Data for: Efficient dynamical field-theoretic simulations for multi-component systems

Understanding the phase behavior and dynamics of
multi-component polymeric systems is essential for designing materials
used in applications ranging from biopharmaceuticals to consumer products.
While computational tools for understanding the equilibrium properties of
such systems are relatively mature, simulation platforms for investigating
non-equilibrium behavior  are comparatively less developed.
Dynamic self-consistent field theory (DSCFT) is a method that retains
essential microscopic thermodynamics while enabling a continuum-level
understanding of multi-component, multi-phase diffusive transport. A
challenge with DSCFT is its high computational complexity and cost, along
with the difficulty of incorporating thermal fluctuations. External
potential dynamics (EPD) offers a more efficient approach to studying
inhomogeneous polymers out of equilibrium, providing similar accuracy to
DSCFT but with significantly lower computational cost. In this work, we
introduce an extension of EPD to enable efficient and stable simulations
of multi-species, multi-component polymer systems, while embedding
thermodynamically consistent noise. We validate this framework through
simulations of a triblock copolymer melt and spinodally decomposing binary
and ternary polymer blends, demonstrating its capability to capture key
features of phase separation and domain growth. Furthermore, we highlight
the role of thermal fluctuations in early-stage coarsening. This study
provides new insights into the interplay between stochastic and
deterministic effects in the dynamic evolution of polymeric fluids with
the EPD framework offering a robust and scalable approach for
investigating the complex dynamics of multi-component polymeric materials.