燃料化学学报（中英文）2026，Vol.54Issue(6)：226-232,7.DOI:10.1016/S1872-5813(26)60683-4
基于铁基催化剂的C1分子催化转化计算数据集
A computational dataset for C1 molecules catalytic conversion over iron-based catalysts
摘要
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.关键词
Fe5C2催化剂/C1分子/密度泛函理论/反应机理/数据集Key words
Fe5C2/C1 molecules/density functional theory/reaction mechanism/dataset分类
化学化工引用本文复制引用
张建,李超超,路宽..基于铁基催化剂的C1分子催化转化计算数据集[J].燃料化学学报（中英文）,2026,54(6):226-232,7.基金项目
Supported by Youth Talent Development Program of SKLCC(2025BWZ010). （2025BWZ010）
