(476c) Molecular Exchange Monte Carlo: A Generalized Method for Identity Exchanges in Grand Canonical Monte Carlo Simulations
- Conference: AIChE Annual Meeting
- Year: 2018
- Proceeding: 2018 AIChE Annual Meeting
- Group: Computational Molecular Science and Engineering Forum
Wednesday, October 31, 2018 - 8:30am-8:45am
A generalized identity exchange algorithm is presented for Monte Carlo simulations in the grand canonical ensemble. The algorithm, referred to as Molecular Exchange Monte Carlo (MEMC), may be applied to multicomponent systems of arbitrary molecular topology, and provides significant enhancements in the sampling of phase space over a wide range of compositions. Three different approaches are presented for the insertion of large molecules, and the pros and cons of each method are discussed. The performance of the algorithms is highlighted through grand canonical Monte Carlo histogram-reweighting simulations of binary mixtures. In simulations of the binary mixture of perfluorobutane+butane, the acceptance rate for MEMC moves is up to 258 times that of configurational-bias insertions and deletions, producing two orders of magnitude improvements in computational efficiencies. Calculations performed for mixtures of methane with various n-alkanes show increases in acceptance rates for molecule exchanges of 2-70 times that of single molecule insertions, with corresponding order of magnitude improvement in computational efficiency. Comparisons to other methods, such continuous fractional component Monte Carlo are made.