Local order and cluster formation in model fluids with competing interactions: a simulation and theoretical study

Area of Science:

• Physical Chemistry
• Soft Matter Physics
• Computational Fluid Dynamics

Background:

• Microscopic competing interactions in model fluids lead to complex phenomena like cluster formation.
• A preliminary study identified a subtle rearrangement of a distant correlation peak in the local density profile as a key indicator.

Purpose of the Study:

• To validate the preliminary finding on the "reversal of trend" mechanism in fluid cluster formation.
• To assess the accuracy of Hypernetted Chain theory in predicting this spatial rearrangement.
• To establish a sensitive criterion for identifying clustering thresholds in model fluids.

Main Methods:

• Monte Carlo simulations were employed to study various two-Yukawa fluid families.
• Simulations maintained fixed temperature, high fluid density, and varied attractive strength.
• Spatial correlation analysis focused on the local density profile and structure factor.

Main Results:

• The "reversal of trend" in spatial correlations was confirmed as a sensitive indicator of clustering onset.
• This phenomenon accurately identifies the clustering threshold, complementing traditional methods.
• Hypernetted Chain theory demonstrated good accuracy in predicting the observed spatial rearrangement.

Conclusions:

• The identified "reversal of trend" mechanism provides a robust criterion for detecting fluid clustering.
• The study validates the predictive power of Hypernetted Chain theory for this phenomenon.
• This work facilitates further investigations into fluid phase behavior using combined theoretical and simulation approaches.