Veröffentlichungen und Vorträge

The objective of this work was to measure and correlate the degree of conversion (DC), mechanical properties and monomer elution from self-, dual- and light-cured core composites. Five samples of each of the following materials were prepared for each test: Clearfil (Core, Photo Core, Automix), Bisco (Core-Flo, Light-Core and Bis-Core). DC was determined using FTIR, compressive and flexural strength and modulus of elasticity using a universal testing machine and microhardness using Vickers hardness. Elution was measured using HPLC. One-way ANOVA with Tukey’s post-test and Pearson's correlation were used to statistically analyze the data. DC of Clearfil-Dual (70.1%) and Clerafil-Photo (66.8%) were higher than Clearfil-Self (55.4%) and all Bisco materials (51.4-55.3%). Flexural strength of Clearfilwas higher than that of Bisco composites. The Microhardness of Clearfil-Dual (119.8VHN) and Clearfil-Photo (118.0VHN) were higher compared to other materials. The greatest elution was detected from self-cured materials. DC positively correlated to microhardness and compressive/flexural strength and negatively to BisGMA elution. Clearfil-Photo and Automix showed higher conversion, lower monomer elution and, generally, better mechanical properties. Self-cured composites should not be recommended for routine clinical use as their performance was inferior to dual- and light-cured composites. Microhardness may be used as an indicator of elution.

It is common knowledge that molecular energy level offsets of a type II heterojunction formed at the donor-acceptor interface are considered to be the driving force for photoinduced charge transfer in organic solar cells. Usually, these offsets - present between molecular energy levels of the donor and acceptor - are obtained via cyclic voltammetry (CV) measurements of organic semiconductors cast in a film or dissolved in solution. Simply transferring such determined energy levels from solution or film of single materials to blend films may be obviously limited and not be possible in full generality. Herein, we report various cases of material combinations in which novel non-fullerene acceptors did not yield successful charge transfer, although energy levels obtained by CV on constituting single materials indicate a type II heterojunction. Whilst the integer charge transfer (ICT) model provides one explanation for a relative rise of molecular energy levels of acceptors, further details and other cases have not been studied so far in great detail. By applying energy-resolved electrochemical impedance spectroscopy (ER-EIS) on several donor-acceptor combinations, a Fano-like resonance feature associated with a distinctive molecular energy level of the acceptor as well as various relative molecular energy level shifts of different kinds could be observed. By analyzing ER-EIS and absorption spectra, not only the exciton binding energy within single materials could be determined, but also the commonly unknown binding energy of the CT state with regard to the joint density of states (jDOS) of the effective semiconductor. The latter is defined by transitions between the highest occupied molecular orbitals (HOMO) of the donor and the lowest unoccupied molecular orbitals (LUMO) of the acceptor. Using this technique among others, we identified cases in which charge generation may occur either via uphill or by downhill processes between the charge transfer exciton and the electronic gap of the effective semiconductor. Exceptionally high CT-exciton binding energies and thus low charge generation yields were obtained for a case in which the donor and acceptor yielded a too intimate blend morphology, indicating π-π stacking as a potential cause for unfavorable molecular energy level alignment.

Friction stir welding (FSW) has developed into a reliable and increasing used industrial joining technology. Various tool configurations can be used for FSW, each of which has advantages and challenges. State-of-the-art FSW employs various tool configurations, including the conventional, the stationary shoulder, and the dual-rotational configuration which is characterized by separate control of shoulder and probe. In this study, an innovative method to combine various tool configurations was developed by a novel FSW spindle stack construction. With an additional servomotor, existing FSW systems can be extended by separate control of shoulder and probe so that varying rotational speeds and rotational directions can be set. This allows enhanced possibilities (a) to adjust frictional heat generation and (b) to apply several tool configurations. The main advantages of this enhanced type of FSW are demonstrated in three ways: increased weld penetration depth, reduction of undesirable machine vibrations, and the combination of varying tool configurations such as stationary shoulder and conventional FSW. The investigations were carried out with 2-mm EN AA 5754 H22 sheets and performed on a robotized FSW setup.

This research presents a hybrid approach to generate sample data for future machine learning applications for the prediction of mechanical properties in directed energy deposition-arc (DED-Arc) using the GMAW process. DED-Arc is an additive manufacturing process which offers a cost-effective way to generate 3D metal parts, due to its high deposition rate of up to 8 kg/h. The mechanical properties additively manufactured wall structures made of the filler material G4Si1 (ER70 S-6) are shown in dependency of the t8/5 cooling time. The numerical simulation is used to link the process parameters and geometrical features to a specific t8/5 cooling time. With an input of average welding power, welding speed and geometrical features such as wall thickness, layer height and heat source size a specific temperature field can be calculated for each iteration in the simulated welding process. This novel approach allows to generate large, artificial data sets as training data for machine learning methods by combining experimental results to generate a regression equation based on the experimentally measured t8/5 cooling time. Therefore, using the regression equations in combination with numerically calculated t8/5 cooling times an accurate prediction of the mechanical properties was possible in this research with an error of only 2.6%. Thus, a small set of experimentally generated data set allows to achieve regression equations which enable a precise prediction of mechanical properties. Moreover, the validated numerical welding simulation model was suitable to achieve an accurate calculation of the t8/5 cooling time, with an error of only 0.3%.