Thermodynamic calculations using reverse Monte Carlo.

Area of Science:

• Computational materials science
• Statistical mechanics
• Thermodynamics

Background:

• Accurate thermodynamic calculations are crucial for materials design.
• Existing methods may be computationally intensive for complex systems.
• Reverse Monte Carlo (RMC) offers a powerful simulation approach.

Purpose of the Study:

• To develop a theoretical framework for thermodynamic calculations in binary lattice systems using RMC.
• To enable rapid and accurate estimation of thermodynamic properties, such as chemical potential.
• To utilize short-ranged order (SRO) parameters within the RMC framework.

Main Methods:

• Developed theoretical background for RMC in binary A_{x}B_{1-x} lattice systems.
• Utilized short-ranged order (SRO) parameters to describe atomic arrangements.
• Solved the detailed balance equation in terms of SRO parameters to find equilibrium values.
• Calculated thermodynamic properties, including chemical potential, from equilibrium SRO parameters.

Main Results:

• Successfully applied the RMC method to bulk lattice materials with varying interactions.
• Demonstrated accurate evaluation of chemical potential within seconds on a desktop computer.
• Showcased the ability to store RMC probability distributions as look-up tables for efficient property estimation.

Conclusions:

• The developed RMC-based method provides a fast and accurate approach for thermodynamic calculations in binary systems.
• The use of SRO parameters and RMC probability distributions offers a versatile tool for materials science research.
• This method significantly accelerates the estimation of thermodynamic properties across different conditions.