Quantifying lateral adsorbate interactions by kinetic Monte-Carlo simulations and density-functional theory: NO dissociation on Rh(100)

Literature Information

Publication Date 2004-03-09
DOI 10.1039/B314944G
Impact Factor 3.676
Authors

A. P. van Bavel, C. G. M. Hermse, M. J. P. Hopstaken, A. P. J. Jansen, J. J. Lukkien, J. W. Niemantsverdriet


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Abstract

The dissociation of NO on Rh(100) surfaces has been modelled by kinetic Monte-Carlo (MC) simulations including nearest neighbour (NN) and next-nearest neighbour (NNN) interactions, and zero-coverage kinetic parameters obtained from experiments. Two approaches were performed to derive the lateral interactions. First, the interactions were quantified by fitting the MC model to the experimental data. All interactions between NO, N and O were found to be repulsive. Nearest-neighbour interactions involving atoms are typically on the order of 20–30 kJ mol−1; between molecules they are below 10 kJ mol−1. All next-nearest neighbour interactions were smaller than 10 kJ mol−1. The simulations show that at higher initial NO coverage, the nitrogen and oxygen atoms were created by dissociation form c(2 × 2) islands, thereby compressing the NO areas and impeding their dissociation. Second, interactions estimated using DFT calculations were significantly higher than the ones estimated from fitting the experiments. Monte-Carlo simulations based on interactions obtained from DFT provide a description that is only qualitatively useful.

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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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