5 Werkstofftechnik
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- 5 Werkstofftechnik (116)
- 5.1 Mikrostruktur Design und Degradation (33)
- 5.6 Glas (25)
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- 5.2 Metallische Hochtemperaturwerkstoffe (20)
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- 6 Materialchemie (15)
- 8 Zerstörungsfreie Prüfung (12)
- 8.5 Röntgenbildgebung (10)
- 1 Analytische Chemie; Referenzmaterialien (9)
Despite of the significant advances in additive manufacturing (AM) process optimization there is still a lack of experimental results and understanding regarding the mechanical behavior and its relationship with the microstructural features of AM-parts, especially in loading conditions typical for safety-relevant applications. Within the scope of the presented ongoing investigations, a basic microstructural characterization, tensile tests at room and elevated temperature (400°C) as well as a characterization of the fatigue behavior of additively manufactured Ti-6Al-4V in the low cycle fatigue regime are carried out in the as-built state. After failure, different techniques are used to describe the failure mechanisms of the specimens. The AM-Specimens are provided by the Fraunhofer institute for production systems and design technology and investigated at the BAM following the philosophy of the TF-Project AGIL.
The 5G technology promises real time data transmission for industrial processes, autonomous driving, virtual and augmented reality, E-health applications and many more. The Low Temperature Co-fired Ceramics (LTCC) technology is well suited for the manufacturing of microelectronic components for such applications. Still, improvement of the technology such as further miniaturization is required. This study focuses on the characterization of inner metallization of LTCC multilayer modules, especially on the vertical interconnect access (VIA). Critical considerations for this characterization are delamination, pore clustering in and at the edge of the VIA, deformation, and stacking offset. A LTCC multilayer consisting of a glassy crystalline matrix with silver based VIAs was investigated by synchrotron x-ray tomography (CT). The aim of this study is to propose a multitude of structural characteristic values to maximize the information gained from the available dataset. Data analysis has been done with the open source software ImageJ as well as several additional plugins. The high-resolution CT data was evaluated through 2D slices for accessibility reasons. The segmentation of all 2000 slices to assess the different regions e.g. pores, silver and glass ceramic was done by a supervised machine learning algorithm. A quantitative evaluation of shape, deformation, and porosity of the VIA with respect to its dimensions is presented and the suitability of the characterization approach is assessed.
The introduction of the 5G technology and automotive radar applications moving into higher frequency ranges trigger further miniaturization of LTCC technology (low temperature co-fired ceramics). To assess dimensional tolerances of inner metal structures of an industrially produced LTCC multilayer, computer tomography (CT) scans were evaluated by machine learning segmentation.
The tested multilayer consists of several layers of a glass ceramic substrate with low resistance silver-based vertical interconnect access (VIA). The VIAs are punched into the LTCC green tape and then filled with silver-based pastes before stacking and sintering. These geometries must abide by strict tolerance requirements to ensure the high frequency properties.
This poster presents a method to extract shape and size specific data from these VIAs. For this purpose, 4 measurements, each containing 3 to 4 samples, were segmented using the trainable WEKA segmentation, a non-commercial machine learning tool. The dimensional stability of the VIA can be evaluated regarding the edge-displacement as well as the cross-sectional area. Deviation from the ideal tubular shape is best measured by aspect ratio of each individual layer. The herein described method allows for a fast and semi-automatic analysis of considerable amount of structural data. This data can then be quantified by shape descriptors to illustrate 3-dimensional information in a concise manner. Inter alia, a 45 % periodical change of cross-sectional area is demonstrated.
Chromia forming high alloyed ferritic-austenitic steels are being used as boiler tube materials in biomass and coal-biomass co-fired power plants. Despite thermodynamic and kinetic boundary conditions, microstructural features such as grain orientation, grain sizes or surface deformation contribute to the oxidation resistance and formation of protective chromium-rich oxide layers. This study elucidates the impact of microstructure such as the grain size and number of carbide precipitates on high temperature oxidation at 650°C in 0.5% SO2 atmosphere. Cold-rolled Fe-16Cr-0.2C material was heat-treated to obtain two additional microstructures. After exposure to hot and reactive gases for 10 h < t < 1000 h layer thicknesses and microstructure of oxide scales are observed by scanning electron microscopy and Energy-dispersive X-ray spectroscopy. The two heat treated alloys showed reasonable oxidation resistance after 1000 h of exposure. The oxidation rate was substantially higher for the alloy with a duplex matrix after heat treatment compared to the fine-grained material.
Due to the advantages of additive manufacturing (AM), it has been increasingly integrated into many industrial sectors.
The application of AM materials for safety-critical parts requires the detailed knowledge about their microstructure stability under thermo-mechanical or mechanical load and knowledge on ageing process mechanisms. Ageing processes are characterized by change of the material microstructure that is to be initially investigated. This work deals with the Investigation of 316L stainless steel manufactured by selective laser melting (SLM). Describing Parameters must be defined and applied on the microstructure of these materials in their initial state and after loads were applied. The findings of this work form the basis for the investigation of AM material ageing.
The Ni-Cr-Mo-W alloy is characterized by the excellent high-temperature corrosion resistance, good strength and ability to work in aggressive environments. To protect the surface of the substrate 13CrMo4-5 steel against aggressive environments the Inconel 686 as clad layer was used. The corrosion process was performed in oxidizing mixture of gases like O2, COx, SOx. The second part of corrosion Experiment concerned the corrosion test of the coating in reducing atmosphere of the specified gases with ashes, which contained e.g. Na, Cl, Ca, Si, C, Fe, Al.
Für die Erfassung der Verbreitung von Mikroplastik (MP) in der Umwelt ist die zeit- und kostenaufwendige Analysestrategie und der damit verbundene geringe Probendurchsatz eine limitierende Größe. Eine große Zahl verschiedener Studien dokumentriet das Auftreten von MP über den gesamten Globus. Meist sind die Studien aufgrund des großen analytischen Aufwands auf exemplarische, stichpunktartige Untersuchungen kleiner Umweltaliquoten und zahlenmäßig kleiner Probenumfänge begrenzt. Um die Verbreitung, die Eintragspfade und den Verbleib von MP in der Umwelt besser zu verstehen und effektive Vermeidungsstrategien abzuleiten, ist es jedoch notwendig, analytisch mehr Proben erfassen zu können.
Bildgebende mikro-spektroskopische Methoden wie das Raman- und FTIR-Imaging ermöglichen eine zeitaufwendige, umfassende Charakterisierung kleiner Umweltaliquoten. Neben der Partikelanzahl sind zusätzlich Informationen zu Partikelgröße, Größenverteilung und Oberflächenmorphologie zugänglich. Chemische und thermische Extraktionsverfahren sind bereits deutlich schneller und können diese Informationen durch eine Massenbilanz vervollständigen. Die analysierbare Probenmenge ist jedoch auf Milligramm Mengen beschränkt.
Wir schlagen daher vor, die Analyse von Proben auf MP durch ein vorangestelltes Screening mit der Nahinfrarot-Spektroskopie (NIRS) zur komplementieren. In diesem wird bereits eine erste Einschätzung über die Präsenz von MP in einer Probe gefällt und dadurch die wertvolle Messzeit anderer Methoden effizienter genutzt.
NIR zur Analyse von Polymeren wird seit langem eingesetzt, jedoch bisher lediglich im Rahmen einer Studie zur Mikroplastikuntersuchung mittels Hyperspektraler Bildgebung beschrieben. Der NIR Spektralbereich findet sich zwischen dem sichtbaren Licht und dem mittleren Infrarot (MIR). MIR Spektren sind durch klar definierte Banden charakterisiert, welche mehrheitlich von den Grundschwingungen der Moleküle stammen. Die höheren Energien im nahen Infrarot regen hingegen Kombinations- und Oberschwingungen der Streck und Biegeschwingungen an. Die resultierenden Absorptionsbanden sind oft breit und relativ unspezifisch. Erst mit Hilfe einer computergestützten Datenauswertung lassen sich aus diesen Spektren nützliche Informationen gewinnen. Dies erklärt die steigende Popularität der NIR-Spektroskopie in der jüngeren Vergangenheit mit einem Schwerpunkt als prozessanalytische Methode. NIR Spektrometer für das industrielle Prozessmonitoring zeichnen sich durch eine kompakte und robuste Konstruktionsweise aus. Die verfügbaren faseroptischen Reflexionssonden eignen sich gut um pulverförmige Proben zu untersuchen. Der räumlich erfassbare Messbereich kann durch die Sondengeometrie variiert werden. Sind die untersuchten Partikel im Verhältnis zur abgetasteten Fläche klein, wird als spektrale Information die Summe der Absorption aller Partikel im Sichtfeld erfasst. Die Methode ist deshalb nicht für Detailuntersuchungen von MP geeignet, erlaubt es jedoch innerhalb weniger Minuten eine Einschätzung über das Vorkommen von Mikroplastik in einer Probe zu treffen.
Exemplarisch wurden für diese Untersuchungen vier der am weitesten verbreiteten Kunststoffe Polyethylen (PE), Polyethylenterephthalat (PET), Polypropylen (PP) und Polystyrol (PS) gewählt. Aus den additivfreien Polymeren wurden nach einer Kryo-vermahlung und anschließender Siebung (< 125 µm) Modellproben generiert. Die Polymere wurden dafür zu einem Massenanteil von 1 % mit einem Standardboden (LUFA2.3, gesiebt < 125 µm) vermischt. Die Gesamtmenge von 1 g je Probe wurde in Aluminiumbehältern präpariert und 8 Messungen an unterschiedlichen, zufällig gewählten Positionen vorgenommen. Die erhaltenen Spektren wurden zur Kalibrierung chemometrischer Modelle genutzt.
In einem hierarchischen Ansatz wurde anhand der NIR-Spektren eine Klassifizierung vorgenommen:
1. Bestimmung ob eine Probe MP enthält (Ja/Nein).
2. Identifikation der Polymere in der Probe.
Eine aussagekräftige Klassifizierung beruht auf einer Vorbehandlung der Spektren. Hierdurch werden die Unterschiede zwischen den einzelnen Polymerbanden hervorgehoben. Die Eignung der so erstellten Modelle wurde anhand eines Referenzmaterials und am Beispiel von Realproben erfolgreich getestet. Dabei zeigte sich, dass nicht nur in den erstellten Polymer-Bodenmischungen, sondern auch in den Rückständen von fermentiertem Bioabfall und in Filterrückständen einer Waschmaschine, MP richtig erkannt wurde. Weiterhin zeigten Tests mit Mikroplastik-freien Bodenproben unterschiedlicher Herkunft, dass keine falsch-positive Resultate erzeugt wurden. Alle vier untersuchten Polymere, d.h. PE, PET, PS und PP mit einem Massenanteil von 1 % in einer Bodenmatrix werden auch bei einer gemischten Polymerzusammensetzung mit der NIR-Spektroskopie erkannt.
Der kombinierte Einsatz von NIRS und Chemometrie ermöglicht die Entscheidung über ein potenzielles Vorkommen sowie die Zuordnung des Materials der enthaltenen Polymerpartikel für eine Massefraktion ≥ 1 % in einer (trockenen) Probenmenge von 1 g innerhalb von 10–15 min. Der zeitaufwendige Schritt der Methode liegt hier in der Erstellung geeigneter chemometrischer Modelle sowie deren Validierung. Wesentliche Voraussetzung ist dabei, dass bei der Kalibrierung die Varianz der zu erwartenden Partikel und der Matrix realistisch abgebildet wird.
Morphologies of Fresnoite surface crystals of BT0.75S glass under different atmospheric conditions
(2019)
Fresnoite glass-ceramics are characterized by piezoelectric, pyroelectric and non-linear optical properties. These properties can be adjusted by orienting the fresnoite crystals during crystallization. Crystallization begins at the surface. The first surface crystals are not oriented perpendicular and, therfore, produce a surface layer that has not the intended properties. To overcome this issue, the formation of fresnoite surface crystals at different atmospheric conditions was studied.
Fiber reinforced polymers (FRPs) are a well established material in lightweight applications, e.g. in automotive, aerospace or wind energy. The FRP components are subjected to multiaxial mechanical as well as hygrothermal loads. Common operation temperatures are in the range of 213 K and 373 K (-60 °C and 100 °C) at a relative humidity of 10% to 90%. In spacecraft applications, the environmental conditions are even more extreme. However, the correlation between multiaxial mechanical loading and harsh environment conditions have to-date not been investigated in detail. The project aims to investigate the fatigue behavior of FRPs dependent on multiaxial mechanical loading, temperature, and humidity. Extensive experimental testing is performed on flat plate and cylindrical tube specimens, accompanied by numerical and analytical calculations.
Within NFDI-MatWerk (“National Research Data Infrastructure for Material Sciences”/ “Nationale Forschungsdateninfrastruktur für Materialwissenschaften und Werkstofftechnik“), the Task Area Materials Data Infrastructure (TA-MDI) will provide tools and services to easily store, share, search, and analyze data and metadata. Such a digital materials environment will ensure data integrity, provenance, and authorship. The MatWerk consortium aims to develop specific solutions jointly with Participant Projects (PPs), which are scientific groups or institutes covering different domains, from theory and simulations to experiments. The Data Exploitation Methods group of the Karlsruhe Institute of Technology-Steinbuch Centre of Computing, as part of TA-MDI, is developing specific solutions in close collaboration with three PPs.
PP07, together with the University of Stuttgart, aims at the image-based prediction of the material properties of stochastic microstructures using large-scale supercomputers. PP13, in cooperation with the University of Saarland, focuses on tomographic methods at various scales in materials research. PP18, together with the Federal Institute for Materials Research and Testing (“Bundesanstalt für Materialforschung und -prüfung”), aspires to define the criteria for materials reference datasets and usage analytics.
The requirements and goals are comparable for each PP: their research outputs, which are scientific datasets, should conform to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. We aim to shape them from a data management perspective making use of the FAIR Digital Object concept, including structured metadata and storage solutions. The results will be a blueprint which will act as a reference for future datasets. Even though the collaboration is in an early stage, the initial steps already show the added value of this approach.
This research has been supported by the Federal Ministry of Education and Research
(BMBF) – funding code M532701 / the Deutsche Forschungsgemeinschaft (DFG, German
Research Foundation) - project number NFDI 38/1, project no. 460247524.
Reference datasets in the MSE domain represent specific material properties, e.g., structural, mechanical, … characteristics. A reference dataset must fulfill high-quality standards, not only in precision of measurement but also in a comprehensive documentation of material, processing, and testing history (metadata). This Infrastructure Use Case (IUC) of the consortium Materials Science and Engineering (MatWerk) of National Research Data Infrastructure (NFDI) aims to develop, together with BAM and other Participant Projects (PP), a framework for generating reference material datasets using creep data of a single crystal Ni-based superalloy as a best practice example. In a community-driven process, we aim to encourage the discussion and establish a framework for identifying reference material datasets. In this poster presentation, we highlight our current vision and activities and intend to stimulate the discussion about the topic reference datasets and future collaborations and work.
Gypsum (CaSO4∙2H2O) and anhydrite (CaSO4) are among the dominant evaporite minerals in the Atacama Desert [1]. They are distributed ubiquitously, and play a key role in local landscape evolution.
The formation mechanism of especially anhydrite has been a matter of scientific debate for more than a century [2]. To date, there exists no model that can reliably predict anhydrite formation at earth’s surface conditions. While thermodynamics favor its formation [3], it is hardly achieved on laboratory time scales at conditions fitting the Atacama Desert. Long induction times for nucleation have recently been modeled by Ossorio et al. [4]. However, anhydrite can be readily found in the Atacama Desert. Recently, the mineral was synthesized in flow-through reactors as a byproduct of K-jarosite dissolution at high water activity (aw=0.98) and room temperature [5], even-though the thermodynamic stability field begins only under a value of ~0.8. Additionally, recent studies investigated the nano-structure of various calcium-sulfates, which advocate for highly non-classical crystallization behavior [6]. The specific roles of particulates, ionic or organic reagents working as catalysts for the non-classical crystallization pathway remain to be determined.
Here, we present recent results from flow-through experiments as well as analyses of anhydrite samples from the Atacama Desert. Flow-through experiments were performed to systematically explore the domains of flow rate, composition, ionic-strengths and starting materials. Neither primary, nor secondary anhydrite was produced in any of these experiments. Analyses on Atacama samples reveal the existence of at least three distinct anhydrite facies, with differing mineralogy and micro- to nano-structures. The facies are (1) aeolian deposits with sub-µm grain sizes, (2) (sub-)surface nodules that formed from aeolian deposits and (3) selenites with secondary anhydrite rims. Possible mechanisms of their formation will be discussed.
Up to now, oriented surface crystallization phenomena are discussed controversially, and related studies are restricted to few glasses. For silicate glasses we found a good correlation between the calculated surface energy of crystal faces and oriented surface nucleation. Surface energies were estimated assuming that crystal surfaces resemble minimum energy crack paths along the given crystal plane. This concept was successfully applied by Rouxel in calculating fracture surface energies of glasses. Several oriented nucleation phenomena can be herby explained assuming that high energy crystal surfaces tend to be wetted by the melt. This would minimize the total interfacial energy of the nucleus. Furthermore, we will discuss the evolution of the microstructure and its effect on the preferred crystal orientation.
The life time of mechanical components in high temperature applications is basically determined by their workings. Corrosion determines the loss of material corresponding to the loss of the effective load-bearing section and consequently increasing stress levels. To improve the material selection for such applications a numerical life prediction corrosion model for different alloys and environments is needed. Based on the ferritic alloys FeCr and FeCrCo a first quantitative model is to be developed. For this purpose, the alloys are aged at 600°C, 650°C and 700°C in synthetic air under normal pressure for between 10 and 240 hours. The first objective is to establish a quantitative relationship between the oxidation rate as a function of composition and microstructure of the alloys. The influence of the inner interface as an essential parameter for transport by diffusion on the oxidation kinetics is discussed in this presentation.
Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific.
This poster presents an approach to create and maintain a comprehensive and intuitive MSE-centric terminology by developing a mid-level ontology–the PMD core ontology (PMDco)–via MSE community-based curation procedures.
The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications.
The PMD Core Ontology (PMDco) is a comprehensive set of building blocks produced via consensus building. The ontological building blocks provide a framework representing knowledge about fundamental concepts used in Materials Science and Engineering (MSE) today. The PMDco is a mid-level ontology that establishes connections between narrower MSE application ontologies and domain neutral concepts used in already established broader (top-level) ontologies. The primary goal of the PMDco design is to enable interoperability between various other MSE-related ontologies and other common ontologies.
PMDco’s class structure is both comprehensive and extensible, rendering it an efficient tool to structure MSE knowledge. The PMDco serves as a semantic middle-layer unifying common MSE concepts via semantic mapping to other semantic representations using well-known key terms used in the MSE domain. The PMDco enables straight-forward documentation and tracking of science data generation and in consequence enables high-quality FAIR data that allows for precise reproducibility of scientific experiments.
The design of PMDco is based on the W3C Provenance Ontology (PROV-O), which provides a standard framework for capturing the production, derivation, and attribution of resources. Via this foundation, the PMDco enables the integration of data from various data origins and the representation of complex workflows.
In summary, the PMDco is a valuable advancement for researchers and practitioners in MSE domains. It provides a common MSE vocabulary to represent and share knowledge, allowing for efficient collaboration and promoting interoperability between diverse domains. Its design allows for the systematic integration of data and metadata, enabling seamless tracing of science data. Overall, the PMDco is a crucial step towards a unified and comprehensive understanding of the MSE domain in general.
Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific.
In this poster presentation, an approach how to maintain a comprehensive and intuitive MSE-centric terminology composing a mid-level ontology–the PMD core ontology (PMDco)–via MSE community-based curation procedures is shown.
The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications.
Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific.
In this presentation, an approach how to maintain a comprehensive and intuitive MSE-centric terminology composing a mid-level ontology–the PMD core ontology (PMDco)–via MSE community-based curation procedures is shown.
The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications.
Currently, calcium manganate CaMnO3 and calcium cobaltite Ca3Co4O9 are being investigated as n-type resp. p-type semiconducting materials as oxidation- and temperature-resistant thermoelectric materials for oxide multilayer thermoelectric generators (TEGs). In order to manufacture multilayer TEGs, pressure-assisted sintering processes at high temperatures are necessary to achieve optimal thermoelectric material properties. To realize TEGs in planar film technology, another method to obtain dense ceramic layers directly from the synthesized starting powders without a subsequent high temperature step is emerging recently: the powder aerosol deposition (PAD) method. In the present work, it is investigated whether PAD is suitable to produce dense ceramic films from Sm-doped CaMnO3 and Ca3Co4O9 powders. The resulting thermoelectric properties are characterized as a function of temperature.
CaMnO3 powder could successfully be processed by PAD with resulting layer thicknesses of 5- 6 µm without any high-temperature sintering steps of the films. The electrical conductivity and the Seebeck coefficient of the films were determined in-plane from room temperature to 600 °C in air. The results show a Seebeck coefficient of around -200 µV/K, which is comparable to results of pressed and sintered bars. At 400 °C, the electrical conductivity corresponds to the conductivity of the bar. At higher temperatures the conductivity is better than with the reference. Below 400°C, the electrical conductivity is somewhat lower than that of the reference sample, a mild thermal treatment of the PAD layer improves it. It is expected that the thermal conductivity of the PAD film will be lower compared to the bars due to the nano-crystalline film morphology. This should result in a significantly increased ZT value for the PAD layers and a higher efficiency of the TEG.
The work shows that both CaMnO3 and Ca3Co4O9 can be successfully processed by PAD, and the PAD films show comparable thermoelectric properties.