The ongoing digitalization is rapidly changing and will further revolutionize all parts of life. This statement is currently omnipresent in the media as well as in the scientific community; however, the exact consequences of the proceeding digitalization for the field of materials science in general and the way research will be performed in the future are still unclear. There are first promising examples featuring the potential to change discovery and development approaches toward new materials. Nevertheless, a wide range of open questions have to be solved in order to enable the so‐called digital‐supported material research. The current state‐of‐the‐art, the present and future challenges, as well as the resulting perspectives for materials science are described.

In this work, we present a new strategy to engineer novel self-healing ionomers, namely, zwitterionic polymers, and a comprehensive analysis of their mechanical, viscoelastic, and scratch-healing properties. This new method enables reproducible damage of the polymer surfaces, calculation of the scratch volume through tactile profile scans, and quantification of the self-healing efficiency. Based on the results of the scratch tests and complementary rheology, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and hardness tests, new trends, and structure-property relationships can be identified.

The automated dialysis of polymers in synthetic robots is described as a first approach for the purification of polymers using an automated protocol. For this purpose, a dialysis apparatus was installed within a synthesis robot. Therein, the polymer solution could be transferred automatically into the dialysis tube. Afterwards, a permanent running dialysis could be started, enabling the removal of residual monomer. Purification efficiency was studied using chromatography and NMR spectroscopy, showing that the automated dialysis requires less solvent and is faster compared to the classical manual approach.

The supramolecular halogen bonding (XB) is utilized for the first time for the preparation of shape‐memory polymers. For this purpose, an iodotriazole‐based bidentate XB donor featuring a methacrylamide is synthesized. Free radical polymerization of the XB donor monomer together with butyl methacrylate, triethylene glycole dimethacrylate, and methacrylic acid results in covalently cross‐linked polymer networks bearing both, halogen bond acceptors and donors, in their side chains. While the reversible halogen bond interactions can act as switching unit, the required stable phase of the shape‐memory polymers is formed by covalent cross‐links. The successful formation of the supramolecular cross‐links is proven via Fourier‐transform Raman spectroscopy. Furthermore, the thermal properties are investigated via differential scanning calorimetry and thermo gravimetric analysis. Thermo‐mechanical analysis reveals excellent shape‐memory abilities with fixity rates above 95% and recovery rates up to 99%. Moreover, it is possible to 3D‐print this kind of material exhibiting the ability to recover its shape within a few seconds at 130 °C.

Particle sizes represent one of the key factors influencing the usability and specific targeting of nanoparticles in medical applications such as vectors for drug or gene therapy. A multi-layered graph convolutional network combined with a fully connected neuronal network is presented for the prediction of the size of nanoparticles based only on the polymer structure, the degree of polymerization, and the formulation parameters. The model is capable of predicting particle sizes obtained by nanoprecipitation of different poly(methacrylates). This includes polymers the network has not been trained with, indicating the high potential for generalizability of the model. By utilizing this model, a significant amount of time and resources can be saved in formulation optimization without extensive primary testing of material properties.

Online NMR measurements are introduced in the current study as a new analytical setup for investigation of the oxymethylene dimethyl ether (OME) synthesis. For the validation of the setup, the newly established method is compared with state‐of‐the‐art gas chromatographic analysis. Afterwards, the influence of different parameters, such as temperature, catalyst concentration and catalyst type on the OME fuel formation based on trioxane and dimethoxymethane is investigated. As catalysts, AmberlystTM 15 (A15) and trifluoromethanesulfonic acid (TfOH) are utilized. A kinetic model is applied to describe the reaction in more detail. Based on these results, the activation energy (A15: 48.0 kJ mol−1 and TfOH: 72.3 kJ mol−1) and the order in catalyst (A15: 1.1 and TfOH: 1.3) are calculated and discussed.

The self-assembly of amphiphilic polymers into worm-like micelles represents a versatile approach to create hydrogels, where interactions and functionalities are widely customizable by the chemistry of the hydrophilic block. However, processing options for such gels remain a bottleneck as fragmentation is often irreversible due to the limited dynamics of the assemblies. We demonstrate here that shear-thinning hydrogels can reversibly be formed by amphiphilic polymers, which assemble into supramolecular polymer nanofibers due to additional directing hydrogen bonds. The addition of bifunctional cross-linkers resulted in robust gels, which feature a surprisingly strong shear-thinning character but recover fully in the absence of shear stress despite the lack of a dynamic exchange of individual building blocks. In addition to increasing the concentration, the strength of the gel can be tuned by varying the content or the length of the bivalent cross-linker. Low viscosities under shear load and the rapid recovery (<5 s) after relief of the strain facilitates an effortless extrusion through even thin needles and subsequent formation of self-supporting structures in a printing process. The polymer covered fiber structure further bestows the gels with an excellent stability in various conditions and good biocompatibility while minimizing cell adhesion. The mesh sizes of the gel allow even large macromolecules to diffuse, but retardation is nevertheless observed for small molecules due to the dense polymer brush structure. This unique set of properties renders these polymer fiber hydrogels a versatile and easily processable scaffold for future applications, for example as an adaptable cell scaffold or injectable drug depots.

An automated synthesis protocol is developed for the synthesis of block copolymers in a multi-step approach in a fully automated manner. For this purpose, an automated dialysis setup is combined with robot-based synthesis protocols. Consequently, several block copolymerizations are executed completely automated and compared to the respective manual synthesis. As a result, this study opens up the field of autonomous multi-step reactions without any human interactions.