Energy-Renormalization for Achieving Temperature Transferable Coarse-Graining of Polymer Dynamics

Area of Science:

• Soft Matter Physics
• Computational Materials Science
• Polymer Physics

Background:

• Bottom-up prediction of polymer properties using molecular dynamics is challenging.
• Coarse-grained (CG) models accelerate simulations but alter thermodynamics and dynamics.
• Existing CG models lack temperature transferability and chemical specificity for polymer dynamics.

Purpose of the Study:

• To develop a temperature-transferable and chemically specific coarse-grained (CG) method for polymer dynamics.
• To address deviations in activation free energies caused by coarse-graining.
• To enable accurate prediction of polymer dynamics across the entire glass formation range.

Main Methods:

• Proposed a strategy based on Adam-Gibbs (AG) theory for glass formation.
• Renormalized cohesive interaction strength and effective interaction length-scale parameters.
• Corrected activation free energy deviations in coarse-grained polystyrene dynamics.

Main Results:

• The energy-renormalization method accurately predicts atomistic polymer dynamics.
• Predictions cover the Arrhenius, non-Arrhenius, and non-equilibrium glassy regimes.
• Demonstrated accurate modeling of dynamic properties over the entire glass formation range.

Conclusions:

• Developed a practical scheme for temperature-transferable CG models.
• Enables predictive modeling and design of polymeric material properties.
• Overcomes limitations of traditional CG methods for polymer dynamics.