Density functional theory investigation of H adsorption and H2 recombination on the basal plane and in the bulk of graphite: Connection between slab and cluster model

2002 ◽  
Vol 116 (18) ◽  
pp. 8124-8131 ◽  
Author(s):  
Y. Ferro ◽  
F. Marinelli ◽  
A. Allouche
Keyword(s):  
Density Functional Theory ◽  
Basal Plane ◽  
Cluster Model ◽  
Density Functional ◽  
Functional Theory

Interaction of Nitric Oxide and Nitric Oxide Dimer with Silver Clusters

2005 ◽  
Vol 1 (4) ◽  
pp. 253-258 ◽  
Author(s):  
V.E. Matulis ◽  
O.A. Ivashkevich ◽  
V.S. Gurin
Keyword(s):  
Nitric Oxide ◽  
Density Functional Theory ◽  
Cluster Model ◽  
Density Functional ◽  
Bond Formation ◽  
Silver Cluster ◽  
Silver Clusters ◽  
Functional Theory ◽  
Nitric Oxide Dimer

Study of interaction of NO and (NO)2 molecules with silver clusters has been carried out using the hybrid method S2LYP based on density functional theory (DFT). The role of cluster charge and site of adsorption on N–O stretch frequency, adsorption energy and geometry has been investigated. Four cluster models of different size have been used for simulation of (NO)2 adsorption on Ag{111} surface. The pronounced effect of N–N bond shortening in comparison with gaseous (NO)2 has been found due to adsorption of (NO)2 on silver cluster. This phenomenon is important as possible pathway of N–N bond formation in catalytic fragmentation of NO molecule. The calculations showed that the silver octamer is the best candidate for simulation of formation and fragmentation of (NO)2 on Ag{111} surface within the cluster model.

A computational study on the electrified Pt(111) surface by the cluster model

2019 ◽  
Vol 21 (11) ◽  
pp. 6112-6125 ◽  
Author(s):  
Jian Yang
Keyword(s):  
Density Functional Theory ◽  
Cluster Model ◽  
Density Functional ◽  
Computational Study ◽  
No Adsorption ◽  
Functional Theory

A hemispherical cuboctahedral Pt37 cluster is applied to study NO adsorption and reduction on the Pt(111) surface by using density functional theory.

scholarly journals Elucidating the germanium distribution in ITQ-13 zeolites by density functional theory

2021 ◽  
Author(s):  
Michael Fischer ◽  
Carlos Bornes ◽  
Luís Mafra ◽  
João Rocha
Keyword(s):  
Density Functional Theory ◽  
Nmr Spectroscopy ◽  
Dft Calculations ◽  
Basal Plane ◽  
Density Functional ◽  
Dynamic Behaviour ◽  
Local Environment ◽  
19F Nmr ◽  
Functional Theory ◽  
Clear Identification

ITQ-13 is a medium-pore zeolite that can be prepared in all-silica form and as silicogermanate with Si/Ge ratios as low as 3. Usually synthesised in the presence of fluoride, ITQ-13 is among the very few systems containing fluoride anions in two distinct cage types, cube-like d4r units and [4·5^6] cages. Here, dispersion-corrected density functional theory (DFT) calculations are used to investigate the energetically most favourable Ge distributions for Si/Ge ratios between 55 and 6. The calculations show Ge atoms are incorporated at both the corners of d4r cages and at the basal plane of the [4·5^6] cages, in accordance with 19F-NMR spectroscopy. Two Ge atoms at adjacent corners of [4·5^6] cages are stable at the highest Ge content. Such a local environment has not yet been considered in the experimental literature. A calculation of the corresponding 19F-NMR resonance points to overlap with other resonances, which might preclude its clear identification. Additional calculations investigate the variation of the dynamic behaviour of the fluoride anions as a function of the local environment as well as the selective defluorination of the [4·5^6] cages.

ADSORPTION AND DECOMPOSITION OF ClCN ON Si (100)-(2×1) SURFACE: A DENSITY FUNCTIONAL THEORY STUDY

2004 ◽  
Vol 03 (03) ◽  
pp. 471-479 ◽  
Author(s):  
JIAN MING HU ◽  
YI LI ◽  
YONG FAN ZHANG ◽  
JUN QIAN LI ◽  
YONG CHEN
Keyword(s):  
Density Functional Theory ◽  
Excellent Agreement ◽  
Cluster Model ◽  
Density Functional ◽  
Density Functional Theory Study ◽  
Functional Theory ◽  
Model Method

The adsorption and decomposition of ClCN on Si (100)-(2×1) surface is studied by using density functional theory and the cluster model method. The Si 9 H 12 dimer cluster is used to simulate the surface. The present calculations show that ClCN may be adsorbed molecularly without a barrier onto the surface with both linear (L1) and parallel (S1) modes. L1 can isomerize to S1 with a small barrier of 5.6 kcal/mol. Both ClCN and ClNC end-on adsorbates were found to dissociate readily to produce Cl and CN species, which was in excellent agreement with the experiment.

DFT study on the interaction between atomic aluminum and graphene

2014 ◽  
Vol 13 (07) ◽  
pp. 1450055 ◽  
Author(s):  
Nicolás F. Domancich ◽  
Ricardo M. Ferullo ◽  
Norberto J. Castellani
Keyword(s):  
Density Functional Theory ◽  
Cluster Model ◽  
Density Functional ◽  
The Other ◽  
Theoretical Treatment ◽  
Molecular Orbital Calculations ◽  
Functional Theory ◽  
Graphene Surface ◽  
Defective Graphene ◽  
Radical Attack

In the present work, molecular orbital calculations using cluster models were performed within density functional theory (DFT) in order to study the adsorption of an Al atom on regular and defective graphene. Depending on the theoretical treatment of electronic exchange and correlations effects, different bonding results for the adsorption on the perfect surface are obtained. On the other hand, they are very similar for Al adsorbed on a carbon monovacancy. On regular graphene, the adsorption is exothermic when the Perdew, Burke and Ernzerhof (PBE) functional is used and endothermic with the Becke, 3-parameter, Lee–Yang–Parr (B3LYP) functional. Regarding the defective graphene surface, it was shown that the carbon atoms of concave angles in the vacancy are the most reactive to a radical attack. The adsorption of an Al atom on the vacancy restores the trigonal symmetry lost after the extraction of the C atom from regular graphene. Complementary calculations performed at PBE level on both regular and defective surfaces imposing periodic conditions qualitatively support the results obtained with the cluster model.

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