structure analyses (DOS and Bader charge) elucidate the physical mechanisms underlying performance differences, establishing a structure-performance relationship characterized by 'dopant type → electronic state of active metal center → catalytic activity'. This database supports rational catalyst design and data-driven research paradigms, with future plans for feature extraction code and experimental validation.