3D‐foam‐structured nitrogen‐doped graphene‐Ni catalyst for highly efficient nitrobenzene reduction. Issue 4 (6th November 2017)

• Record Type: Journal Article
• Authors: Wang, Zhiyong; Pu, Yuan; Wang, Dan; Shi, Jie; Wang, Jie‐Xin; Chen, Jian‐Feng
• Is Part Of: AIChE journal. Volume 64:Issue 4(2018)
• Page Start: 1330
• Page End: 1338
• Publication Date: 2017-11-06
• Subjects: nitrogen‐doped graphene -- 3D‐foam‐structured catalysts -- nitrobenzene reduction -- Langmuir‐Hinshelwood model -- density functional theory calculation; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; 660.28
• DOI: 10.1002/aic.16016
• Languages: English
• ISSNs: 0001-1541

Abstract

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