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For the first time, reversible covalent urethane units are used for the design of new self-healing polymers. For this purpose, an electron-poor diol was synthesized and utilized as crosslinker to create a dynamic polymer network. Therefore, the diol, butyl methacrylate as well as 2-isocyanato ethyl methacrylate are intermixed and photo-polymerized in a bone-shaped PTFE mold. The resulting test specimens are characterized by DSC, TGA and DMTA and the self-healing behavior is studied using tensile tests. Thereby, healing efficiencies of up to 85% could be reached while the material exhibits good mechanical properties with high E-moduli. Additionally, the self-healing mechanism, which is based on exchange reactions of the reversible urethane moieties, is investigated by Raman as well as temperature dependent IR measurements.

An experimental method for determining solid/liquid interfacial energies of alloys is presented. Spherical intermetallic particles of Al2Cu with diameters down to 50 nm were generated as ”divorced eutectic” in an initially homogeneous solid solution of 4 wt% Cu in Al by short-term annealing (t

The incorporation of metal complexes into polymers leads to functional materials; whereas, the properties of polymers – easy processability, light weight or the adjustable molar mass – and those of metal complexes – optical properties, catalytic activity or biomedical potential – can be combined. Through the years, various different applications have been developed, depending on the needs of current techniques and society. Thus, advanced applications enabled by metallopolymers, include areas: like self-assembly, stimuli-responsive behavior, catalysis, optics, self-healing, shape-memory as well as biomedicine and further potential applications can be expected. This review will summarize and discuss these applications as well as how the interactions of metal complexes and polymers enable them.

The scratch healing behavior of different polymers based on reversible interactions was investigated. For this purpose, scratches were induced via femtosecond laser ablation and were analyzed using laser-scanning microscopy. The healing process was monitored over time and the residual scratch volume was studied. Thus, healing kinetics of different self-healing polymers were obtained revealing a new three step-healing process. An initial time is required in order to start the crack closure behavior. Afterwards, a fast healing behavior followed by a final slow healing period could be observed. Consequently, this study discloses significant insights into the time-dependent healing behavior of polymeric materials.

Self-healing polymers based on the novel damage management concept were introduced several years ago. Since then different concepts have been successfully developed. However, the analysis and characterization of the self-healing process represents still a significant challenge, in particular for the quantification of scratch healing. Consequently, the comparability of the reported healing efficiencies of different polymers (materials) is often not provided. Within the variety of different characterization methods, different parameters like defect-area, length and width are utilized for the determination of the healing efficiency; however, the precise quantification is still problematic. For this reason, the present study focuses on two different methods, the mechanical analysis with the scratch tester MST3 and the optical analysis using laser scanning microscopy (LSM). For this purpose, a previously reported metallopolymer was damaged mechanically with an indenter and optically with a laser, respectively. Both types of defects were analyzed with the two characterization methods. By this manner, 3D images of the defects could also be obtained. The step-wise healing enabled a detailed analysis of the healing behavior of the polymer. Noteworthy, the optical analysis provided a high comparability enabling a precise quantification of the self-healing efficiency. The user-independent evaluation is crucial. As a consequence, a MATLAB® script was developed, which processes the data of the LSM measurements. Hereby, the data set and the microscope image are processed simultaneously and provide a combined result leading finally to the visualization (3D image) and quantification of the healing process.