A Hybrid Green-Kubo (hGK) Framework for Calculating Viscosity from Short MD Simulations

Area of Science:

• Computational chemistry and materials science.
• Molecular dynamics simulations.
• Transport phenomena.

Background:

• Viscosity calculation via equilibrium molecular dynamics (MD) traditionally uses the Green-Kubo (GK) framework, integrating the stress autocorrelation function (SACF).
• The conventional GK method demands extensive phase space sampling, proving computationally prohibitive for complex systems like soft matter and polymers due to slow convergence.
• Accurate viscosity prediction is crucial for understanding and designing materials for applications ranging from lubricants to electrolytes.

Purpose of the Study:

• To introduce a novel hybrid Green-Kubo (hGK) framework for efficient and accurate viscosity calculations from MD simulations.
• To overcome the limitations of traditional GK methods, particularly concerning computational cost and convergence issues in challenging systems.
• To provide a computationally inexpensive yet accurate alternative for viscosity prediction in molecular liquids, polymer melts, and ionically conducting soft materials.

Main Methods:

• Developed a hybrid Green-Kubo (hGK) framework that partitions the SACF into short-time ballistic and long-time relaxation components.
• The short-time component is directly extracted from MD simulations, while the long-time tail is modeled using analytically motivated functions fitted to short trajectories.
• Benchmarked the hGK method against SPC/E water and applied it to challenging electrolyte systems (EC-LiTFSI and PEO-LiTFSI) where traditional GK fails.

Main Results:

• The hGK framework demonstrates excellent agreement with established results for SPC/E water.
• Successfully predicted viscosities for electrolyte systems (EC-LiTFSI and PEO-LiTFSI), overcoming convergence failures of the traditional GK method.
• Achieved substantial computational savings, reducing required sampling by several orders of magnitude without compromising predictive accuracy.

Conclusions:

• The hGK framework offers a conceptually simple, broadly applicable, and computationally efficient approach for viscosity prediction.
• This method significantly reduces the computational burden associated with MD simulations for viscosity calculations, especially for soft matter and ionic materials.
• The hGK method presents a promising advancement for materials modeling, enabling accurate viscosity predictions with unprecedented efficiency.