Phase Separation Dynamics for a Polymer Blend Compatibilized by Protein-like Copolymers: A Monte Carlo Simulation

Dynamical self-consistent field theory captures multi-scale physics during spinodal decomposition in a symmetric binary homopolymer blend

We study the spinodal decomposition in a symmetric, binary homopolymer blend using our recently developed dynamical self-consistent field theory. By taking the extremal solution of a dynamical functional integral, the theory reduces the interacting, multi-chain dynamics to a Smoluchowski equation describing the statistical dynamics of a single, unentangled chain in a self-consistent, time-dependent, mean force-field. We numerically solve this equation by evaluating averages over a large ensemble of replica chains, each one of which obeys single-chain Langevin dynamics, subject to the mean field. Following a quench from the disordered state, an early time spinodal instability in the blend composition develops, before even one Rouse time elapses. The dominant, unstable, growing wavelength is on the order of the coil size. The blend then enters a late-time, t, scaling regime with a growing domain size that follows the expected Lifshitz-Slyozov-Wagner t^1/3 power law, a characteristic of a diffusion-driven coarsening process. These results provide a satisfying test of this new method, which correctly captures both the early and late time physics in the blend. Our simulation spans five orders-of-magnitude in time as the domains coarsen to 20 times the coil size, while remaining faithful to the dynamics of the microscopic chain model.

Morphology on Reaction Mechanism Dependency for Twin Polymerization

An in-depth knowledge of the structure formation process and the resulting dependency of the morphology on the reaction mechanism is a key requirement in order to design application-oriented materials. For twin polymerization, the basic idea of the reaction process is established, and important structural properties of the final nanoporous hybrid materials are known. However, the effects of changing the reaction mechanism parameters on the final morphology is still an open issue. In this work, the dependence of the morphology on the reaction mechanism is investigated based on a previously introduced lattice-based Monte Carlo method, the reactive bond fluctuation model. We analyze the effects of the model parameters, such as movability, attraction, or reaction probabilities on structural properties, like the specific surface area, the radial distribution function, the local porosity distribution, or the total fraction of percolating elements. From these examinations, we can identify key factors to adapt structural properties to fulfill desired requirements for possible applications. Hereby, we point out which implications theses parameter changes have on the underlying chemical structure.

Proteinlike copolymers as encapsulating agents for small-molecule solutes

We describe the utilization of proteinlike copolymers (PLCs) as encapsulating agents for small-molecule solutes. We perform Monte Carlo simulations on systems containing PLCs and model solute molecules in order to understand how PLCs assemble in solution and what system conditions promote solute encapsulation. Specifically, we explore how the chemical composition of the PLCs and the range and strength of molecular interactions between hydrophobic segments on the PLC and solute molecules affect the solute encapsulation efficiency. The composition profiles of the hydrophobic and hydrophilic segments, the solute, and implicit solvent (or voids) within the PLC globule are evaluated to gain a complete understanding of the behavior in the PLC/solute system. We find that a single-chain PLC encapsulates solute successfully by collapsing the macromolecule to a well-defined globular conformation when the hydrophobic/solute interaction is at least as strong as the interaction strength among hydrophobic segments and the interaction among solute molecules is at most as strong as the hydrophobic/solute interaction strength. Our results can be used by experimentalists as a framework for optimizing unimolecular PLC solute encapsulation and can be extended potentially to applications such as "drug" delivery via PLCs.