In light of the recent surge in computational
studies
of gold thiolate
clusters, we present a comparison of popular density functionals (DFAs)
and three-part corrected methods (3c-methods) on their performance
by taking a data set named as AuSR18 consisting of 18
isomers of Au
n
(SCH3)
m
(m ≤ n =
1–3). We have compared the efficiency and accuracy of the DFAs
and 3c-methods in geometry optimization with RI-SCS-MP2 as the reference
method. Similarly, the performance for accurate and efficient energy
evaluation was compared with DLPNO-CCSD(T) as the reference method.
The lowest energy structure among the isomers of the largest stoichiometry
from our data set, AuSR18, i.e., Au3(SCH3)3, is considered to evaluate the computational
time for SCF and gradient evaluations. Alongside this, the numbers
of optimization steps to locate the most stable minima of Au3(SCH3)3 are compared to assess the efficiency
of the methods. A comparison of relevant bond lengths with the reference
geometries was made to estimate the accuracy in geometry optimization.
Some methods, such as LC-BLYP, ωB97M-D3BJ, M06-2X, and PBEh-3c,
could not locate many of the minima found by most of the other methods;
thus, the versatility in locating various minima is also an important
criterion in choosing a method for the given project. To determine
the accuracy of the methods, we compared the relative energies of
the isomers in each stoichiometry and the interaction energy of the
gold core with the ligands. The dependence of basis set size and relativistic
effects on energies are also compared. The following are some of the
highlights. TPSS has shown accuracy, while mPWPW shows comparable
speed and accuracy. For the relative energies of the clusters, the
hybrid range-separated DFAs are the best option. CAM-B3LYP excels,
whereas B3LYP performs poorly. Overall, LC-BLYP is a balanced performer
considering both the geometry and relative stability of the structures,
but it lacks diversity. The 3c-methods, although fast, are less impressive
in relative stability.