Regulating the oxidation state of Pd to enhance the selective hydrogenation for 5-hydroxymethylfurfural

被引:0
|
作者
Li, Xin [1 ]
Ma, Yue [1 ]
Wang, Xuning [1 ]
Wu, Jianguo [1 ]
Cao, Dong [1 ,2 ]
Cheng, Daojian [1 ,2 ]
机构
[1] Beijing Univ Chem Technol, State Key Lab Organ Inorgan Composites, Beijing 100029, Peoples R China
[2] Beijing Univ Chem Technol, Coll Chem Engn, Beijing 100029, Peoples R China
关键词
Selective hydrogenation; 5-hydroxymethylfurfural; 2,5-dihydroxymethylfuran; Oxidation state; CARBON NITRIDE; CATALYSTS; ACID; 2,5-DIMETHYLFURAN; HYDROGENOLYSIS; CONVERSION;
D O I
10.1016/j.cjche.2024.05.006
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
The highly selective hydrogenation of 5-hydroxymethylfurfural to 2,5-dihydroxymethylfuran is an important reaction in the field of biomass hydrogenation, because it is a bridge between biomass resources and chemical industry. Here, we precisely constructed carbon nitride supported Pd-based catalysts by a simple impregnation-reduction method. By changing the reduction temperature, catalysts with different oxidation state could be precisely constructed. Moreover, the important correlation between the ratio of Pd0/Pd2+ 0 /Pd 2+ and catalytic activity is revealed during the selective hydrogenation of HMF. The Pd/g-C3N4-300 3 N 4-300 catalyst with a Pd0/Pd2+ 0 /Pd 2+ ratio of 3/2 showed the highest catalytic activity, which could get 96.9% 5-hydroxymethylfurfural conversion and 90.3% 2,5-dihydroxymethylfuran selectivity. Further density functional theory calculation revealed that the synergistic effect between Pd0 0 and Pd2+ 2+ in Pd/g-C3N4-300 3 N 4-300 system could boost the adsorption of the substrate and the dissociation of hydrogen. In this work, we highlight the important correlation between metal oxidation state and catalytic activity, which provides valuable insights for the rational design of precious metal catalysts for hydrogenation reactions. (c) 2024 The Chemical Industry and Engineering Society of China, and Chemical Industry Press Co., Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
引用
收藏
页码:60 / 68
页数:9
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