Toward in silico modeling of palladium–hydrogen–carbon nanohorn nanocomposites

Literature Information

Publication Date 2014-05-02
DOI 10.1039/C4CP01345J
Impact Factor 3.676
Authors

Piotr Kowalczyk, Artur P. Terzyk, Piotr A. Gauden, Sylwester Furmaniak, Katsumi Kaneko


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Abstract

We present the first in silico modeling of the Pd–H-single-walled carbon nanohorn nanocomposites. Temperature-quench Monte Carlo simulations are used to generate the most stable morphologies of Pd81 clusters (cluster sizes of ∼2 nm) deposited inside the morphologically defective single-walled carbon nanohorns (S. Furmaniak, A. P. Terzyk, K. Kaneko, P. A. Gauden, P. Kowalczyk, T. Itoh, Phys. Chem. Chem. Phys., 2013, 15, 1232–1240). The optimized Pd81-single-walled carbon nanohorn nanocomposites are next used in calculating the H binding energy distributions at 300 K. The most stable positions of H impurity in confined Pd81 clusters are identified, showing subsurface character of H absorption from the dilute H2 gas at 300 K. The H binding energy distribution on the Pd(100) open surface at 300 K is computed and compared with those corresponding to Pd81–single-walled carbon nanohorn nanocomposites. Finally, the impact of the Pd–H short-range order on the H binding energy is explored and critically discussed.

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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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