Ab initio thermodynamics of liquid and solid water

Area of Science:

• Computational physics and chemistry
• Materials science
• Thermodynamics

Background:

• Accurate prediction of thermodynamic properties for water and its solid phases (ice) is crucial for understanding various natural phenomena.
• Previous computational methods often struggled to rigorously incorporate quantum mechanical effects and complex molecular behaviors like proton disorder.

Purpose of the Study:

• To predict the thermodynamic properties of liquid water, hexagonal ice (Ih), and cubic ice (Ic) with high accuracy.
• To rigorously account for quantum nuclear motion, anharmonic fluctuations, and proton disorder in ab initio calculations.

Main Methods:

• Density functional theory (DFT) at the hybrid-functional level.
• Advanced free-energy methods combined with state-of-the-art machine-learning techniques.
• Ab initio calculations incorporating quantum nuclear effects and proton disorder.

Main Results:

• Achieved excellent agreement between calculated structural properties and experimental data for water and ice.
• Provided reliable estimates for the melting points of light and heavy water.
• Demonstrated that nuclear quantum effects are critical for the enhanced stability of ice Ih compared to ice Ic.

Conclusions:

• The developed computational approach accurately predicts thermodynamic properties of water and ice phases.
• Nuclear quantum effects play a vital role in differentiating the stability of various ice polymorphs.
• The methodology, utilizing machine-learning potentials, offers a general and transferable framework for ab initio thermodynamic predictions.