Study of Cl(-)(H2O)n (n = 1-4) using basin-hopping method coupled with density functional theory

Area of Science:

• Computational Chemistry
• Physical Chemistry
• Quantum Chemistry

Background:

• Investigating the structure and properties of anionic water clusters is crucial for understanding solvation phenomena.
• Accurate theoretical methods are needed to model the complex interactions within these systems.

Purpose of the Study:

• To accurately predict the global and local minima of chloride-water clusters (Cl(-)(H2O)n, n=1-4).
• To evaluate and compare the performance of various density functionals and DF-LMP2 for optimizing larger clusters (n>4).

Main Methods:

• Basin-hopping (BH) algorithm coupled with density functional theory (DFT) for initial structure prediction.
• High-level ab initio calculations for obtaining detailed structural, energetic, thermodynamic, and vibrational properties.
• Comparison of different density functionals and DF-LMP2 against MP2 optimized results.

Main Results:

• The BH-DFT combination accurately predicted the structures and properties of Cl(-)(H2O)n (n=1-4) clusters.
• DF-LMP2 demonstrated outstanding performance in describing relative binding energies and geometrical parameters for these clusters.
• The study identified DF-LMP2 as a promising method for optimizing larger anionic water clusters.

Conclusions:

• The BH-DFT approach is a reliable tool for studying small anionic water clusters.
• DF-LMP2 is recommended for future investigations of larger Cl(-)(H2O)n clusters due to its accuracy and efficiency.