Water clusters to nanodrops: a tight-binding density functional study.

Area of Science:

• Computational chemistry
• Physical chemistry
• Materials science

Background:

• Accurate prediction of water cluster structures and energies is crucial for understanding various chemical and physical processes.
• Traditional methods like density functional theory (DFT) and wave function theory (WFT) can be computationally expensive for large systems.

Purpose of the Study:

• To evaluate the accuracy of tight-binding density functional theory (DFTB) for predicting the structures and energies of water clusters up to 100 water molecules.
• To develop a correction method to improve the accuracy of DFTB energies.

Main Methods:

• Utilized tight-binding density functional theory (DFTB) for structural optimizations and energy calculations of water clusters.
• Developed and applied a per-hydrogen-bond energy correction to systematically improve DFTB energies.
• Compared DFTB results with high-level density functional theory (DFT) and wave function theory (WFT) calculations.

Main Results:

• DFTB, with the proposed hydrogen bond correction, accurately predicts water cluster structures and energies.
• The corrected DFTB method achieves a root-mean-square difference of less than 1 kcal mol(-1) compared to highly accurate WFT values.
• DFTB optimizations are orders of magnitude faster than DFT or canonical MP2 calculations.

Conclusions:

• DFTB with a simple hydrogen bond correction is a highly accurate and computationally efficient method for studying large water clusters.
• This approach offers a practical solution for predicting the properties of extended water systems, bridging the gap between accuracy and computational cost.