Simulations of Polymeric Nanoparticle Assembly Through Rapid Solvent Exchange

Abstract

Structured nanoparticles are important for various scientific and industrial applications. For example, Janus particles can act as pigments in electronic paper, interfacial stabilizers, optical probes and catalysts; core-shell particles are useful in drug delivery; patchy particles can self-assemble into hierarchical structures. These applications require nanoparticles with a narrow size and morphology distribution, which needs to be addressed by the fabrication methods. In addition, a method which is simple and scalable is also desirable in order to achieve commercial applications of the nanoparticles. Flash Nanoprecipitation (FNP), which involves the rapid mixing of polymers in solution with a miscible non-solvent, is a continuous and scalable process that offers independent control over nanoparticle size, morphology, and composition.

To understand the assembly mechanism of FNP and to make quantitative predictions for experiments, I performed molecular dynamics (MD) and kinetic Monte Carlo (KMC) simulations. On the nanoscale, the MD simulations studied the assembly mechanism and revealed how nanoparticles with a range of surface structures, including Janus, core-shell and patchy, arise from different processing conditions. The simulations also indicated that nanoparticle morphologies and other properties such as the composition and patchiness can be reliably tuned. To reach macroscopic length- and time-scales, I performed KMC simulations and studied how nanoparticle size and size distribution can be controlled by processing parameters specific to FNP, such as the mixing rate and the feed concentration. The model produced results in quantitative agreement with experiments and also provided insights on particle aggregation mechanism through the solvent displacement process. This multi-scale simulation approach allows predictions for the FNP process from a given set of feed polymers and processing parameters. The results demonstrate that the process is highly promising for the production of structured nanoparticles with various surface features in a scalable and controlled way. These results also provide guidelines for future design and preparation of polymeric nanoparticles with desired properties using FNP techniques, and thus facilitate their applications in various areas.