Water liquid-vapor equilibria predicted by refined ab initio derived potentials

Area of Science:

• Physical Chemistry
• Computational Chemistry
• Thermodynamics

Background:

• Understanding water's behavior near its critical point is crucial for various scientific fields.
• Previous ab initio models have shown limitations in accurately reproducing water properties under these conditions.

Purpose of the Study:

• To evaluate the coexistence properties of water near the critical point using multiple ab initio models.
• To assess the performance of these models compared to previous ones and identify key factors influencing accuracy.

Main Methods:

• Grand canonical Monte Carlo simulations were employed.
• Multiple histogram reweighting techniques were utilized for enhanced sampling and analysis.
• Several ab initio models with varying degrees of complexity were tested.

Main Results:

• The tested ab initio models demonstrated good performance in reproducing water properties near the critical point.
• These models showed improvement over a previously used ab initio model.
• Polarizable rigid water models accurately predicted bulk geometry and dipole values, unlike non-polarizable models.

Conclusions:

• Ab initio models, particularly polarizable ones, are effective for simulating water's critical behavior.
• The accuracy of simulations is significantly influenced by the inclusion of polarization effects.
• These findings advance the computational understanding of water's phase behavior.