Direct vs. indirect pathway for nitrobenzene reduction reaction on a Ni catalyst surface: a density functional study

Literature Information

Publication Date 2014-10-21
DOI 10.1039/C4CP04355C
Impact Factor 3.676
Authors

Arup Mahata, Rohit K. Rai, Indrani Choudhuri, Sanjay K. Singh, Biswarup Pathak


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Abstract

Density functional theory (DFT) calculations are performed to understand and address the previous experimental results that showed the reduction of nitrobenzene to aniline prefers direct over indirect reaction pathways irrespective of the catalyst surface. Nitrobenzene to aniline conversion occurs via the hydroxyl amine intermediate (direct pathway) or via the azoxybenzene intermediate (indirect pathway). Through our computational study we calculated the spin polarized and dispersion corrected reaction energies and activation barriers corresponding to various reaction pathways for the reduction of nitrobenzene to aniline over a Ni catalyst surface. The adsorption behaviour of the substrate, nitrobenzene, on the catalyst surface was also considered and the energetically most preferable structural orientation was elucidated. Our study indicates that the parallel adsorption behaviour of the molecules over a catalyst surface is preferable over vertical adsorption behaviour. Based on the reaction energies and activation barrier of the various elementary steps involved in direct or indirect reaction pathways, we find that the direct reduction pathway of nitrobenzene over the Ni(111) catalyst surface is more favourable than the indirect reaction pathway.

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Source Journal

Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

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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