Within this paper, we are dealing with a mixture of thermoplastic polymer that is filled with inorganic fillers at high concentrations up to 60 vol.%. A high number of particles in the compound can substantially change the rheological behaviour of the composite and can lead to problems during processing in the molten state. The rheological behaviour of highly filled materials is complex and influenced by many interrelated factors. In the present investigation, we considered four different spherical materials: steel, aluminium alloy, titanium alloy and glass. Particles with similar particle size distribution were mixed with a binder system at different filling grades (30–60 vol.%). We showed that the rheological behaviour of highly filled materials is significantly dependent on the chemical interactions between the filler and matrix material. Moreover, it was shown that the changes of the particle shape and size during processing lead to unexpected rheological behaviour of composite materials as it was observed in the composites filled with glass beads that broke at high contents during processing.

The viscosity of feedstock materials is directly related to its processability during injection molding; therefore, being able to predict the viscosity of feedstock materials based on the individual properties of their components can greatly facilitate the formulation of these materials to tailor properties to improve their processability. Many empirical and semi-empirical models are available in the literature that can be used to predict the viscosity of polymeric blends and concentrated suspensions as a function of their formulation; these models can partly be used also for metal injection molding binders and feedstock materials. Among all available models, we made a narrow selection and used only simple models that do not require knowledge of molecular weight or density and have parameters with physical background. In this paper, we investigated the applicability of several of these models for two types of feedstock materials each one with different binder composition and powder loading. For each material, an optimal model was found, but each model was different; therefore, there is not a universal model that fits both materials investigated, which puts under question the underlying physical meaning of these models.

The ForMAX beamline at the MAX IV Laboratory provides multiscale and multimodal structural characterization of hierarchical materials in the nanometre to millimetre range by combining small- and wide-angle X-ray scattering with full-field microtomography. The modular design of the beamline is optimized for easy switching between different experimental modalities. The beamline has a special focus on the development of novel fibrous materials from forest resources, but it is also well suited for studies within, for example, food science and biomedical research.

Polyethylene based ionomers are demonstrated to feature a thermo‐mechanical and dielectric property portfolio that is comparable to cross‐linked polyethylene (XLPE), which may enable the design of more sustainable high voltage direct‐current (HVDC) power cables, a crucial component of future electricity grids that seamlessly integrate renewable sources of energy. A new type of ionomer is obtained via high‐pressure/high‐temperature free radical copolymerization of ethylene in the presence of small amounts of ion‐pair comonomers comprising amine terminated methacrylates and methacrylic acid. The synthesized ionomers feature a crystallinity, melting temperature, rubber plateau modulus and thermal conductivity like XLPE but remain melt‐processable. Moreover, the preparation of the ionomers is free of byproducts, which readily yields a highly insulating material with a low dielectric loss tangent and a low direct‐current (DC) electrical conductivity of 1 to 6·10⁻¹⁴ S m⁻¹ at 70 °C and an electric field of 30 kV mm⁻¹. Evidently, the investigated ionomers represent a promising alternative to XLPE‐based high voltage insulation, which may permit to ease the production as well as end‐of‐use recycling of HVDC power cables by combining the advantages of thermoset and thermoplastic materials while avoiding the formation of byproducts.

A facile novel approach of introducing dopamine and [2-(methacryloyloxy) ethyl] dimethyl-(3-sulfopropyl) ammonium hydroxide via dopamine-triggered in situ synthesis into gelatin hydrogels in the presence of ZnSO₄ is presented in this study. Remarkably, the resulting hydrogels showed 99.99 and 100% antibacterial efficiency against Gram-positive and Gram-negative bacteria, respectively, making them the highest performing surfaces in their class. Furthermore, the hydrogels showed adhesive properties, self-healing ability, antifreeze properties, electrical conductivity, fatigue resistance, and mechanical stability from -100 to 80 °C. The added multifunctional performance overcomes several disadvantages of gelatin-based hydrogels such as poor mechanical properties and limited thermostability. Overall, the newly developed hydrogels show significant potential for numerous biomedical applications, such as wearable monitoring sensors and antibacterial coatings.

The design of supramolecular hydrogels comprising aligned domains is important for the fabrication of biomimetic materials and applications in optoelectronics. One way to access such materials is by the self-assembly of small molecules into long fibres, which can be aligned using an external stimulus. Out-of-equilibrium supramolecular gels can also be designed, where pre-programmed changes of state can be induced by the addition of chemical fuels. Here we exploit these dynamic properties to form materials with aligned domains through a ‘forging’ approach: an external force is used to rearrange the underlying network from random to aligned fibres as the system undergoes a pre-programmed gel-to-sol-to-gel transition. We show that we can predictably organize the supramolecular fibres, leading to controllable formation of materials with aligned domains through a high degree of temporal control.