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Assembly and Characterization of Polyelectrolyte Complex Micelles
Published on: March 2, 2020
Simulation estimates of cloud points of polydisperse fluids
Matteo Buzzacchi1, Peter Sollich, Nigel B Wilding
1Department of Physics, University of Bath, Bath BA2 7AY, United Kingdom.
Summary
Two Monte Carlo simulation methods accurately determine cloud-point densities and coexistence properties for polydisperse fluid mixtures. Both approaches yield distinct finite-size corrections, with the second method showing exponentially smaller corrections for phase coexistence properties.
Area of Science:
- Physical Chemistry
- Computational Fluid Dynamics
- Statistical Mechanics
Background:
- Accurate determination of phase coexistence properties is crucial for understanding fluid mixtures.
- Polydisperse fluid mixtures present unique challenges due to their broad distribution of molecular sizes.
- Grand-canonical ensemble Monte Carlo simulations are a powerful tool for studying fluid phase behavior.
Purpose of the Study:
- To present two novel Monte Carlo simulation methods for calculating cloud-point densities and coexistence properties of polydisperse fluid mixtures.
- To theoretically analyze and compare the finite-size corrections associated with each method.
- To validate the theoretical predictions through simulations of a polydisperse lattice-gas model.
Main Methods:
- Method 1: Constraining the chemical potential distribution to match a prescribed particle density distribution, leading to unequal peak weights in fluctuating particle density.
- Method 2: Assigning the chemical potential distribution to satisfy an equal-peak-weight criterion, requiring operational determination of phase weighting factors.
- Monte Carlo simulations in the grand-canonical ensemble were employed, specifically for a polydisperse lattice-gas model.
Main Results:
- Method 1 predicts finite-size corrections that scale as power laws with system size.
- Method 2 predicts finite-size corrections that are exponentially small with system size.
- Simulations of the polydisperse lattice-gas model demonstrated excellent quantitative agreement with both theoretical scaling predictions.
Conclusions:
- Both described Monte Carlo methods are effective for obtaining cloud-point densities and coexistence properties of polydisperse fluid mixtures.
- The choice of method impacts the nature and magnitude of finite-size corrections.
- The second method offers superior accuracy for coexistence properties due to its exponentially small finite-size corrections.
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