A temperature-dependent critical Casimir patchy particle model benchmarked onto experiment

Area of Science:

• Colloid science
• Soft matter physics
• Computational materials science

Background:

• Synthetic colloidal patchy particles self-assemble into superstructures (chains, networks) in binary liquid mixtures.
• Self-assembly is driven by critical Casimir interactions.
• Existing potential models lack quantitative accuracy for simulating and predicting this behavior.

Purpose of the Study:

• To develop a quantitatively accurate potential model for simulating patchy particle self-assembly.
• To establish a protocol for creating accurate models based on theoretical Casimir potentials and angular switching functions.

Main Methods:

• Developed a model combining theoretical Casimir potentials and angular switching functions.
• Utilized Monte Carlo simulations to optimize material-specific parameters.
• Matched model predictions to experimental data for chain length distribution and persistence length.

Main Results:

• Successfully optimized model parameters to accurately reproduce experimental observations.
• Demonstrated a systematic approach to obtain accurate potentials for critical Casimir interactions.
• Validated the model's ability to simulate patchy particle self-assembly.

Conclusions:

• The developed protocol provides a systematic method for creating accurate interaction potentials for patchy particles.
• This model enables precise simulation and prediction of self-assembled superstructures.
• The approach is suitable for large-scale simulations in colloid and soft matter research.