Rational design of nitrogen-doped carbon for palladium catalysts in hydrogenation of hydrazo compounds

被引：0
作者：
Xu, Junzhe [1 ]
Liu, Shuang [1 ]
Li, Lin [2 ]
Qin, Xian [1 ]
Qu, Ruixin [1 ]
Wang, Jinguo [1 ]
Liu, Di [3 ]
Wei, Gaixia [4 ]
机构：
[1] Shanghai Univ Engn Sci, Sch Chem & Chem Engn, Shanghai 201620, Peoples R China
[2] Chinese Acad Sci, Dalian Inst Chem Phys, CAS Key Lab Sci & Technol Appl Catalysis, Dalian 116023, Peoples R China
[3] Samsung China Semicond CO LTD, Xian 710075, Peoples R China
[4] Qingyang Chem Ind Corp, Liaoyang 111001, Peoples R China
来源：
CHINESE JOURNAL OF CHEMICAL ENGINEERING | 2025年 / 77卷
基金：
上海市自然科学基金;
关键词：
Pd nanocatalyst; Nitrogen-doped carbon; Hydrogenation; Deprotection of CBz; Bimethylation of amino; REDUCTION; NITRIDE; DEPROTECTION; EVOLUTION; GRAPHENE;
D O I：
10.1016/j.cjche.2024.09.023
中图分类号：
TQ [化学工业];
学科分类号：
0817 ;
摘要：
We synthesized CN11, a carbon nitride material rich in sp3 hybrid graphitic nitrogen (sp3-N), employing a facile oxalic acid-assisted melamine molecular assembly strategy. CN11 promoted the formation of Pd nanoparticles (NPs) predominantly exposing {2 0 0} facets, termed Pd/CN11-2. This facet-specific configuration significantly boosted hydrogen adsorption, leading to notable improvements in catalytic activity. Compared to Pd/XC-72-2 and Pd/g-C3N4-2, Pd/CN11-2 exhibited a remarkable two-fold and nineteen-fold increase in catalytic yield for hydrazo compound hydrogenation, respectively. Pd/CN11-2 also demonstrated robust performance across a range of reaction conditions, maintaining excellent yield. This study emphasizes the critical role of tailored support structures in controlling Pd NPs facets, thereby enhancing hydrogenation efficiency. It provides valuable insights for advancing the industrial application of Pd-based catalysts, underscoring the importance of strategic support modulation for optimizing catalytic performance. (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.
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收藏
页码：156 / 166
页数：11
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