Hydration of Atmospheric Molecular Clusters: A New Method for Systematic Configurational Sampling

Abstract

We present a new systematic configurational sampling algorithm for investigating the potential energy surface of hydrated atmospheric molecular clusters. The algorithm is based on creating a Fibonacci sphere around each atom in the cluster and adding water molecules to each point in nine different orientations. For the sampling of water molecules to existing hydrogen bonds, the cluster is displaced along the hydrogen bond, and a water molecule is placed in between in three different orientations. Generated redundant structures are eliminated based on minimizing the root-mean-square distance of different conformers. Initially, the clusters are sampled using the semiempirical PM6 method and subsequently using density functional theory (M06-2X and ωB97X-D) with the 6-31++G(d,p) basis set. Applying the developed algorithm, we study the hydration of sulfuric acid with up to 15 water molecules. We find that the addition of the first four water molecules "saturate" the sulfuric acid molecule and that they are more thermodynamically favorable than the addition of water molecules 5-15. Using the large generated set of conformers, we assess the performance of approximate methods (ωB97X-D, M06-2X, PW91, and PW6B95-D3) in calculating the binding energies and assigning the global minimum conformation compared to high level CCSD(T)-F12a/VDZ-F12 reference calculations. The tested DFT functionals systematically overestimate the binding energies compared to coupled cluster calculations, and we find that this deficiency can be corrected by a simple scaling factor.

Particle formation and surface processes on atmospheric aerosols: A review of applied quantum chemical calculations

“…[ 79–84 ] Recently, a new systematic method of configurational sampling based on the Fibonacci sphere has been applied to atmospheric molecular clusters. [ 85,86 ] Once all the low‐energy isomers are identified by one of these configurational sampling methods, [ 87 ] the main parameter of interest to be computed using quantum chemistry is the equilibrium constant of formation under atmospherically relevant conditions dictated by the temperature, pressure, and RH. This is accomplished by computing finite‐temperature corrections to the gas‐phase vacuum energy of the molecular cluster and involves the computation of the vibrational structure of the cluster, so that the Gibbs free energy of formation can be calculated at the desired temperature.…”

Frontier molecular orbital analysis for determining the equilibrium geometries of atmospheric prenucleation complexes

“…Temelso [75] has provided the structures of global minimum for these molecular systems. Also Kildgaard and coworkers [55] have used his results to test a new method for systematic configurational sampling. We have applied our own method to figure out whether it can lead to the localization of the same global minima and if it can have an impact on the number of computational runs needed to do so.…”

“…As it T A B L E 1 Global minimum (H 2 O) n cluster structures from the literature: comparison n Global minima [72] can be seen in the second column of Table 1, the structures proposed in the literature have been listed. The number of runs carried out to find each one of the global minima [55,75] following the methodology suggested in the present study have been provided in the third column. A total exploration of the PES is practically impossible for both, the statistics or our method.…”

“…The optimized structures are in agreement with the literature data. [13,20,22,55,77] However, some differences can be extracted from the analysis of the results. The HOMO(H 2 O) = −10.90 eV is lower than the HOMO(NH 3 ) = − 9.66 eV while the LUMO's energies can be considered comparable (see Table 3).…”

Computation of Atmospheric Concentrations of Molecular Clusters from <em>ab initio</em> Thermochemistry

“…In some cases, these are followed by higher level wavefunction methods such as MP2, CCSD(T), and the cost efficient DLPNO-CCSD(T) 34,35 . Kildgaard et al 36 developed a systematic method where water molecules are added at points on the Fibonacci spheres 37 around smaller hydrated or unhydrated clusters to generate candidates for larger clusters. Unphysical and redundant candidates are removed based on close contact thresholds and root-mean-square distance between different conformers.…”