Monte Carlo Simulation Methods for Computing Liquid-Vapor Saturation Properties of Model Systems

Area of Science:

• Computational chemistry
• Thermodynamics
• Materials science

Background:

• Accurate computation of phase coexistence properties is crucial for understanding and predicting the behavior of complex molecules.
• Existing molecular simulation methods may face challenges in efficiently handling complex molecular systems.

Purpose of the Study:

• To present and evaluate histogram-based molecular simulation strategies for computing phase coexistence properties.
• To compare the effectiveness of different methods for locating saturation points and tracing saturation lines.

Main Methods:

• Utilized histogram-based approaches relating thermodynamic properties to probability distributions.
• Employed grand canonical and isothermal-isobaric ensembles.
• Incorporated reservoir and growth expanded ensemble techniques for molecule insertion.
• Applied temperature expanded ensemble techniques for tracing saturation lines.

Main Results:

• Demonstrated phase coexistence data for n-octane, cyclohexane, water, 1-propanol, squalane, and pyrene.
• Found the direct grand canonical approach most effective for locating a coexistence point at a specific temperature.
• Identified the isothermal-isobaric temperature expanded ensemble scheme as most effective for following saturation curves to low temperatures.

Conclusions:

• The discussed molecular simulation methods provide robust strategies for computing phase coexistence properties of complex molecules.
• The choice of method depends on whether the goal is to locate a specific coexistence point or to trace a saturation curve over a temperature range.