(89a) A Versatile Coarse-Grained Approach for Simulating Multi-Component Polymers: Field-Accelerated Monte Carlo Simulation

Coarse-grained simulations have played a crucial role in advancing our understanding of polymer behaviors. The success owes to one unique feature of polymers -- their generic and universal behaviors are to a large extent insensitive to interaction details at the atomistic level. The reduced computational cost enables coarse-grained simulations to access the experimentally relevant degree of polymerization and structural length scale. Coarse-grained simulations can be generally categorized into the particle-based and field-based approach. The particle-based method provides more microscopic details and higher spatial resolution for a given model, while the field-based approach enjoys better computational efficiency in simulating dense and inhomogeneous systems. Here we present a hybrid particle-field scheme -- Field-Accelerated Monte Carlo (FAMC) Simulation, that aims to take advantage of both approaches. The FAMC scheme offers the flexibility of computing interactions in the simulated system in the particle- or field-based fashion depending on their specific types. The choice between the two representations can be made based on physical considerations of the strength and the magnitude of fluctuation of the interaction energy. Applications of FAMC to two polymer systems are discussed to illustrate the versatility of the method. The first example is a microphase separating diblock copolymer melt containing monomers that can form hydrogen bonds. A small fraction of these hydrogen bonding "moieties" could induce drastic changes in the free energy landscape, leading to abruptly different structural and dynamical behaviors. This requires simulations to simultaneously capture the microscopics of the reversible bonding (difficult to achieve in a full field-based approach) in the presence of inhomogeneous microstructures (computationally expensive for a full particle-based approach). Another application is to simulate dilute polymer solutions with explicit solvents. Such simulations are computationally demanding for a full particle-based method due to the need for computing a large number of solvent-solvent interactions. A mean field approach, on the other hand, is not sufficient to capture the large magnitude fluctuations as a result of small polymer concentration. We show that in simulating both systems, the FAMC method offers the optimal combination of accuracy and computational efficiency. A prospective outlook on the FAMC's applications in polymer research will also be discussed at the end of the presentation.