Concurrently coupling particle and continuum simulations to study block copolymer membrane fabrication

Area of Science:

• Materials Science
• Computational Chemistry
• Chemical Engineering

Background:

• Membrane fabrication via self-assembly and phase separation is crucial for various applications.
• Existing simulation methods struggle to capture both molecular details and large-scale phenomena efficiently.
• Understanding nonequilibrium structure formation in block copolymer systems is essential for designing advanced materials.

Purpose of the Study:

• To develop a concurrent multiscale simulation framework for block copolymer membrane fabrication.
• To integrate molecularly resolved particle simulations with continuum models for enhanced efficiency and accuracy.
• To enable predictive simulations of membrane formation on experimentally relevant scales.

Main Methods:

• Concurrent coupling of a coarse-grained particle model (for micro/macrophase separation) and the Uneyama-Doi continuum model (for large-scale morphology).
• Machine learning-guided adaptive coupling strategy to dynamically allocate computational resources.
• Consistent exchange of solvent fluxes between models for multicomponent systems.

Main Results:

• The framework successfully simulates micro- and macrophase separation, including thermal fluctuations and nonequilibrium morphologies.
• Adaptive strategy enables predictive simulations on length scales up to micrometers and time scales of minutes.
• Demonstrated application examining the influence of polymer concentration on membrane formation.

Conclusions:

• The developed framework provides a powerful computational tool for investigating complex soft-matter systems.
• It enables efficient and accurate simulations of nonequilibrium structure formation in membrane fabrication.
• The approach is general, extensible, and applicable to various multicomponent soft-matter systems.