2018, Purtov, Julia, Verch, Andreas, Rogin, Peter, Hensel, René

Natural functional surfaces often rely on unique nano- and micropatterns. To mimic such surfaces successfully, patterning techniques are required that enable the fabrication of three-dimensional structures at the nanoscale. It has been reported that two-photon polymerization (TPP) is a suitable method for this. However, polymer structures fabricated by TPP often tend to shrink and to collapse during the fabrication process. In particular, delicate structures suffer from their insufficient mechanical stability against capillary forces which mainly arisein the fabrication process during the evaporation of the developer and rinsing liquids. Here, we report a modified development approach, which enables an additional UV-treatment to post cross-link created structures before they are dried. We tested our approach on nanopillar arrays and microscopic pillar structures mimicking the moth-eye and the gecko adhesives, respectively. Our results indicate a significant improvement of the me- chanical stability of the polymer structures, resulting in fewer defects and reduced shrinkage of the structures.

2016, Wahyuono, Ruri Agung, Schmidt, Christa, Dellith, Andrea, Dellith, Jan, Schulz, Martin, Seyring, Martin, Rettenmayr, Markus, Plentz, Jonathan, Dietzek, Benjamin

We have developed an efficient, low temperature, synthetic route for ZnO nanoflowers (NFs) as photoanode material. This alternative route yields small flowerlike nanostructures, built from densely self-assembled tip-ended rod structures. The obtained ZnO NFs possess a large bandgap of 3.27 - 3.39 eV, enabling the generation of an average open current voltage of 0.56 V. Additionally, they show a high internal light harvesting of 14.6•10-7A-mol-1. The growth mechanism and self-assembly of ZnO NFs were studied in detail by joint spectroscopic-TEM investigations. It is shown that the ZnO crystallite size increases with increasing annealing temperatures and that the stress and the improved crystallinity are induced by annealing and reduce the lattice strain and the dislocation density. The bandgaps of ZnO are affected by the lattice strain revealing an optimal region of lattice strain to gain high bandgap energies. The properties of the synthesized ZnO NFs are compared with other morphologies, i.e. ZnO spherical aggregates (SPs) and ZnO nanorods (NRs), and are tested as electrode materials in dye-sensitized solar cells.

2019, Kruppke, Iris, Scheffler, Christina, Simon, Frank, Hund, Rolf-Dieter, Cherif, Chokri

In this paper, the oxy-fluorination process and the influence of different concentrations of fluorine and oxygen in the gas phase on the physicochemical properties of polyacrylonitrile(PAN)-based carbon fibers are described. The properties of the treated carbon structures are determined by zeta potential and tensiometry measurements. In addition, changes in surface composition and morphology are investigated by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). Adhesion properties are characterized by the single fiber pull-out (SFPO) test. Furthermore, changes in intrinsic properties are described by means of tensile and density measurements. After a primary desizing effect by oxy-fluorination, an increased number of oxygen-containing surface functional groups could be detected, which led to more debonding work in SFPOs with an epoxy-based matrix. It was also shown that the polar surface energy grows with rising fluorine concentration in the reaction gas mixture. In addition, a minor increase of ~10% in the maximum strength of PAN-based carbon fibers is detected by single fiber tensile measurements after oxy-fluorination with a fluorine content of 5% in the reaction mixture.

2023, Samri, Manar, Thiemecke, Jonathan, Hensel, René, Arzt, Eduard

Bioinspired fibrillar adhesives have been proposed for novel gripping systems with enhanced scalability and resource efficiency. Here, we propose an in-situ optical monitoring system of the contact signatures, coupled with image processing and machine learning. Visual features were extracted from the contact signature images recorded at maximum compressive preload and after lifting a glass object. The algorithm was trained to cope with several degrees of misalignment and with unbalanced weight distributions by off-center gripping. The system allowed an assessment of the picking process for objects of various mass (200, 300, and 400 g). Several classifiers showed a high accuracy of about 90 % for successful prediction of attachment, depending on the mass of the object. The results promise improved reliability of handling objects, even in difficult situations.