Polymer Structure Predictor (PSP): A Python Toolkit for Predicting Atomic-Level Structural Models for a Range of Polymer Geometries.

Three-dimensional atomic-level models of polymers are the starting points for physics-based simulation studies. A capability to generate reasonable initial structural models is highly desired for this purpose. We have developed a python toolkit, namely, polymer structure predictor (psp), to generate a hierarchy of polymer models, ranging from oligomers to infinite chains to crystals to amorphous models, using a simplified molecular-input line-entry system (SMILES) string of the polymer repeat unit as the primary input.

Role of Solvation on Diffusion of Ions in Diblock Copolymers: Understanding the Molecular Weight Effect through Modeling.

Salt-doped diblock copolymers with microphase-separated domains of both an ion conductive and a mechanically strong polymer have been extensively studied due to their potential in transport applications. Several unusual or counterintuitive trends regarding their transport properties have been observed experimentally, such as increasing ion conduction as a function of molecular weight. A crucial feature of these systems is the strong solvation of ions in the conducting microphase due to its higher dielectric constant.

Diffusion in Lamellae, Cylinders, and Double Gyroid Block Copolymer Nanostructures.

We study transport of penetrants through nanoscale morphologies motivated by common block copolymer morphologies, using confined random walks and coarse-grained simulations. Diffusion through randomly oriented grains is 1/3 for cylinder and 2/3 for lamellar morphologies versus an unconstrained (homopolymer) system, as previously understood. Diffusion in the double gyroid structure depends on the volume fraction and is 0.