Monte Carlo simulations in generalized isobaric-isothermal ensembles

Area of Science:

• Computational Physics
• Statistical Mechanics
• Chemical Physics

Background:

• Traditional ensemble simulations often require multiple runs to cover broad thermodynamic conditions.
• Efficient calculation of thermodynamic averages across diverse pressures and temperatures is crucial for materials science and physical chemistry.

Purpose of the Study:

• To introduce novel generalized isobaric-isothermal ensemble Monte Carlo algorithms.
• To enable calculation of thermodynamic averages across wide pressure and temperature ranges from a single simulation.

Main Methods:

• Development of three generalized algorithms: multibaric-multithermal, multibaric-isothermal, and isobaric-multithermal.
• Implementation of Monte Carlo simulations with random walks in volume and/or potential energy space.
• Application to a 500-particle Lennard-Jones 12-6 potential system.

Main Results:

• Demonstrated the effectiveness of the proposed algorithms.
• Showcased the ability to obtain isobaric-isothermal-ensemble averages over wide pressure and temperature ranges in a single simulation run.
• Validated the approach using the Lennard-Jones potential.

Conclusions:

• The developed generalized ensemble Monte Carlo algorithms significantly improve the efficiency of thermodynamic property calculations.
• These methods provide a powerful tool for exploring phase diagrams and thermodynamic behavior of various systems.
• The algorithms are effective for systems with intermolecular potentials like the Lennard-Jones interaction.