This award supports computational studies of the equilibrium behavior and dynamics of block copolymer materials aimed to identify universal behavior. Understanding the equilibrium behavior of these materials has long been based on various forms of self-consistent-field theory. The self-consistent-field approximation is valid in the limit of very long, very strongly overlapping polymers, but neglects strong collective correlations that have very important effects for shorter, more strongly interacting polymers. More sophisticated coarse-grained theories beyond self-consistent-field approximations yield predictions for all physical properties that depend upon the degree of overlap, as quantified by a dimensionless parameter. Simulations of the disordered phase of diblock copolymers have confirmed the predicted existence of systematic, universal behavior of the structure factor that can now be quantitatively described by recently developed theories. Two research thrusts supported by this award will build upon this progress in different ways.
The first thrust is a comprehensive computational study of the parameter dependence of phase boundaries in diblock copolymer melts, using graphics processor unit accelerated simulations and free energy methods to precisely identify phase boundaries. This project aims to use simulation to produce a universal phase map for finite diblock copolymers. This will generalize the phase map in a manner that should allow accurate quantitative predictions of phase boundaries even for short, strongly interacting diblock copolymers. Distinctive features of this approach include development of more sophisticated methods for analyzing simulation results in order to minimize ambiguities that arise from imperfect knowledge of the phenomenological Flory-Huggins interaction parameter.
The second thrust focuses on the use of simulations to study collective dynamical phenomena in diblock copolymer melts. Specifically, it will address collective dynamics in the disordered phase near the order-disorder transition, and the dynamics and mechanisms of order-disorder and order-order transitions.
The research supported by this award will provide opportunities for training graduate students in cutting edge computational and theoretical methods in an environment that provides rich exposure to experimental aspects of polymer science. This award also supports the development, documentation, and dissemination of open source computational software for both particle-based simulations and self-consistent field calculations, which contributes to the cyberinfrastructure of the soft-materials research community.
Nontechnical Summary
This award supports computational studies aimed to advance understanding of materials made from long chain-like molecules, polymers. Block copolymers are polymers comprised of linear blocks or subchains of different chemistry. A linear polymer chain, that contains two such blocks, of A and B monomers, bonded together by their ends forming a bigger chain (AB), is called a diblock copolymer. At temperatures at which mixtures of liquids composed of pure A and pure B chains would still be a liquid, diblock copolymers form periodically ordered structures. Spontaneous formation of these periodic structures is driven by the tendency of different blocks to phase separate, and by the fact that macroscopic phase separation is suppressed by the covalent linkage of the two blocks with each other. These ordered structural materials found applications as membranes for water purification, and as template materials for microelectronics and storage devices. Studies suggest that diverse kinds of diblock copolymers display nearly identical behavior when interpreted in the correct way. This award supports research aimed to advance fundamental understanding of diblock copolymer materials and would contribute to the ability to design new diblock copolymer materials with desired properties for new applications.
The PI will investigate whether much more accurate predictions might be possible for real systems by quantifying how the behavior seen in computer simulations depends on interactions between chains. A primary goal of this research is to use computer simulations to generate a map of structural transformations as related to chemical structure and chain interactions.
This award also supports the development, documentation, and dissemination of open source software that contributes to the cyberinfrastructure of the soft-materials research community.
