Monte Carlo Simulation Modeling of Nanoparticle-Polymer Cosuspensions

Area of Science:

• Materials Science
• Chemical Engineering
• Computational Chemistry

Background:

• Polymer-particle nanocomposites require understanding particle and polymer behavior in suspension.
• Simulations are crucial for identifying parameters governing suspension behavior.

Purpose of the Study:

• To investigate the agglomeration processes of zinc oxide (ZnO) nanoparticle and poly(methyl methacrylate) (PMMA) polymer cosuspensions.
• To analyze the impact of resting time, particle-to-polymer ratio, polymer chain length, and drying on agglomeration.

Main Methods:

• Utilized a constant number Monte Carlo simulation approach.
• Employed a modified Derjaguin-Landau-Verwey-Overbeek (DLVO) theory to model particle-particle interactions.
• Measured average agglomerate size and number under varying conditions.

Main Results:

• Agglomerate size increased with suspension resting time and particle content, reaching 4.6 μm at 20 vol % particle content after 30 min.
• Agglomeration intensified with increasing polymer chain length.
• Agglomerate size distribution followed a lognormal pattern across all particle contents.

Conclusions:

• Suspension resting time and particle concentration are key factors influencing ZnO-PMMA nanocomposite agglomeration.
• Higher polymer chain length exacerbates particle agglomeration.
• Drying enhances suspension stability due to increased viscosity and depletion stabilization, counteracting agglomeration.