Genetic Algorithm Workflow for Parameterization of a Water Model Using the Vashishta Force Field

Area of Science:

• Geochemistry
• Materials Science
• Computational Chemistry

Background:

• Water significantly alters mineral surface properties, impacting geological processes like fracture.
• Accurate molecular-level water models are essential for simulating mineral behavior in aqueous environments.
• Existing molecular dynamics water models are often computationally expensive or lack compatibility with mineral interaction models.

Purpose of the Study:

• To develop a computationally efficient water model for molecular dynamics simulations.
• To enable accurate modeling of mineral-water interactions, particularly in dynamic processes.
• To parametrize a 3-point water model using the Vashishta potential form.

Main Methods:

• Parametrization of a 3-point water potential using the Vashishta potential form.
• Molecular dynamics simulations to study water properties and mineral interactions.
• Comparison of model predictions with experimental transport and liquid-vapor properties.

Main Results:

• The Vashishta-based water model shows good agreement with experimental transport and liquid-vapor properties.
• The model is computationally inexpensive, facilitating large-scale simulations.
• The Vashishta form ensures compatibility with existing silica glass models.

Conclusions:

• The developed Vashishta water model provides a computationally efficient and accurate method for simulating water properties.
• This model is suitable for studying mineral-water interactions, advancing research in geochemistry and materials science.
• Enables the simulation of dynamic processes involving mineral fracture in aqueous environments.