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Paper des Monats
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The microstructure of an apatite-wollastonite (code name AP40) glass-ceramic is analyzed in this study by combining 2D microscopy, phase analysis, X-ray absorption and synchrotron X-ray refraction computed tomography (XCT and SXRCT, respectively). It is shown that this combination provides a useful toolbox to characterize the global microstructure in a wide scale range, from sub-micrometer to millimeter. The material displays a complex microstructure comprising a glassy matrix with embedded fluorapatite and wollastonite small crystals. In this matrix, large (up to 200 μm) spike-shaped structures are distributed. Such microstructural features are oriented around a central sphere, thereby forming a structure resembling a sea urchin. A unique feature of SXRCT, in contrast to XCT, is that internal interfaces are visualized; this allows one to show the 3D distribution of these urchins with exceptionally good contrast. Furthermore, it is revealed that the spike-shaped structures are not single crystals, but rather composed of sub-micrometric crystals, which are identified as fluorapatite and diopside phases by SEM-EDX analysis.
Aero-engine turbine disks are safety-relevant components which are operated under high thermal and mechanical stress conditions. The actual part qualification and certification procedures make use of spin-tests conducted on production-similar disks. While these tests provide, on the one hand, a reliable definition of the critical conditions for real components, on the other hand they represent a relevant cost item for engine manufacturers. The aim of this work is to present two alternative burst speed assessment methods under development based on the Failure Assessment Diagram (FAD) and a global stability criterion, respectively. In the scope of the fracture mechanics assessment, the failure modes hoop-burst and rim-peeling are investigated with semicircular surface cracks modelled at the critical regions on the turbine disk. The comparison of the predicted critical rotational speed shows good agreement between the assessment methods.
To improve the predictive capability of long-term stress relaxation of elastomers during thermo-oxidative ageing, a method to separate reversible and irreversible processes was adopted.
The separation is performed through the analysis of compression set after tempering. On the Basis of this separation, a numerical model for long-term stress relaxation during homogeneous ageing is proposed. The model consists of an additive contribution of physical and chemical relaxation.
Computer simulations of compression stress relaxation were performed for long ageing times and the results were validated with the Arrhenius treatment, the kinetic study and the time-temperature superposition technique based on experimental data. For chemical relaxation, two decay functions are introduced each with an activation energy and a degradative process. The first process with the lower activation energy dominates at lower ageing times, while the second one with the higher activation energy at longer ageing times. A degradation-rate based model for the evolution of each process and ist contribution to the total system during homogeneous ageing is proposed. The main advantage of the model is the possibility to quickly validate the interpolation at lower temperatures within the range of slower chemical processes without forcing a straight-line extrapolation.
Large-scale nanoimprinted metasurfaces based on silicon photonic crystal slabs were produced and coated with a NaYF4:Yb3+/Er3+ upconversion nanoparticle (UCNP) layer. UCNPs on these metasurfaces yield a more than 500-fold enhanced upconversion emission compared to UCNPs on planar surfaces. It is also demonstrated how the optical response of the UCNPs can be used to estimate the local field energy in the coating layer. Optical simulations using the finite element method validate the experimental results and the calculated spatial three-dimensional field Energy distribution helps us to understand the emission enhancement mechanism of the UCNPs closely attached to the metasurface. In addition, we analyzed the spectral shifts of the resonances for uncoated and coated metasurfaces and metasurfaces submerged in water to enable a prediction of the optimum layer thicknesses for different excitation wavelengths, paving the way to applications such as electromagnetic field sensors or bioassays.
Offshore wind turbines (OWT) are a major goal of the energy strategy of Germany encompassing the increase of the installed wind power. OWT components are manufactured from welded steel plates with thicknesses up to 200 mm. The underlying standards and technical recommendations for construction of OWTs encompass specifications of so-called minimum waiting time (MWT) before non-destructive testing of the weld joints is allowed. Reason is the increased risk of time-delayed hydrogen assisted cold cracking as hydrogen diffusion is very slow due to the very thick plates. The strict consideration of those long MWT up to 48 h during the construction of OWTs leads to significant financial burden (like disproportionately high costs for installer ships as well as storage problems (onshore)). In this study, weld joints made of S355 ML were examined in comparison with the offshore steel grade S460 G2+M. The aim was to optimize, i.e., reduce, the MWT before NDT considering varied heat input, hydrogen concentration and using self-restraint weld tests. This would significantly reduce the manufacturing time and costs of OWT construction. To quantify the necessary delay time until hydrogen-assisted cold cracks appear, acoustic emission analysis was applied directly after welding for at least 48 h.
Wire arc additive manufacturing (WAAM) enables the efficient production of weight-optimized modern engineering structures. Further increases in efficiency can be achieved by using high-strength structural steels. Commercial welding consumables for WAAM are already available on the market. Lack of knowledge and guidelines regarding welding residual stress and component safety during production and operation leads to severely limited use for industry applications. The sensitive microstructure of high-strength steels carries a high risk of cold cracking; therefore, residual stresses play a crucial role. For this reason, the influences of the material, the WAAM process, and the design on the formation of residual stresses and the risk of cold cracking are being investigated. The material used has a yield strength of over 800 MPa. This strength is adjusted via solid solution strengthening and a martensitic phase transformation. The volume expansion associated with martensite formation has a significant influence on the residual stresses. The focus of the present investigation is on the additive welding parameters and component design on their influence on hardness and residual stresses, which are analyzed by means of X-ray diffraction (XRD). Reference specimens (hollow cuboids) are welded fully automated with a systematic variation of heat control and design. Welding parameters and AM geometry are correlated with the resulting microstructure, hardness, and residual stress state. Increased heat input leads to lower tensile residual stresses which causes unfavorable microstructure and mechanical properties. The component design affects heat dissipation conditions and the intensity of restraint during welding and has a significant influence on the residual stress.
Grain boundaries (GBs)’s role in determining the functional and mechanical properties of polycrystalline materials is inscribed in both their structure and chemistry. Upon solute segregation, the structure and composition of a GB can change concurrently. We study the co-evolution of GB’s structure and segregation by enhancing the density-based phase-field model to account for the in-plane structural variations in the GB. Significant mutual coupling is revealed between the GB’s chemical and structural states during Mn segregation in Fe-Mn alloys. We found that the structural degrees of freedom in a GB (the ability of the GB structure to respond to the chemical variation) amplifies Mn segregation transition, even when the GB structure stays unchanged. When the GB structure is not uniform, that is the usual case, the coupling between GB structure and segregation evolution also enables the spinodally formed low- and high-Mn phases (upon segregation transition) to co-exist within the GB region. These findings explain the stabilizing mechanism of pronounced interfacial segregation fluctuations, experimentally evidenced in Fe-Mn GBs, and give new insights on the structural sensitivity of GBs’ segregation phenomena and the mutual chemo-structural interplay.
This paper presents a novel approach for developing sustainable building materials through Sequential Learning. Data sets with a total of 1367 formulations of different types of alkali-activated building materials, including fly ash and blast furnace slag-based concrete and their respective compressive strength and CO2-footprint, were compiled from the literature to develop and evaluate this approach. Utilizing this data, a comprehensive computational study was undertaken to evaluate the efficacy of the proposed material design methodologies, simulating laboratory conditions reflective of real-world scenarios. The results indicate a significant reduction in development time and lower research costs enabled through predictions with machine learning. This work challenges common practices in data-driven materials development for building materials. Our results show, training data required for data-driven design may be much less than commonly suggested. Further, it is more important to establish a practical design framework than to choose more accurate models. This approach can be immediately implemented into practical applications and can be translated into significant advances in sustainable building materials development.
The application and benefits of Semantic Web Technologies (SWT) for managing, sharing, and (re-)using of research data are demonstrated in implementations in the field of Materials Science and Engineering (MSE). However, a compilation and classification are needed to fully recognize the scattered published works with its unique added values. Here, the primary use of SWT at the interface with MSE is identified using specifically created categories. This overview highlights promising opportunities for the application of SWT to MSE, such as enhancing the quality of experimental processes, enriching data with contextual information in knowledge graphs, or using ontologies to perform specific queries on semantically structured data. While interdisciplinary work between the two fields is still in its early stages, a great need is identified to facilitate access for nonexperts and develop and provide user-friendly tools and workflows. The full potential of SWT can best be achieved in the long term by the broad acceptance and active participation of the MSE community. In perspective, these technological solutions will advance the field of MSE by making data FAIR. Data-driven approaches will benefit from these data structures and their connections to catalyze knowledge generation in MSE.
Fused filament fabrication (FFF) is a material extrusion-based technique often used in desktop 3D printers. Polymeric filaments are melted and are extruded through a heated nozzle to form a 3D object in layers. The extruder temperature is therefore a key parameter for a successful print job but also one of the main emission driving factors as harmful pollutants (e.g., ultrafine particles) are formed by thermal polymer degradation. The awareness of potential health risks has increased the number of emission studies in the past years. However, studies usually refer their calculated emission data to the printer set extruder temperature for comparison purposes. In this study, we used a thermocouple and an infrared camera to measure the actual extruder temperature and found significant temperature deviations to the displayed set temperature among printer models. Our result shows that printing the same filament feedstocks with three different printer models and with identical printer set temperature resulted in a variation in particle emission of around two orders of magnitude. A temperature adjustment has reduced the variation to approx. one order of magnitude. Thus, it is necessary to refer the measured emission data to the actual extruder temperature as it poses a more accurate comparison parameter for evaluation of the indoor air quality in user scenarios or for health risk assessments.