To gain insight into the fundamental processes determining the motion of macromolecules in polymeric matrices, the dynamical hindrance of polymeric dextran molecules diffusing as probe through a polyacrylamide hydrogel is systematically explored. Three complementary experimental methods combined with Brownian dynamics simulations are used to study a broad range of dextran molecular weights and salt concentrations. While multi-parameter fluorescence image spectroscopy (MFIS) is applied to investigate the local diffusion of single molecules on a microscopic length scale inside the hydrogel, a macroscopic transmission imaging (MTI) fluorescence technique and nuclear magnetic resonance (NMR) are used to study the collective motion of dextrans on the macroscopic scale. These fundamentally different experimental methods, probing different length scales of the system, yield long-time diffusion coefficients for the dextran molecules which agree quantitatively. The measured diffusion coefficients decay markedly with increasing molecular weight of the dextran and fall onto a master curve. The observed trends of the hindrance factors are consistent with Brownian dynamics simulations. The simulations also allow us to estimate the mean pore size for the herein investigated experimental conditions. In addition to the diffusing molecules, MFIS detects temporarily trapped molecules inside the matrix with diffusion times above 10 ms, which is also confirmed by anisotropy analysis. The fraction of bound molecules depends on the ionic strength of the solution and the charge of the dye. Using fluorescence intensity analysis, also MTI confirms the observation of the interaction of dextrans with the hydrogel. Moreover, pixelwise analysis permits to show significant heterogeneity of the gel on the microscopic scale.

A density functional theory for the bulk phase diagram of two-dimensional orientable hard rods is proposed and tested against Monte Carlo computer simulation data. In detail, an explicit density functional is derived from fundamental mixed measure theory and freely minimized numerically for hard discorectangles. The phase diagram, which involves stable isotropic, nematic, smectic, and crystalline phases, is obtained and shows good agreement with the simulation data. Our functional is valid for a multicomponent mixture of hard particles with arbitrary convex shapes and provides a reliable starting point to explore various inhomogeneous situations of two-dimensional hard rods and their Brownian dynamics.

Using the classical density functional theory of freezing and Monte Carlo computer simulations, we explore the liquid-crystalline phase behavior of hard rectangles on flat and cylindrical manifolds. Moreover, we study the effect of a static external field which couples to the rectangles' orientations, aligning them towards a preferred direction. In the flat and field-free case, the bulk phase diagram involves stable isotropic, nematic, tetratic, and smectic phases depending on the aspect ratio and number density of the particles. The external field shifts the transition curves significantly and generates a binematic phase at the expense of the tetratic phase. On a cylindrical manifold, we observe tilted smectic-like order, as obtained by wrapping a smectic layer around a cylinder. We find in general good agreement between our density functional calculations and particle-resolved computer simulations and mention possible setups to verify our predictions in experiments.

The dissolution of polyethylene oxide (PEO) tablets in water has been followed in situ by neutron radiography. When in contact with water, the crystalline phase of semi-crystalline PEO melts once a certain water content is attained. Polymer concentration profiles obtained from the neutron transmission images exhibited a pronounced kink which corresponds to a sharp front in the images and which is related to the melting transition. Sharp diffusion fronts and phase transitions are often linked to non-Fickian behaviour. However, by considering the time evolution of the complete concentration profiles in detail it is shown that the dissolution process can be explained using Fickian diffusion equations with a concentration-dependent diffusion coefficient.