Coarse grained molecular dynamics simulation of nanoconfined water

Area of Science:

• Computational chemistry and materials science
• Nanoscale physics and fluid dynamics

Background:

• Simulating water behavior in nanoscale confinement is crucial for understanding various physical and chemical processes.
• Existing atomistic models are computationally expensive for large-scale simulations of nanoconfined systems.

Purpose of the Study:

• To develop a coarse-grained (CG) model for efficient simulation of water confined between graphene surfaces.
• To ensure the developed CG model accurately predicts structural and dynamic properties of nanoconfined water.

Main Methods:

• Developed a pure CG model by grouping water sites and graphene atoms into CG beads.
• Constructed CG potentials by matching radial distribution functions and density profiles with mixed-grained simulations.
• Validated the model's transferability across a range of pore sizes, from narrow pores to bulk water.

Main Results:

• The CG model accurately predicts water layering and solvation forces in nanoconfined systems.
• Parallel diffusion coefficients of water molecules in pores are smaller than in bulk water.
• Water dynamics, including exchange rates between layers, were characterized, with equilibrium achieved in a few nanoseconds.

Conclusions:

• The developed CG model provides a computationally efficient and accurate method for studying nanoconfined water.
• The model's pore-size transferability allows for broad applicability in simulating water behavior in graphene-based nanoconfinement.
• The study offers detailed insights into the structural and dynamic properties of water at the nanoscale.