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Area of Science:

  • Polymer Science
  • Computational Chemistry
  • Materials Science

Background:

  • Coarse-grained (CG) simulation models simplify complex polymeric systems.
  • Matching interaction parameters between different CG models is crucial for reliable simulations.
  • Previous work established a mapping for symmetric diblock copolymers.

Purpose of the Study:

  • To investigate the transferability of a known mapping between CG simulation model interaction parameters.
  • To ensure matching long-range structural characteristics in multicomponent polymer systems.
  • To extend the mapping to various polymer architectures and mixtures.

Main Methods:

  • Utilized a mapping function derived from symmetric diblock copolymers.
  • Applied the mapping to asymmetric diblock copolymers, triblock copolymers, and copolymer-solvent mixtures.
  • Validated the mapping by comparing structure factor peaks from different CG models.
  • Proposed and demonstrated a methodology for creating ordered morphologies using hard repulsive potentials.

Main Results:

  • The mapping function showed excellent agreement for structure factor peaks across all investigated polymer melt systems.
  • The mapping proved transferable irrespective of polymer blockiness or overall composition.
  • The developed mapping functions were also effective for polymer-solvent systems.
  • Successfully created lamellar and cylindrical phases of diblock copolymers using the proposed methodology.

Conclusions:

  • The developed mapping is a universal tool for matching CG simulation models across diverse polymer systems.
  • This approach facilitates computationally efficient creation of ordered polymer morphologies.
  • The findings enable more accurate and predictive simulations of complex polymer behavior.