Mesoscale Simulations of Polymer Solution Self-Assembly: Selection of Model Parameters within an Implicit Solvent...

Area of Science:

• Polymer Science
• Computational Chemistry
• Materials Science

Background:

• Coarse-grained modeling is essential for simulating polymer systems across diverse time and length scales.
• Selecting accurate model parameters remains a significant challenge for faithful structural and dynamic characterization.

Purpose of the Study:

• To develop a robust coarse-grained modeling framework for polymer systems.
• To establish a clear relationship between model parameters and experimentally measurable quantities.
• To enable accurate prediction of polymer assembly and behavior.

Main Methods:

• A hybrid particle- and field-based simulation approach was employed.
• A generalized energy functional based on density fields was utilized.
• Extensive exploration of model parameter spaces was performed.

Main Results:

• A comprehensive parameter map correlating model parameters with experimental observables was generated.
• The model successfully reproduced experimentally observed polymer solution assembly across various concentrations and solvent qualities.
• Simulations accurately captured structure and shape evolution in emulsified block copolymer droplets.

Conclusions:

• The developed hybrid modeling approach provides a powerful tool for coarse-grained polymer simulations.
• Accurate parameter mapping is crucial for achieving predictive power in polymer modeling.
• This methodology facilitates the study of complex polymer phenomena, including self-assembly and interfacial behavior.