3D‐foam‐structured nitrogen‐doped graphene‐Ni catalyst for highly efficient nitrobenzene reduction |
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| Authors: | Zhiyong Wang Yuan Pu Dan Wang Jie Shi Jie‐Xin Wang Jian‐Feng Chen |
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| Affiliation: | 1. State Key Laboratory of Organic‐Inorganic Composites, Beijing University of Chemical Technology, Beijing 100029, China;2. Research Center of the Ministry of Education for High Gravity Engineering and Technology, Beijing University of Chemical Technology, Beijing 100029, China;3. Beijing Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China |
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| Abstract: | We report the preparation of a porous 3D‐foam‐structured nitrogen‐doped graphene‐Ni (NG/NF) catalyst and the evaluation of its performance in the reduction of nitrobenzene (NB) through detailed studies of the kinetics. The NG/NF catalyst showed a significantly higher reaction rate than pure Ni foam (NF). Moreover, the separation of the 3D‐foam‐structured catalyst from the products was more convenient than that of NG powdered catalysts. The obtained kinetics data fit well to the Langmuir‐Hinshelwood model, with an error ratio below 10%. Density functional theory (DFT) calculations indicated that the adsorption of sodium borohydride (NaBH4) on the NG/NF surface was stronger than that of NB, which strongly agreed with the kinetic parameters determined from the Langmuir‐Hinshelwood model. The excellent catalytic efficiency of the 3D‐foam‐structured catalyst combined with the knowledge of the kinetics data make this catalyst promising for application in larger scale nitrobenzene reduction. © 2017 American Institute of Chemical Engineers AIChE J, 64: 1330–1338, 2018 |
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| Keywords: | nitrogen‐doped graphene 3D‐foam‐structured catalysts nitrobenzene reduction Langmuir‐Hinshelwood model density functional theory calculation |
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