This project considers the hierarchical structure formed in aqueous solution from rationally‑designed block polymer sequence and chemistry. Regular nanoscale structures spontaneously form in aqueous solution by tailoring the antagonistic interactions among the solution and copolymer moieties. These structures, however, can display a hierarchy at multiple length scales, therefore making characterization a challenge. Further, experimentally, it is demonstrated that monomer-level modifications induce larger scale structure changes. This is a general outcome facing modern tailored materials, thereby increasing the need for a rapid materials property-space searches.
Block copolymer amphiphiles are larger-scale analogues to surfactants that have a hydrophilic head group and hydrophobic tail. However, polymer-based amphiphiles have an advantage of designed molecular weight, block asymmetry, and relative solubility. Further, by incorporating biomimetic and specific functional groups, the molecular-scale ordering can lead to novel morphologies (Figure 1). Further by considering the multi-block structure one may design materials that span nanoparticles, gels, and ordered solutions that would serve different purpose in biomaterials design.
Figure 1. Adapted from S. Venkataraman et al. Macromolecules 46, 4839 (2013)
Block Polyelectrolytes : In collaboration with CHiMaD
Complex coacervates are hierarchical structured materials formed by oppositely charged polymers. These ion-containing multi-block polymer complexes form materials that span discrete nanoscale objects, solid-liquid two-phase systems, microphase-ordered viscoelastic solids, and gels. The hierarchically-structured materials have a vast materials property phase-space controlled not only by the polymer parameters, but the solution conditions, and non-equilibrium mixing conditions. Due to the long-ranged and strong electrostatic interactions, combined with block copolymer microstructure, these materials represent a challenge in polymer physics, both experiment and simulation. This project shall provide quantitative unique experimental data to test predictions and identify missing molecular-mesoscale structure information for challenging model systems. It is a goal to cooperate to develop and advance simulation methods and models toward predictive material properties to accelerate in silico materials discovery.