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Related Experiment Video

Updated: Jan 18, 2026

Computation of Atmospheric Concentrations of Molecular Clusters from ab initio Thermochemistry

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Quantifying Molecular Properties of Hexagonal Water Clusters.

Giuseppe Lanza¹

¹Dipartimento di Scienze del Farmaco e della Salute, Università di Catania, Viale A. Doria 6, 95125, Catania, Italy.

|June 1, 2025

Summary

This summary is machine-generated.

This study used large hexagonal water clusters to model ice Ih. Computational results closely matched experimental data, validating this approach for water science research.

Keywords:

DFT calculations hexagonal clusters ice stability vibrational spectra

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Area of Science:

Computational chemistry
Condensed matter physics
Water science

Background:

Investigating the molecular properties of hexagonal ice (ice Ih) is crucial for understanding water's complex behavior.
Experimental studies of ice Ih face challenges due to its intricate structure and phase transitions.

Purpose of the Study:

To model hexagonal ice (ice Ih) using large hexagonal water clusters.
To validate computational methods for studying water clusters and their properties.
To bridge the gap between theoretical calculations and experimental observations in water science.

Main Methods:

Density functional theory (DFT) with the M06-2X functional and the polarizable continuum model (PCM) were employed.
Gaussian basis sets were utilized for calculations on (H2O)n clusters (n=96-332).
Cluster structures were designed to minimize surface dangling hydrogen bonds and maintain hexagonal crystallinity.

Main Results:

Large water cluster structures exhibited high stability.
Computed electronic energy and entropy showed asymptotic behavior, closely aligning with experimental thermodynamics.
Excellent agreement was found between computed and experimental data for structural (neutron and X-ray diffraction) and vibrational (IR, Raman, INS, hyper-Raman) properties.

Conclusions:

The use of large-size water clusters is a promising computational methodology for studying ice Ih.
Standard quantum chemical methods, when applied to large clusters, can accurately predict properties of experimentally challenging systems.
This approach offers a reliable pathway for advancing research in water science.