PtN3-Embedded graphene as an efficient catalyst for electrochemical reduction of nitrobenzene to aniline: a theoretical study

Literature Information

Publication Date 2020-07-15
DOI 10.1039/D0CP02389B
Impact Factor 3.676
Authors

Shuang Wang, Yuejie Liu, Jingxiang Zhao


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Abstract

The electrochemical reduction of nitrobenzene (NBER) holds great promise for not only removing toxic pollutants, but also producing valuable aniline, in which the development of catalysts with high-efficiency still remains a huge challenge. In this work, by means of density functional theory (DFT) computations, we proposed several single transition metal (TM) atoms embedded into the single vacancy of graphene with nitrogen-doping (TMN3/G, TM = Ni, Cu, Pd, and Pt) as the catalysts for NBER. Our results revealed that, among these candidates, PtN3/G is the most active catalyst for the NBER due to its smallest limiting potential (−0.21 V), in which the hydrogenation of Ph-NO2* to Ph-NOOH* is identified as the potential-determining step. Compared with other catalysts, the strongest binding strength of Ph-NOOH* with PtN3/G is responsible for its superior catalytic activity towards NBER, which can be deeply understood on the basis of the corresponding electronic structure analysis. Thus, PtN3/G is a quite promising single-atom-catalyst with high efficiency for nitrobenzene reduction, which provides a rational paradigm for converting harmful nitrobenzene to valuable aniline under ambient conditions.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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