Search

Recent interest in parallelizing flat-histogram transition-matrix Monte Carlo simulations in the grand canonical ensemble, due to its demonstrated effectiveness in studying phase behavior, self-assembly and adsorption, has led to the most extreme case of single-macrostate simulations, where each macrostate is simulated independently with ghost particle insertions and deletions. Despite their use in several studies, no efficiency comparisons of these single-macrostate simulations have been made with multiple-macrostate simulations. We show that multiple-macrostate simulations are up to 3 orders of magnitude more efficient than single-macrostate simulations, which demonstrates the remarkable efficiency of flat-histogram biased insertions and deletions, even with low acceptance probabilities. Efficiency comparisons were made for supercritical fluids and vapor–liquid equilibrium of bulk Lennard-Jones and a three-site water model, self-assembling patchy trimer particles and adsorption of a Lennard-Jones fluid confined in a purely repulsive porous network, using the open source simulation toolkit FEASST. By directly comparing with a variety of Monte Carlo trial move sets, this efficiency loss in single-macrostate simulations is attributed to three related reasons. First, ghost particle insertions and deletions in single-macrostate simulations incur the same computational expense as grand canonical ensemble trials in multiple-macrostate simulations, yet ghost trials do not reap the sampling benefit from propagating the Markov chain to a new microstate. Second, single-macrostate simulations lack macrostate change trials that are biased by the self-consistently converging relative macrostate probability, which is a major component of flat histogram simulations. Third, limiting a Markov chain to a single macrostate reduces sampling possibilities. Existing parallelization methods for multiple-macrostate flat-histogram simulations are shown to be more efficient than parallel single-macrostate simulations by approximately an order of magnitude or more in all systems investigated.

Using molecular simulations, we investigate the structural and diffusive dynamics properties of a model fluid in highly absorptive cylindrical pores. At subcritical temperatures, self-diffusivity displays three distinct regimes as a function of average pore density ρ: (1) a decrease in self-diffusivity with increasing ρ at low ρ, (2) constant self-diffusivity with respect to varying ρ at moderate density, and (3) a decrease in self-diffusivity with increasing ρ at high density. These regimes are closely linked to the thermodynamic properties of the fluid in the pore, specifically, the adsorption isotherm, isosteric heat of adsorption, and the density profile. We show that these three diffusivity regimes qualitatively correspond to three distinct adsorption regimes: monolayer formation, multilayer adsorption, and pore filling, respectively. In addition, we find that the self-diffusivity is a universal function of the local film density in the monolayer formation regime at subcritical temperatures. The results of this work suggest a potential means to estimate the self-diffusivity over a broad pressure range using a limited number of experiments.