Jason Koski

Size-controlled self-assembly of superparamagnetic polymersomes.

We report the size-controlled self-assembly of polymersomes through the cooperative self-assembly of nanoparticles and amphiphilic polymers. Polymersomes densely packed with magnetic nanoparticles in the polymersome membrane (magneto-polymersome) were fabricated with a series of different sized iron oxide nanoparticles. The distribution of nanoparticles in a polymersome membrane was size-dependent; while small nanoparticles were dispersed in a polymer bilayer, large particles formed a well-ordered superstructure at the interface between the inner and outer layer of a bilayer membrane. The yield of magneto-polymersomes increased with increasing the diameter of incorporated nanoparticles. Moreover, the size of the polymersomes was effectively controlled by varying the size of incorporated nanoparticles. This size-dependent self-assembly was attributed to the polymer chain entropy effect and the size-dependent localization of nanoparticles in polymersome bilayers. The transverse relaxation rates (r2) of magneto-polymersomes increased with increasing the nanoparticle diameter and decreasing the size of polymersomes, reaching 555 ± 24 s(-1) mM(-1) for 241 ± 16 nm polymersomes, which is the highest value reported to date for superparamagnetic iron oxide nanoparticles.

Field theoretic simulations of polymer nanocomposites

Polymer field theory has emerged as a powerful tool for describing the equilibrium phase behavior of complex polymer formulations, particularly when one is interested in the thermodynamics of dense polymer melts and solutions where the polymer chains can be accurately described using Gaussian models. However, there are many systems of interest where polymer field theory cannot be applied in such a straightforward manner, such as polymer nanocomposites. Current approaches for incorporating nanoparticles have been restricted to the mean-field level and often require approximations where it is unclear how to improve their accuracy. In this paper, we present a unified framework that enables the description of polymer nanocomposites using a field theoretic approach. This method enables straightforward simulations of the fully fluctuating field theory for polymer formulations containing spherical or anisotropic nanoparticles. We demonstrate our approach captures the correlations between particle positions, present results for spherical and cylindrical nanoparticles, and we explore the effect of the numerical parameters on the performance of our approach.

Field-theoretic simulations of block copolymer nanocomposites in a constant interfacial tension ensemble

Block copolymers, due to their ability to self-assemble into periodic structures with long range order, are appealing candidates to control the ordering of functionalized nanoparticles where it is well-accepted that the spatial distribution of nanoparticles in a polymer matrix dictates the resulting material properties. The large parameter space associated with block copolymer nanocomposites makes theory and simulation tools appealing to guide experiments and effectively isolate parameters of interest. We demonstrate a method for performing field-theoretic simulations in a constant volume-constant interfacial tension ensemble (nVγT) that enables the determination of the equilibrium properties of block copolymer nanocomposites, including when the composites are placed under tensile or compressive loads. Our approach is compatible with the complex Langevin simulation framework, which allows us to go beyond the mean-field approximation. We validate our approach by comparing our nVγT approach with free energy calculations to determine the ideal domain spacing and modulus of a symmetric block copolymer melt. We analyze the effect of numerical and thermodynamic parameters on the efficiency of the nVγT ensemble and subsequently use our method to investigate the ideal domain spacing, modulus, and nanoparticle distribution of a lamellar forming block copolymer nanocomposite. We find that the nanoparticle distribution is directly linked to the resultant domain spacing and is dependent on polymer chain density, nanoparticle size, and nanoparticle chemistry. Furthermore, placing the system under tension or compression can qualitatively alter the nanoparticle distribution within the block copolymer.