Self-assembly in mixtures with competing interactions.

Area of Science:

• Soft Matter Physics
• Computational Chemistry
• Materials Science

Background:

• Investigating binary particle mixtures with complex interactions is crucial for understanding microsegregation.
• Near-critical solvents and charged particles introduce unique challenges in predicting mixture behavior.

Purpose of the Study:

• To develop a predictive theory for structural and thermodynamic properties of binary particle mixtures.
• To investigate the impact of concentration fluctuations on phase diagrams.
• To analyze the formation and characteristics of layered structures in ordered phases.

Main Methods:

• Combining density functional theory and field-theoretical methods for theoretical predictions.
• Employing molecular dynamics (MD) simulations to validate theoretical models.
• Analyzing particle interactions with short-range attraction/repulsion and long-range repulsion/attraction.

Main Results:

• Concentration fluctuations qualitatively alter phase diagrams compared to mean-field predictions.
• Coexistence of low-density disordered and high-density layered phases observed.
• Ordered phases exhibit crystalline structure in solids and are absent in liquid crystals.
• Density and order decrease with temperature; a narrow two-phase region emerges at higher temperatures.

Conclusions:

• The developed theory accurately predicts microsegregation and phase behavior in complex binary mixtures.
• Layered structures form with distinct characteristics in solid and liquid crystalline states.
• Temperature significantly influences the density, order, and shape of ordered phases.