Numerical Study of Soft Colloidal Nanoparticles Interaction in Shear Flow

Area of Science:

• Materials Science
• Computational Mechanics
• Polymer Physics

Background:

• Experimental study of nanoparticle assembly mechanics is challenging due to complex interactions.
• Nanoparticle morphology dictates adhesive and elastic-plastic behaviors during contact.
• Understanding these interactions is crucial for predicting macroscopic properties of nanoparticle aggregates.

Purpose of the Study:

• To investigate the influence of contact interactions between polymer nanoparticles on aggregate properties.
• To develop and utilize a computational model for simulating nanoparticle assembly behavior.

Main Methods:

• Employed the discrete element method (DEM) to model interactions.
• Developed a model combining elastic-plastic deformation and adhesion for spherical polymeric nanoparticles.
• Simulated single-particle contacts and extended to multibody interactions in dispersed systems under shear flow.

Main Results:

• Adhesion and plastic deformation significantly affect pull-off forces in particle contacts.
• Aggregate size and cluster strength are dependent on nanoparticle softness.
• Softer nanoparticles lead to weaker clusters and lower interaction strength upon breakage.

Conclusions:

• Contact interaction type directly dictates the macroscopic mechanical response of nanoparticle assemblies.
• The developed DEM model accurately predicts the mechanical behavior of polymer nanoparticle systems.
• Primary particle properties can be adjusted to optimize the mechanical performance of nanoparticle assemblies.