Multi-scale simulations of polymeric nanoparticle aggregation during rapid solvent exchange

Area of Science:

• Materials Science
• Nanotechnology
• Computational Chemistry

Background:

• Fabricating stable nanoparticles with controlled properties is crucial for diverse applications.
• Flash NanoPrecipitation (FNP) offers a rapid solvent exchange method for nanoparticle synthesis.
• Understanding nanoparticle formation mechanisms at multiple scales is essential for process optimization.

Purpose of the Study:

• To develop and validate a multi-scale simulation approach for Flash NanoPrecipitation (FNP).
• To investigate the aggregation mechanisms governing nanoparticle formation during FNP.
• To establish quantitative relationships between processing parameters and nanoparticle characteristics.

Main Methods:

• Utilized a multi-scale simulation strategy combining molecular dynamics (MD) and kinetic Monte Carlo (KMC) methods.
• Employed MD simulations to capture microscopic details of nanoparticle formation.
• Applied KMC simulations to extend the analysis to macroscopic length and time scales.

Main Results:

• Achieved good agreement between simulation predictions and experimental results for nanoparticle fabrication.
• Elucidated nanoparticle aggregation mechanisms at both microscopic and macroscopic levels.
• Determined the influence of mixing rate and polymer feed concentration on nanoparticle size and growth time.

Conclusions:

• The multi-scale MD/KMC simulation approach provides a powerful tool for understanding and optimizing the FNP process.
• This method enables quantitative predictions and facilitates the rational design of nanoparticles with desired properties.
• The findings offer valuable insights for tailoring FNP for specific material applications.