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Comparative theoretical study of small Rh n nanoparticles (2 ≤ n ≤ 8) using DFT methods
Author(s) -
Bertin V.,
LopezRendón R.,
del Angel G.,
Poulain E.,
Avilés R.,
UcRosas V.
Publication year - 2010
Publication title -
international journal of quantum chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.484
H-Index - 105
eISSN - 1097-461X
pISSN - 0020-7608
DOI - 10.1002/qua.22220
Subject(s) - energy minimization , basis set , nanoparticle , gaussian , adsorption , bond length , chemistry , spin (aerodynamics) , ground state , molecule , geometry , molecular physics , computational chemistry , atomic physics , physics , materials science , nanotechnology , density functional theory , thermodynamics , quantum mechanics , mathematics
This work is aimed at identifying some key characteristics (energy, geometry, and spin) concerning Rh n particles (2 = n ≤ 8) to perform further studies on adsorption and coadsorption sites of pollutants (CO and NO). The DFT methods of the Gaussian 03 program with the LANL2DZ basis set and the LANL2 potential are used. With the purpose to obtain a better nanoparticles definition, five different functionals were tested: B3LYP, O3LYP, BPW91, BP86, and HCTH; and the corresponding results are used to determine which of them best describes distances, spin, and gives acceptable highest vibration frequency and binding energy values, by comparing these results with values measured or calculated by many other authors. For the structure optimization process of the particles, the initial geometric shape was taken mainly from the literature, using the Rh–Rh distance: 2.67 Å, known for the bulk; and doing a complete optimization. We also considered flat nanoparticles structures, which most of them display three‐dimensional structures after the optimization process. The few flat shapes are mainly higher in energy than those of three‐dimensional structure. For some Rh n particles for different n values, the spin of the ground state present degeneration. In some cases, the optimization process changes the initial geometry, but in most cases, there are only minor changes in bonds and geometry. © 2009 Wiley Periodicals, Inc. Int J Quantum Chem, 2010