2. COMPUTATIONAL METHOD AND DETAILS
In this study, atomic structures of all nanosized gold clusters are taken
from previously resolved global minimum structures on the basis of
combined photoelectron spectroscopy (PES) measurements and
density functional theory (DFT) global optimization.73−77 The
geometric structures of intermediates and transition states are optimized
using either restricted or unrestricted DFT methods with the general
gradient approximation (GGA) in the form of a Perdew−Burke−
Ernzerhof (PBE) functional78 or with the hybrid meta-GGA functional
(TPSSh)79 implemented in Dmol3 4.480 and Gaussian 09,81
respectively. For the planar Au7−Au10, cage Au16, and pyramidal Au19
clusters, the TPSSh functional combined with the LAN2DZ basis set
(for Au) and 6-31G* basis set for C and O are used for all energy
computations. The energy reported here includes the zero-energy
correction. For larger gold clusters, the PBE functional with a semicore
pseudopotential (DSPP) is used, together with the double numerical
(DND) basis set for the geometric optimization and transition-state
search
2. COMPUTATIONAL METHOD AND DETAILS
In this study, atomic structures of all nanosized gold clusters are taken
from previously resolved global minimum structures on the basis of
combined photoelectron spectroscopy (PES) measurements and
density functional theory (DFT) global optimization.73−77 The
geometric structures of intermediates and transition states are optimized
using either restricted or unrestricted DFT methods with the general
gradient approximation (GGA) in the form of a Perdew−Burke−
Ernzerhof (PBE) functional78 or with the hybrid meta-GGA functional
(TPSSh)79 implemented in Dmol3 4.480 and Gaussian 09,81
respectively. For the planar Au7−Au10, cage Au16, and pyramidal Au19
clusters, the TPSSh functional combined with the LAN2DZ basis set
(for Au) and 6-31G* basis set for C and O are used for all energy
computations. The energy reported here includes the zero-energy
correction. For larger gold clusters, the PBE functional with a semicore
pseudopotential (DSPP) is used, together with the double numerical
(DND) basis set for the geometric optimization and transition-state
search
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