An extensible density-biasing approach for molecular simulations of multicomponent block copolymers

A node-density biased Monte Carlo methodology is proposed for the molecular structure generation of complex block copolymers. Within this methodology, the block copolymer is represented as bead-spring model. Using self-consistent field theory, a density field for all monomer species within the system is calculated. Block copolymers are generated by random walk configuration biased by the density fields. The proposed algorithm then modifies the generation process by taking the global structure of the polymer into account. It is then demonstrated that these global considerations can be built into the sampling procedure, specifically through functions that assign a permissible difference in density field value between relevant monomer species to each step of the random walk. In this way, the random walk may be naturally controlled to provide the most appropriate conformations. The overall viability of this approach has been demonstrated by using the resulting configurations in molecular dynamics simulations. This new methodology is demonstrated to be powerful enough to generate molecular configurations for a much wider variety of materials than the original approach. Two key examples of the new capabilities of the method are viable configurations for ABABA pentablock copolymers and ABC triblock terpolymers.

Automated summary

A node-density biased Monte Carlo methodology is proposed for the molecular structure generation of complex block copolymers. Within this methodology, block copolymers are represented as bead-spring models and a density field is calculated using self-consistent field theory. The generation process is modified taking the global structure of the polymer into account. The resulting configurations are shown to be suitable for molecular dynamics simulations of a wider variety of materials.