Biopolymers are abundant, renewable, and biodegradable resources. However, bio-based materials often require toughening additives, like (co)polymers or small plasticizing molecules. Plasticization is monitored via the glass transition temperature versus diluent content. To describe this, several thermodynamic models exist; nevertheless, most expressions are phenomenological and lead to over-parametrization. They also fail to describe the influence of sample history and the degree of miscibility via structure-property relationships. We propose a new model to deal with semi-compatible systems: the generalized mean model, which can classify diluent segregation or partitioning. When the constant k_GM is below unity, the addition of plasticizers has hardly any effect, and in some cases, even anti-plasticization is observed. On the other hand, when the k_GM is above unity, the system is highly plasticized even for a small addition of the plasticizer compound, which indicates that the plasticizer locally has a higher concentration. To showcase the model, we studied Na-alginate films with increasing sizes of sugar alcohols. Our k_GM analysis showed that blends have properties that depend on specific polymer interactions and morphological size effects. Finally, we also modeled other plasticized (bio)polymer systems from the literature, concluding that they all tend to have a heterogeneous nature.

Reported here is a 2D, interfacial microcompartmentalization strategy governed by 3D phase separation. In aqueous polyethylene glycol (PEG) solutions doped with biotinylated polymers, the polymers spontaneously accumulate in the interfacial layer between the oil-surfactant-water interface and the adjacent polymer phase. In aqueous two-phase systems, these polymers first accumulated in the interfacial layer separating two polymer solutions and then selectively migrated to the oil-PEG interfacial layer. By using polymers with varying photopolymerizable groups and crosslinking rates, kinetic control and capture of spatial organisation in a variety of compartmentalized macroscopic structures, without the need of creating barrier layers, was achieved. This selective interfacial accumulation provides an extension of 3D phase separation towards synthetic compartmentalization, and is also relevant for understanding intracellular organisation.

Magnetic field effects can provide a handle on steering chemical reactions and manipulating yields. The presence of a magnetic field can influence the energy levels of the active species by interacting with their spin states. Here we demonstrate the effect of a magnetic field on the electrocatalytic processes taking place on platinum-based nanoparticles in fuel cell conditions. We have identified a shift in the potentials representing hydrogen adsorption and desorption, present in all measurements recorded in the presence of a magnetic field. We argue that the changes in electrochemical behavior are a result of the interactions between the magnetic field and the unpaired spin states of hydrogen.

We report on the effect of lattice strain in three different types of core-shell electrocatalyst particles on their catalytic activity towards the oxygen reduction reaction. We decouple the changes in catalytic activity with respect to a geometrical and an energetic contribution, both of electronic origin.

We report on the thermal, electrical, and mechanical properties of alginate biopolymer nanocomposites prepared by solution casting with various amounts of graphene oxide (GO) or reduced GO (rGO). Our data shows that the thermal stability of alginate nanocomposites can be improved by the introduction of cross-linking through divalent metal cations, albeit that under these conditions little influence by the amount of rGO remains. On the other hand, the electrical conductivity of divalent metal ion cross-linked-rGO improves approximately 10 orders of magnitude with increasing weight fraction of rGO, whereas it declines for sodium alginate-GO composites. In addition, storage moduli and glass to rubber transition temperatures show strong composition dependence as a consequence of complex interactions of the ions with both polymer and filler. We propose a mechanical model that allows for the accurate prediction of reinforcement by GO sheets in sodium alginate-GO composites taking into account the orientational order of the sheets. Creep tests reveal the complex nature of multiple stress relaxation mechanisms in the nanocomposites although the stretched exponential Burgers' model accurately describes short time creep compliance.

The water sorption and diffusion in (reduced) graphene oxide-alginate composites of various compositions is analyzed. Water sorption of sodium alginate can be significantly reduced by the inclusion of graphene oxide sheets due to the formation of an extensive hydrogen bonding network between oxygenated groups. Crosslinking alginate with divalent metal ions and the presence of reduced graphene oxide can further improve the swelling resistance due to the strong interactions between metal ions, alginate, and filler sheets. Depending on conditions and composition, the overall water barrier properties of alginate composites improve upon (reduced) graphene oxide filling, making them attractive for moisture barrier coating applications. Water sorption kinetics in all alginate composites indicate a non-Fickian diffusion process that can be accurately described by the Variable Surface Concentration model. In addition, the water barrier properties of sodium alginate-graphene oxide composites can be adequately predicted using a simple model that takes the orientational order of filler sheets and their effective aspect ratio into account. (Figure presented.).