Boosting hydrocarbon conversion via Cu-doping induced oxygen vacancies on CeO2 in CO2 electroreduction

被引:0
|
作者
Xue, Lei [1 ,2 ]
Shi, Tong [1 ,3 ]
Han, Chenhui [1 ]
Zhang, Heng [1 ]
Liu, Fenrong [1 ]
Li, Haorun [1 ]
Wang, Yan [4 ]
Gu, Xiaojun [1 ]
Zeng, Shanghong [1 ]
机构
[1] Inner Mongolia Univ, Sch Chem & Chem Engn, Inner Mongolia Key Lab Chem & Phys Rare Earth Mat, Hohhot 010021, Inner Mongolia, Peoples R China
[2] Chinese Acad Sci, Inst Coal Chem, State Key Lab Coal Convers, Taiyuan 030001, Shanxi, Peoples R China
[3] Zhejiang Univ, Inst Catalysis, Dept Chem, Hangzhou 310058, Zhejiang, Peoples R China
[4] Baotou Res Inst Rare Earths, Natl Key Lab Baiyunobo Rare Earth Resource Res & C, Baotou 014030, Inner Mongolia, Peoples R China
来源
关键词
Cu/CeO2_x; Oxygen vacancy; Hydrocarbon production; Reaction mechanism; REDUCTION; CATALYSTS; CERIA; SPECTROSCOPY; SELECTIVITY; INTERFACES; OXIDATION; SITES;
D O I
10.1016/j.jechem.2024.08.025
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
Conversion of CO2 back to hydrocarbons is the most direct way of closing the "carbon cycle", and its significance is further enlarged if this process is driven by renewable energies such as electricity. However, precisely controlling the product selectivity towards hydrocarbons against the competitive hydrogen evolution remains challenging, especially for Cu-based catalysts. Herein, we report a novel defect engineering strategy, by which Cu-doping-induced oxygen vacancies on CeO2 nanorods were effectively created, with adjustable vacancy/Cu ratio. The resulting optimum catalyst shows up to 79% catalytic current density to hydrocarbons (excluding CO), with 49% faradaic efficiency to CH4. Experiments and density functional theory unveil that the ratio between oxygen vacancy and Cu affects significantly the formation of *CHO and activation of H2O, which leads to the following deep hydrogenation to hydrocarbons. These findings may spur new insights for designing and developing more controllable chemical process relevant to CO2 utilization. (c) 2024 Science Press and Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by ELSEVIER B.V. and Science Press. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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页码:66 / 76
页数:11
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