Density functional for additive mixtures

Area of Science:

• Statistical Mechanics
• Physical Chemistry
• Computational Physics

Background:

• Developing accurate theoretical models for particle mixtures is crucial for understanding their behavior.
• Existing theories often struggle with systems involving both soft and hard interactions or complex cross-species interactions.

Purpose of the Study:

• To introduce a novel density functional theory (DFT) for mixtures of particles with radially symmetric potentials.
• To generalize the soft fundamental measure theory (SFMT) for multicomponent systems.
• To provide a theoretical framework that respects known physical limits and expansions.

Main Methods:

• Formulated a DFT for mixtures with an additivity constraint on cross interactions.
• Extended the soft fundamental measure theory (SFMT) to handle mixture interactions.
• Ensured the theory's consistency with zero-dimensional limits and virial expansions.

Main Results:

• The developed DFT accurately models systems with soft or hard interactions between like particles.
• The theory reproduces Rosenfeld's functional for hard sphere mixtures.
• Calculated pair distributions for colloidal hard spheres and star polymer mixtures, showing good agreement with simulations.

Conclusions:

• The new DFT provides a robust framework for studying particle mixtures.
• The theory's applicability is demonstrated through successful prediction of colloidal mixture behavior.
• This approach offers a valuable tool for theoretical and computational studies of complex fluid systems.