Generation, characterization, and modeling of polymer micro- and nano-particles

Polymer micro- and nano-particles are important in many technological applications, including polymer blends or alloys, biomaterials for drug delivery systems, electro-optic and luminescent devices, and polymer powder impregnation of inorganic fibers in composites. They are also critical in polymer-supported heterogeneous catalysis. This article reviews recent progress in experimental and simulation methods for generating, characterizing, and modeling polymer micro- and nano-particles in a number of polymer and polymer blend systems. A description of the use of gas atomization (of melts) and microdroplet (solution) approaches to generation and characterization of spherical polymer powders and microparticles represents their unique applications, giving the non-specialist reader a comprehensive overview. Using novel instrumentation developed for probing single fluorescent molecules in submicrometer droplets, it is demonstrated that polymer particles of nearly arbitrary size and composition can be made with uniform size dispersion. This interesting finding is ascribed to new dynamic behavior, which emerges when polymers are confined in a small droplet of solution the size of a molecule or molecular aggregates. Solvent evaporation takes place on a time scale short enough to frustrate phase separation, producing dry pure polymer or polymer blend microparticles that have tunable properties and that are homogeneous within molecular dimensions. In addition, it shows how a number of optical methodologies such as Fraunhofer diffraction can be used to probe polymer particles immobilized on two-dimensional substrates or levitated in space using a three-dimensional quadrupole (Paul) trap. Unlike conventional methods such as electron-beam microscopy, the optical diffraction methods provide a unique look inside a polymer particle in a measurement time scale of a few milliseconds, making it attractive to in-line production applications. In particular, it shows that it is possible to use computational neural networks, extensive classical trajectory calculations (i.e., classical molecular dynamics methods) in conjunction with experiments to gain deeper insights into the structure and properties of the polymer microparticles. Overall, it is possible to use the new understanding of phase separation to produce a number of useful, scientifically interesting homogeneous polymer blends from bulk-immiscible components in solution. Additionally, this new knowledge provides useful guidelines for future experimental studies and theory development of polymer and polymer blend micro- and nano-particles, which are not widely studied.