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, 2017

中文翻译：

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3D泡沫结构的氮掺杂石墨烯-Ni催化剂，可高效还原硝基苯

我们报告了多孔3D泡沫结构的氮掺杂石墨烯-镍（NG / NF）催化剂的制备，并通过动力学的详细研究评估了其在还原硝基苯（NB）方面的性能。NG / NF催化剂显示出比纯镍泡沫（NF）更高的反应速率。而且，从产物中分离3D泡沫结构的催化剂比NG粉末催化剂更方便。所获得的动力学数据非常适合Langmuir-Hinshelwood模型，误差比低于10％。密度泛函理论（DFT）计算表明，硼氢化钠（NaBH ₄）在NG / NF表面上比NB上的强，这与从Langmuir-Hinshelwood模型确定的动力学参数非常吻合。3D泡沫结构催化剂的出色催化效率，加上动力学数据的知识，使该催化剂有望用于大规模的硝基苯还原。©2017美国化学工程师学会AIChE J，2017