{"title":"A computational dataset for C1 molecules catalytic conversion over iron-based catalysts","authors":"Jian ZHANG , Chaochao LI , Kuan LU","doi":"10.1016/S1872-5813(26)60683-4","DOIUrl":null,"url":null,"abstract":"<div><div>The catalytic conversion of C1 molecules (e.g., CO, CO<sub>2</sub>) represents a pivotal technology in the energy and chemical sectors, essential for achieving sustainable C1 chemistry and low-carbon transformation. A profound understanding of the underlying microscopic reaction mechanisms necessitates systematic support from both theoretical and experimental data support. This study constructs a “Computational Dataset for C1 Molecular Catalytic Conversion Based on Iron-Based Catalysts,” focusing on Fe<sub>5</sub>C<sub>2</sub>-based catalysts and systematically integrating multidimensional information on C1 molecular adsorption, dissociation, and formation reactions across different crystal surfaces (001, 111, 510). The dataset includes: the number of polycrystalline surface structures (Fe<sub>5</sub>C<sub>2</sub>(001) with 96 configurations, Fe<sub>5</sub>C<sub>2</sub>(111) with 93, and Fe<sub>5</sub>C<sub>2</sub>(510) with 472); species involved in the full reaction pathways under complex co-adsorption environments (adsorbed states such as COH and H<sub>2</sub>, dissociated states like CO under 2H conditions, and formation states such as CH/CH<sub>3</sub> under 2H and H<sub>2</sub>O conditions); and a standardized hierarchical storage system categorizing reaction types, crystal surfaces, and structural parameters. This dataset not only serves as a benchmark for validating quantum chemical calculation methods but also provides critical data support for catalyst design and reaction pathway optimization in C1 molecular catalytic conversion by uncovering the coupling effects of crystal surfaces and reaction mechanisms.<span><figure><span><img><ol><li><span><span>Download: <span>Download high-res image (224KB)</span></span></span></li><li><span><span>Download: <span>Download full-size image</span></span></span></li></ol></span></figure></span></div></div>","PeriodicalId":15956,"journal":{"name":"燃料化学学报","volume":"54 6","pages":"Article 16"},"PeriodicalIF":0.0000,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"燃料化学学报","FirstCategoryId":"1087","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1872581326606834","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/6/15 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"Energy","Score":null,"Total":0}
引用次数: 0
Abstract
The catalytic conversion of C1 molecules (e.g., CO, CO2) represents a pivotal technology in the energy and chemical sectors, essential for achieving sustainable C1 chemistry and low-carbon transformation. A profound understanding of the underlying microscopic reaction mechanisms necessitates systematic support from both theoretical and experimental data support. This study constructs a “Computational Dataset for C1 Molecular Catalytic Conversion Based on Iron-Based Catalysts,” focusing on Fe5C2-based catalysts and systematically integrating multidimensional information on C1 molecular adsorption, dissociation, and formation reactions across different crystal surfaces (001, 111, 510). The dataset includes: the number of polycrystalline surface structures (Fe5C2(001) with 96 configurations, Fe5C2(111) with 93, and Fe5C2(510) with 472); species involved in the full reaction pathways under complex co-adsorption environments (adsorbed states such as COH and H2, dissociated states like CO under 2H conditions, and formation states such as CH/CH3 under 2H and H2O conditions); and a standardized hierarchical storage system categorizing reaction types, crystal surfaces, and structural parameters. This dataset not only serves as a benchmark for validating quantum chemical calculation methods but also provides critical data support for catalyst design and reaction pathway optimization in C1 molecular catalytic conversion by uncovering the coupling effects of crystal surfaces and reaction mechanisms.
期刊介绍：
Journal of Fuel Chemistry and Technology (Ranliao Huaxue Xuebao) is a Chinese Academy of Sciences(CAS) journal started in 1956, sponsored by the Chinese Chemical Society and the Institute of Coal Chemistry, Chinese Academy of Sciences(CAS). The journal is published bimonthly by Science Press in China and widely distributed in about 20 countries. Journal of Fuel Chemistry and Technology publishes reports of both basic and applied research in the chemistry and chemical engineering of many energy sources, including that involved in the nature, processing and utilization of coal, petroleum, oil shale, natural gas, biomass and synfuels, as well as related subjects of increasing interest such as C1 chemistry, pollutions control and new catalytic materials. Types of publications include original research articles, short communications, research notes and reviews. Both domestic and international contributors are welcome. Manuscripts written in Chinese or English will be accepted. Additional English titles, abstracts and key words should be included in Chinese manuscripts. All manuscripts are subject to critical review by the editorial committee, which is composed of about 10 foreign and 50 Chinese experts in fuel science. Journal of Fuel Chemistry and Technology has been a source of primary research work in fuel chemistry as a Chinese core scientific periodical.
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