• 文献标题:   3D-foam-structured nitrogen-doped graphene-Ni catalyst for highly efficient nitrobenzene reduction
  • 文献类型:   Article
  • 作  者:   WANG ZY, PU Y, WANG D, SHI J, WANG JX, CHEN JF
  • 作者关键词:   nitrogendoped graphene, 3dfoamstructured catalyst, nitrobenzene reduction, langmuirhinshelwood model, density functional theory calculation
  • 出版物名称:   AICHE JOURNAL
  • ISSN:   0001-1541 EI 1547-5905
  • 通讯作者地址:   Beijing Univ Chem Technol
  • 被引频次:   9
  • DOI:   10.1002/aic.16016
  • 出版年:   2018

▎ 摘  要

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. (c) 2017 American Institute of Chemical Engineers AIChE J, 64: 1330-1338, 2018