Conventional molecular simulations of multi-chain systems are hindered by harsh excluded-volume interactions and expensive pair-potential calculations. The former greatly reduces the chain relaxation towards equilibrium configurations and the efficiency of sampling the configurational space, while the latter becomes computationally very expensive for concentrated polymeric systems.

The idea of fast off-lattice Monte Carlo (FOMC) simulations is to perform particle-based Monte Carlo simulations in continuum with a Hamiltonian commonly used in polymer field theories such as the well developed self-consistent field (SCF) theory, where individual polymer segments are modeled as volumeless points and the excluded-volume interactions are modeled by the Helfand compressibility. This avoids the harsh repulsion and, in some cases, the pair-potential calculations, thus allowing much faster and better sampling of the configurational space. Furthermore, using the same Hamiltonian in both SCF calculations and FOMC simulations enables quantitative comparisons between the two without any parameter-fitting.

To demonstrate the great advantages of FOMC simulations, we have studied two polymeric systems: confined homopolymer solutions and microphase separation of diblock copolymers. In both cases, the FOMC simulations are compared with SCF calculations to reveal the effects of fluctuations ignored in the latter.