Approaching complexity of alkyl hydrogenation on Pd via density-functional modelling

Literature Information

Publication Date 2017-07-18
DOI 10.1039/C7CP03516K
Impact Factor 3.676
Authors

Sergey M. Kozlov, Georgi N. Vayssilov


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Abstract

Pd is widely used to catalyse hydrogenation and dehydrogenation reactions. One of them is the hydrogenation of ethylene, which includes the transformation of ethyl species to ethane. Herein, by means of density-functional calculations we address several still insufficiently understood factors affecting the latter process. In particular, we shed light on the following aspects of hydrogenation of alkyls on Pd: (i) the mechanistic details of how subsurface H accelerates the reaction on a (111) surface; (ii) the role of nanoparticle edges; and (iii) the influence of a common spectator ethylidyne, C–CH3. These factors are identified as significant for the height of the ethyl hydrogenation barrier on Pd. Moreover, we show that butyl hydrogenation on Pd is also governed by very similar interactions, which suggests a broader applicability of our conclusions. This study highlights the complexity of alkyl hydrogenation and analyses the factors that need to be taken into account for a more realistic description of the hydrogenation processes on metal surfaces.

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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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