We have generated closed-cell microcellular foams from gliadin, an abundantly available wheat storage protein. The extraction procedure of gliadin from wheat gluten, which involves only the natural solvents water and ethanol, respectively, is described with emphasis on the precipitation step of gliadin which results in a fine dispersion of mostly spherical, submicron gliadin particles composed of myriad of protein molecules. A dense packing of these particles was hydrated and subjected to an atmosphere of carbon dioxide or nitrogen in a high-pressure cell at 250 bar. Subsequent heating to temperatures close to but still below 100 A degrees C followed by sudden expansion and simultaneous cooling resulted in closed-cell microcellular foam. The spherical gliadin templates along with the resulting foam have been analyzed by scanning electron microscope (SEM) pictures. The size distribution of the primary particles shows diameters peaked around 0.54 mu m, and the final foam cell size peaks around 1.2 mu m, at a porosity of about 80 %. These are the smallest foam cell sizes ever reported for gliadin. Interestingly, the cell walls of these microcellular foams are remarkably thin with thicknesses in the lower nanometer range, thus nourishing the hope to be able to reach gliadin nanofoam.

The shape and interactions between model microemulsion droplets (R = 8.2 nm, polydispersity 20%) either decorated with hydrophilic-hydrophobic diblock (PEO-m: C12H25-(EO)n, MPEO = 5.2 kg/mol), or with telechelic triblock copolymers (PEO-2m: C12H25-(EO)2n-C12H25 , MPEO = 10.4 kg/mol) have been studied by small angle neutron scattering (SANS). The results as a function of droplet and copolymer concentration have been compared to the reference case of the bare microemulsion. Using Porod representations, the average bare droplet size was found to be independent of microemulsion concentration in the range studied here, up to some 13%v. Upon addition of copolymer (from r=0 to 30 hydrophobic stickers per droplet), the average droplet radius was unaffected. The interactions between bare and decorated droplets have been analyzed using the structure factor S(q), at first in a model-free way based on its low-q limit S(q→0). This analysis provides clear evidence on the concentration-dependent repulsive or attractive nature of the contributions to the pair droplet-droplet pair potential of the copolymers. Model pair potentials describing the steric repulsions and attractions by copolymer bridging are used to describe the low-q behavior of the structure factor based on an integral equation approach, giving a quantitative estimate of the range and amplitude of the potentials. Moreover, they provide an explanation for the observed transient clustering in terms of a shallow minimum of the total potential.

The existence of two independent filler-dependent high-temperature Maxwell–Wagner–Sillars (MWS) dielectric processes is demonstrated and characterized in detail in silica-filled styrene–butadiene (SB) industrial nanocomposites of simplified composition using Broadband Dielectric Spectroscopy (BDS). The uncrosslinked samples are made with 140 kg/mol SB-chains, half of which carry a single graftable end-function (50% D3), and Zeosil 1165 MP silica incorporated by solid-phase mixing. While one high-temperature process is known to exist in other systems, the dielectric properties of a new silica-related process – strength, relaxation time, and activation energy – have been evidenced and described as a function of silica volume fraction and temperature. In particular, it is shown that its strength follows a percolation behavior as observed with the ionic conductivity and rheology. Moreover, activation energies show the role of polymer layers separating aggregates even when they are percolated. Apart from simultaneous characterization over a broad frequency range up to local polymer and silanol dynamics, it is believed that such high-temperature BDS-measurements can thus be used to detect reorganizations in structurally-complex silica nanocomposites. Moreover, they should contribute to a better identification of dynamical processes via the described sensitivity to structure in such systems.