5 Werkstofftechnik
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Efforts towards digitalization in the material science and technology community have enhanced in the last years. In 2019 the German digitalization initiative platform „MaterialDigital“1 (MD) has been started. Numerous projects concerning digitalization, including the copper related project „KupferDigital“ (copper digital) have been initiated under the umbrella of MD. The initiative strives to
address numerous issues concerning data access, exchange, security, provenance and sovereignty. Heterogeneous data origin, storage and evaluation often result in problems concerning comparability and reproducibility of scientific and technological results. In many cases material data are recorded, but the methods of testing are insufficiently described, or such information is not communicated along with the raw data. The material data can also have numerous different formats such as paper printouts, pdfs, excel sheets or csv-files. Hence, gathering and integrating material data from different sources is challenging for potential users like materials scientists and engineers, especially if there are contradictory data where the reasons for contradictions is not clear due their vague description. In order to address these problems, data should comply to the so called „FAIR“ principle which calls for data to be findable, accessible, interoperable, and reusable (FAIR)2 and hence be accessible via so-called decentralized but interconnected data spaces. By using knowledge representation withontologies, data can be enriched with meaning and the methods of the testing procedures can be accurately provided. In this presentation we want to introduce our approach to such knowledge representation based on a high-throughput alloy development process for Cu-based alloys³ along with characterization techniques such as hardness testing and microstructural characterization (e.g. EBSD – Electron Backscattered Diffraction).
At high temperatures and in harsh environments ceramic springs are often superior to metallic ones and allow for innovative solutions. A further application was proposed by using ceramic springs as capacitive force sensor. Lower and upper coil surfaces are coated by electrically conducting layers. Deformation of such spring results in a change of capacity. Sensor application calls for helical springs with rectangular cross-section, a linear stress-strain characteristic over entire deformation range and low manufacturing tolerances relating to inner and outer diameter, coil cross section and spring pitch. Furthermore, complex spring design with integrated connecting elements has to be realized.
Alumina, zirconia (Y-TZP) and silicon nitride springs were produced by hard machining starting from sintered hollow cylinders. After external and internal cylindrical grinding the hollow cylinders were filled with hard wax, followed by multi-stage cutting of spring coils with custom-made cutting discs. Finally, hard wax was removed by melting and burnout. Best surface and edge qualities of springs were reached using Y-TZP material and hot isostatic pressed alumina. Y-TZP springs produced with material-specifically selected cutting discs and optimized process parameters show sharp coil edges without spallings and mean roughness values of inner surfaces < 0.2 μm. Manufacturing tolerances of spring diameters, spring pitch, height and width of coil cross section are in the range of ± 10 microns. Good reproducibility of spring geometry by optimized hard machining technology allows for production of Y-TZP springs with spring constants differing less than ± 1 % within a series.
According to DIN 2090 spring constant for rectangular coil cross section is proportional to the square of height and width of coil cross section and indirectly proportional to number of active coils and to the cube of the mean spring diameter. Hence, spring constants can be tailored over a range of many orders of magnitude by changing the spring dimensions. Good agreement was reached between calculated target spring constants and measured values on produced springs.
Alumina and zirconia springs were characterized relating to deformation behavior under dynamic compression load with various deformation speeds and under static tensile loads over long periods of time. Contrary to alumina springs, a non-linear stress-strain behavior of TZP springs was proved in both test series. It is supposed, that pseudoelasticity caused by stress-induced transformation of tetragonal to monoclinic phase is responsible for this special feature of TZP springs. Therefore, TZP material cannot be used for capacitive spring sensors.
Thermoelectric generators can be used as energy harvesters for sensor applications. Multilayer thermoelectric generators (ML-TEGs) are a promising alternative to conventional π-type generators due to their high filling factor, high capability of automated production and the texturing potential during the production process. Calcium cobaltite is a promising thermoelectric oxide (p-type) with highly anisotropic properties. The following study shows the development of a textured unileg ML-TEG using ceramic multilayer technology.
Tape-casting and pressure assisted sintering are applied to fabricate textured calcium cobaltite. Compared to conventional sintering, pressure assisted sintering increases the strength by the factor 10. Thermoelectric properties can be tuned either towards maximum power factor or towards maximum figure of merit depending on the pressure level.
As electrical insulation material, a screen-printable glass-ceramic with high resistivity and adapted coefficient of thermal expansion is developed. From various commercial pastes a metallization with low contact resistance is chosen. The unileg ML-TEG is co-fired in one single step. The demonstrators reach 80% of the simulated output power and the power output is highly reproducible between the different demonstrators (99%). These results provide the first proof-of-concept for fabricating co-fired multilayer generators based on textured calcium cobaltite with high power factor, high density, and high strength.
Thermal spraying provides a rapid method for additive deposition of various ceramics as electrical insulation in applications where polymers are not suitable. New applications in complex shaped additive manufactured metal parts are emerging for example in large scale electrical devices. Microstructural and dielectric evaluation of coatings is crucial to the employment of such free-form processes. The properties and microstructure of the plasma sprayed alumina coatings are compared with dense reference samples of the same powder produced by spark plasma sintering (SPS). To obtain dense bulk samples from the coarse alumina powder for spray coating, SPS is used.
Samples are fabricated by atmospheric plasma spraying (APS) of commercially available alumina powder (d50 = 33 µm) on copper substrates and by SPS of the same powder. Microstructure and porosity were analyzed by optical microscopy and scanning electron microscopy (SEM). Phase compositions were determined by X-ray diffraction (XRD). Dielectric properties such as DC resistance, dielectric strength, dielectric loss, and relative permittivity were determined according to the standards. The microstructure and dielectric properties of the coating and bulk material are compared to assess whether the coating is suitable for use in electrical insulation application.
In this presentation, the results of the determination of the diffraction and single-crystal elastic constants of laser powder bed fused Inconel 718 are presented. The analysis is based on high-energy synchrotron diffraction experiments performed at the Deutsches Elektronen-Synchrotron. It is shown that the characteristic microstructure of laser powder bed fused Inconel 718 impacts the elastic anisotropy and therefore the diffraction and single-crystal elastic constants. Finally, the consequences on the diffraction-based residual stress determination of laser powder bed fused Inconel 718 are discussed.
Laser powder bed fusion (PBF-LB/M) of metallic alloys is a layer-wise additive manufacturing process that provides significant scope for more efficient designs of components, benefiting performance and weight, leading to efficiency improvements for various sectors of industry. However, to benefit from these design freedoms, knowledge of the high produced induced residual stress and mechanical property anisotropy associated with the unique microstructures is critical. X-ray and neutron diffraction are considered the benchmark for non-destructive characterization of surface and bulk internal residual stress. The latter, characterized by the high penetration power in most engineering alloys, allows for the use of a diffraction angle close to 90° enabling a near cubic sampling volume to be specified. However, the complex microstructures of columnar growth with inherent crystallographic texture typically produced during PBF-LB/M of metallics present significant challenges to the assumptions typically required for time efficient determination of residual stress. These challenges include the selection of an appropriate set of diffraction elastic constants and a representative lattice plane suitable for residual stress analysis. In this contribution, the selection of a suitable lattice plane family for residual stress analysis is explored. Furthermore, the determination of an appropriate set of diffraction and single-crystal elastic constants depending on the underlying microstructure is addressed.
In-situ loading experiments have been performed at the Swiss Spallation Neutron Source with the main scope to study the deformation behaviour of laser powder bed fused Inconel 718. Cylindrical tensile bars have been subjected to an increasing mechanical load. At pre-defined steps, neutron diffraction data has been collected. After reaching the yield limit, unloads have been performed to study the accumulation of intergranular strain among various lattice plane families.
Glasses stand out by their wide and continuously tunable chemical composition and large variety of unique shaping techniques making them a key component of modern high technologies. Glass development, however, is still often too cost-, time- and energy-intensive. The use of robotic melting systems embedded in an ontology-based digital environment is intended to overcome these problems in future.
For this purpose, a robotic high throughput glass melting system is equipped with novel inline sensors for process monitoring, machine learning (ML)-based, adaptive algorithms for process monitoring and optimization, novel tools for high throughput glass analysis and ML-based algorithms for glass design. This includes software tools for data mining as well as property and process modelling. The presentation provides an overview of how all these tools merge into a digital infrastructure and illustrates their usability using examples.
All infrastructural parts were developed by a consortium consisting of the Fraunhofer ISC in Würzburg, the Friedrich-Schiller-University Jena (OSIM), the Clausthal University of Technology (INW) and the Federal Institute for Materials Research and Testing (BAM, Division Glasses) as part of a joint project of the German research initiative MaterialDigital.