Carbon clusters on the Ni(111) surface: a density functional theory study

Literature Information

Publication Date 2013-11-26
DOI 10.1039/C3CP54376E
Impact Factor 3.676
Authors

Jingde Li, Eric Croiset, Luis Ricardez-Sandoval


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Abstract

To understand the nucleation of carbon atoms to form carbon clusters on transition metal substrates during chemical vapor deposition (CVD) synthesis, the structure, energetics, and mobility of carbon intermediates up to 6 atoms on the Ni(111) surface were investigated using Density Functional Theory (DFT). Carbon clusters were found to be more thermodynamically stable than adsorbed atomic carbon, with linear carbon structures being more stable than branched and ring structures. Carbon chains were also found to have higher mobility than branched configurations. The interaction energy between carbon clusters and the Ni surface shows that branched carbon clusters have stronger interaction with the Ni substrate when compared with the carbon chains, supporting that carbon chains generally have higher mobility than branched clusters. The transition states and energy barriers for the formation of different carbon clusters were also studied. The results show that the formation of the branched configurations is kinetically favored as it presents lower energy barriers than those obtained for carbon chains.

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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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