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

Area of Science:

• Atmospheric Chemistry
• Computational Chemistry
• Molecular Modeling

Background:

• Investigating potential energy surfaces of hydrated atmospheric clusters is crucial for understanding atmospheric processes.
• Accurate modeling of molecular clusters requires efficient configurational sampling algorithms.

Purpose of the Study:

• To develop a novel systematic configurational sampling algorithm for hydrated atmospheric molecular clusters.
• To study the hydration of sulfuric acid and assess the performance of various computational methods.

Main Methods:

• A new algorithm employing Fibonacci spheres and specific water molecule orientations for cluster sampling.
• Initial sampling using the PM6 method, followed by DFT calculations (M06-2X, ωB97X-D) with the 6-31++G(d,p) basis set.
• Elimination of redundant structures using root-mean-square distance minimization.

Main Results:

• The first four water molecules significantly "saturate" sulfuric acid, showing greater thermodynamic favorability than subsequent water molecules.
• Density functional theory (DFT) functionals systematically overestimate binding energies compared to high-level coupled cluster calculations.
• A simple scaling factor can correct the overestimation of binding energies by tested DFT functionals.

Conclusions:

• The developed algorithm provides an efficient approach for exploring potential energy surfaces of hydrated clusters.
• Sulfuric acid hydration exhibits a saturation effect with the initial water molecules.
• DFT binding energy calculations require correction for accurate comparison with high-level reference data.