Free-energy model for nanoparticle self-assembly by liquid crystal sorting.

Area of Science:

• Materials Science
• Soft Matter Physics
• Computational Chemistry

Background:

• Nanoparticle (NP) self-assembly into ordered structures is crucial for advanced materials.
• Liquid crystals (LCs) offer a unique medium for templating NP organization.
• Understanding the thermodynamic driving forces is key to controlling NP assembly.

Purpose of the Study:

• To model the self-assembly of nanoparticles into microshells within a liquid crystal host.
• To investigate the thermodynamic principles governing shell formation.
• To develop an analytical model for predicting equilibrium configurations.

Main Methods:

• Field-based Monte Carlo simulations were employed to explore system configurations.
• Minimization of a free-energy functional incorporating NP excluded-volume and LC interactions.
• Development of a Gaussian-profile approximation for the LC order-parameter field.

Main Results:

• Equilibrium configurations of nanoparticle shells up to 10 μm were determined.
• An analytical model accurately predicted free energies of LC droplets and microshells.
• A first-order phase transition between states with and without microshells was identified.

Conclusions:

• Field-based thermodynamic methods provide a robust theoretical framework for NP shell self-assembly in LCs.
• The transition is primarily governed by excluded-volume and phase-transition energies.
• LC elasticity plays a minor role, mainly influencing the transition barrier.