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Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines.
The combination of microstructural data with other experimental techniques and with modeling is paramount, if we want to extract the maximum amount of information on porous material properties. In particular, quantitative image analysis, statistical approaches, direct discretization of tomographic reconstructions represent concrete possibilities to extend the power of the tomographic 3D representation to insights into the material and component performance. I will show a few examples of possible use of X-ray tomographic data for quantitative assessment of porosity in ceramics.
Moreover, I will show how not-so-novel 2D characterization techniques, based X-ray refraction, can allow a great deal of insights in the damage evolution in microcracked (and porous) ceramics. I will show how X-ray refraction can detect objects (e.g. microcracks) below its own spatial resolution.
Finally, I will discuss the link between the microstructural findings and the mechanical properties of porous microcracked ceramics.
Additive Manufacturing (AM) in terms of laser powder-bed fusion (L-PBF) offers new prospects regarding the design of parts and enables therefore the production of complex structures. The quality of the feedstock material receives increasing attention, as it depicts the first part of the L-PBF process chain. The powder quality control in terms of flowability and powder bed packing density is therefore mandatory.
In this work, a workflow for quantitative 3D powder analysis in terms of particle size, particle shape, particle porosity, inter-particle distance and packing density was established. Synchrotron computed tomography (CT) was used to correlate the packing density with the particle size and particle shape for three different powder batches. The polydisperse particle size distribution (PSD) was transformed into a statistically equivalent bidisperse PSD. The ratio of the small and large particles helped to understand the powder particle packing density. While the particle shape had a neglectable influence, the particle size distribution was identified as major contributor for the packing density.
Layer-by-layer additive manufacturing (AM) by means of laser-powder bed Fusion (L-PBF) offers many prospects regarding the design of lattice structures used, for example, in gas turbines. However, defects such as bulk porosity, Surface roughness, and re-entrant features are exacerbated in nonvertical structures, such as tilted struts. The characterization and quantification of these kinds of
defects are essential for the correct estimation of fracture and fatigue properties.
Herein, cylindrical struts fabricated by L-PBF are investigated by means of X-ray computed tomography (XCT), with the aim of casting light on the dependence of the three kinds of defects (bulk porosity, surface roughness, and re-entrant features) on the build angle. Innovative analysis methods are proposed to correlate shape and position of pores, to determine the angular-resolved Surface roughness, and to quantify the amount of re-entrant surface features, q. A meshing of the XCT surface enables the correlation of q with the classical Surface roughness Pa. This analysis leads to the conclusion that there is a linear correlation between q and Pa. However, it is conjectured that there must be a threshold of surface roughness, below which no re-entrant features can be build.
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique).
Metal Additive Manufacturing (AM) technologies such as Laser Powder Bed Fusion (LPBF) are characterized by layer wise construction, which enable advancements of component design, leading to potential efficiency and performance improvements. However, the rapid cooling rates associated with the process consequently leads to the generation of high magnitude residual stresses (RS). Therefore, a deep understanding of the formation of RS, the influence of process parameters on their magnitude and the impact on mechanical performance is crucial for widespread application. The experimental characterization of these RS is essential for safety related engineering application and supporting the development of reliable numerical models. Diffraction-based methods for RS analysis using high energy synchrotron X-rays and neutrons enable non-destructive spatially resolved characterization of both surface and bulk residual stresses in complex components. This presentation will provide an overview of recent research conducted by the BAM at large scale facilities for the characterization of residual stresses in LPBF metallic alloys. Special focus will be given to the challenges posed by textured LPBF materials for the reliable choice of the diffraction elastic constants (DECs), which is crucial to the accurate calculation of the level of RS.
The focus of the presentation focus will be on 3D imaging by means of X-ray Computed Tomography (XCT) at the lab and at synchrotron, and the non-destructive residual stress (RS) characterization by diffraction of additively manufactured (AM) materials in BAM (Berlin, Germany). The manufacturing defects and high RS are inherent of AM techniques and affect structural integrity of the components. Using XCT the defects size and shape distribution as well as geometrical deviations can be characterized, allowing the further optimization of the manufacturing process. Diffraction-based RS analysis methods using neutron and synchrotron X-rays at large scale facilities offer the possibility to non-destructively spatially resolve both surface and bulk RS in complex components and track their changes following applied thermal or mechanical loads.
The overview of the activity of group 8.5 Micro-NDT (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique).
Absorption edge tomography, also known as differential tomography at absorption edges, is a method which exploits the sudden change of the attenuation coefficient, when the photon energy crosses the absorption edge of an element. Synchrotron radiation is the best source for absorption edge tomography, because of its small bandwidth, high intensity and easily adjustable photon energy. The synchrotron beamline BAMline at the synchrotron radiation facility BESSY II in Berlin, which is operated by the Bundesanstalt für Materialforschung und -prüfung (BAM), provides a monochromatized beam in a photon energy range from 5 keV up to 80 keV with a bandwidth of 2%, when the double multilayer monochromator is used. Together with the microtomography setup, this enables differential tomography with submicron resolution at the K edge of the elements from chromium up to the lanthanides, and up to uranium, when the L edges are used as well.
In this work, metal organic frameworks (MOFs) embedded in polymer are characterized using differential tomography. MOFs are microporous structures of metal ions, coordinated by organic linker molecules, that can be used in a broad field of applications, especially in gas storage and catalysis. In this work, polymer embedded MOFs were extruded into filaments, which could be used for 3d-printing to profit from the specific properties of the MOFs in polymeric materials combined with the arbitrary shapes provided by 3d-printing. For the extrusion, different polymer classes like ABS, polyester- and polyetherurethanes, as well as different MOFs (ZIF-8, ZIF-67, HKUST-1) were used to create MOF containing filaments with a nominal diameter of 3.0 mm. Differential tomography at the edges of the Zn, Co, and Cu was then used to find the distribution of the corresponding MOF in the filament and to analyze the shape of the inclusions.
The quality of components made by laser beam melting (LBM) additive manufacturing is naturally influenced by the quality of the powder bed. A packing density <1 and porosity inside the powder particles lead to intrinsic voids in the powder bed. Since the packing density is determined by the particle size and shape distribution, the determination of these properties is of significant interest to assess the printing process. In this work, the size and shape distribution, the amount of the particle’s intrinsic porosity, as well as the packing density of micrometric powder used for LBM, have been investigated by means of synchrotron X-ray computed tomography (CT). Two different powder batches were investigated: Ti–6Al–4V produced by plasma atomization and stainless steel 316L produced by gas atomization. Plasma atomization particles were observed to be more spherical in terms of the mean anisotropy compared to particles produced by gas atomization. The two kinds of particles were comparable in size according to the equivalent diameter. The packing density was lower (i.e., the powder bed contained more voids in between particles) for the Ti–6Al–4V particles. The comparison of the tomographic results with laser diffraction, as another particle size measurement technique, proved to be in agreement.
As opposed to reviewing results on experimental determination of residual stress by diffraction, this paper discusses the open issues when dealing with residual stress determination in additive manufactured parts, in particular those manufactured with laser powder bed fusion techniques. Three points are addressed in detail: (a) the proper determination of the strain-free reference d0, (b) the problem of the determination of the principal axes, and (c) the use of the correct diffraction elastic constants. It is shown that all methods to determine the strain-free reference d0 suffer from caveats, and care must be taken in evaluating the most suitable for the problem being tackled. In addition, it is shown that, in some systems, the principal axes do correspond to the geometrical axes of the specimen, but this needs to be systematically checked, especially in the case of uni- or bidirectional hatching strategies. Finally, the need to experimentally determine the proper diffraction elastic constants is underlined, especially in the case of strongly textured specimens, which again depends on the deposition strategy.
The prediction of porosity is a crucial task for metal based additive manufacturing techniques such as laser powder bed fusion. Short wave infrared thermography as an in-situ monitoring tool enables the measurement of the surface radiosity during the laser exposure. Based on the thermogram data, the thermal history of the component can be reconstructed which is closely related to the resulting mechanical properties and to the formation of porosity in the part. In this study, we present a novel framework for the local prediction of porosity based on extracted features from thermogram data. The framework consists of a data pre-processing workflow and a supervised deep learning classifier architecture. The data pre-processing
workflow generates samples from thermogram feature data by including feature information from multiple subsequent layers.
Thereby, the prediction of the occurrence of complex process phenomena such as keyhole pores is enabled. A custom convolutional neural network model is used for classification. Themodel is trained and tested on a dataset from thermographic in-situ monitoring of the manufacturing of an AISI 316L stainless steel test component. The impact of the pre-processing parameters and the local void distribution on the classification performance is studied in detail. The presented model achieves an accuracy of 0.96 and an f1-Score of 0.86 for predicting keyhole porosity in small sub-volumes with a dimension of (700 × 700 × 50) μm3. Furthermore, we show that pre-processing parameters such as the porosity threshold for sample
labeling and the number of included subsequent layers are influential for the model performance. Moreover, the model prediction is shown to be sensitive to local porosity changes although it is trained on binary labeled data that disregards the actual sample porosity.
By means of a small-scale truss bridge, the ability of the Measurement- and Model-based Structural Analysis to detect and localize damage was examined. Although there was no noteworthy difficulty in detecting damage, it turned out that damage localization responds sensitively to systematic influences, i.e. non-modelled properties of the mechanical model. Therefore, another experiment is being conducted to re-examine the Measurement- and Model-based Structural Analysis. For this purpose, the bending test is carried out as it has been already theoretically respectively numerically discussed. In this attempt, the systematic influences such as residual stress are kept as low as possible.
By means of a small-scale truss bridge, the ability of the Measurement- and Model-based Structural Analysis to detect and localise damage was examined in. Although there was no noteworthy difficulty in detecting damage, it turned out that damage localisation responds sensitively to systematic influences, i.e. non-modelled properties of the mechanical model. Therefore, another experiment is being conducted to re-examine the Measurement- and Model-based Structural Analysis. For this purpose, the bending test is carried out as it has been already theoretically respectively numerically discussed in. In this attempt, the systematic influences such as residual stress are kept as low as possible.
Fiber-reinforced concretes (FRCs) offer significant improvements in tensile strength and durability compared to most other concrete mixes.
However, for safe and efficient use of FRC in large structures, anisotropy of fiber orientation needs to be understood and properly controlled. In this project, both cored samples extracted from a FRC slab and FRC samples cast individually in molds were assessed using X-ray computed tomography (CT) and measurements of fiber orientation were extracted from the resulting CT images. These results showed that fibers within the slab were highly anisotropic in orientation while fibers in individually cast samples showed a much more heterogeneous distribution of orientations.
This indicates that fiber orientation is highly dependent on the casting process and suggests that FRC can only be safely and efficiently utilized if anisotropic fiber orientation is properly accounted for during design and optimized casting methods are used during construction.
Additive Manufacturing (AM) in terms of laser powder-bed fusion (L-PBF) offers new prospects regarding the design of parts and enables therefore the production of lattice structures. These lattice structures shall be implemented in various industrial applications (e.g. gas turbines) for reasons of material savings or cooling
channels. However, internal defects, residual stress, and structural deviations from the nominal geometry are unavoidable.
In this work, the structural integrity of lattice structures manufactured by means of L-PBF was non-destructively investigated on a multiscale approach.
A workflow for quantitative 3D powder analysis in terms of particle size, particle shape, particle porosity, inter-particle distance and packing density was established.
Synchrotron computed tomography (CT) was used to correlate the packing
density with the particle size and particle shape. It was also observed that at least about 50% of the powder porosity was released during production of the struts.
Struts are the component of lattice structures and were investigated by means of laboratory CT. The focus was on the influence of the build angle on part porosity and surface quality. The surface topography analysis was advanced by the quantitative characterisation of re-entrant surface features. This characterisation was compared with conventional surface parameters showing their complementary
information, but also the need for AM specific surface parameters.
The mechanical behaviour of the lattice structure was investigated with in-situ CT under compression and successive digital volume correlation (DVC). The Deformation was found to be knot-dominated, and therefore the lattice folds unit cell layer wise.
The residual stress was determined experimentally for the first time in such lattice structures. Neutron diffraction was used for the non-destructive 3D stress investigation. The principal stress directions and values were determined in dependence of the number of measured directions. While a significant uni-axial stress state was found in the strut, a more hydrostatic stress state was found in the knot. In both cases, strut and knot, seven directions were at least needed to
find reliable principal stress directions.
A paradigm shift in the description of creep in metals can only occur through multi-scale imaging
(2022)
The description of creep in metals has reached a high level of complexity; fine details are revealed by all sorts of characterization techniques and different theoretical models. However, to date virtually no fully microstructure-driven quantitative description of the phenomenon is available. This has brought to interesting inconsistencies; the classic description of (secondary) creep rests on the so-called power law, which however: a- has a pre-factor spanning over 10 orders of magnitude; b- has different reported exponents for the same material; c- has no explanation for the values of such exponents.
Recently, a novel description (the so-called Solid State Transformation Creep (SSTC) Model) has been proposed to tackle the problem under a different light. The model has two remarkable features: 1- it describes creep as the accumulation of elementary strains due to dislocation motion; 2- it predicates that creep is proceeding by the evolution of a fractal arrangement of dislocations. Such description, however, needs a great deal of corroborating evidence, and indeed, is still incomplete.
To date, we have been able to observe and somehow quantify the fractal arrangement of microstructures through Transmission Electron Microscopy (TEM), observe the accumulation of dislocations at grain boundaries by EBSD-KAM (Electron Back-Scattered Diffraction-Kernel Angular Misorientation) analysis, quantify the kinetic character (solid state transformation) of experimental creep curves, and estimate the sub-grain size of the fractal microstructure through X-ray refraction techniques. All pieces of the mosaic seem to yield a consistent picture: we seem being on the right path to reconstruct the whole elephant by probing single parts of it. What is still missing is the bond between the various scales of investigation.
The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples.
In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge.
This paper describes a new ultrasonic measuring device called “W-Box”. It was developed based on the requirements of the DFG Forschergruppe (research unit) CoDA for a portable device for monitoring of concrete specimens, models and actual structures using embedded ultrasonic transducers as well as temperature and humidity sensors. The W-Box can send ultrasonic pulses with a variable frequency of 50–100 kHz to one selectable transducer and records signals from up to 75 multiplexed channels with a sample rate of 1 MHz and a resolution of 14 bits. In addition, it measures temperature and humidity with high accuracy, adjustable amplification, restarts automatically after a power failure and can be fully controlled remotely. The measured data are automatically stored locally on-site data quality checks and transferred to remote servers. The comparison of the W-Box with a laboratory setup using commercial devices proves that it is equally reliable and precise, at much lower cost. The W-Box also shows that their measurement capacities, with the used embedded ultrasonic transducers, can reach above 6 m in concrete.
The hard X-ray beamline BAMline at BESSY II (Berlin, Germany) has now been in service for 20 years. Several improvements have been implemented in this time, and this review provides an overview of the imaging methods available at the BAMline. Besides classic full-field synchrotron X-ray computed tomography (SXCT), also absorption edge CT, synchrotron X-ray refraction radiography (SXRR), and synchrotron X-ray refraction tomography (SXRCT) are used for imaging. Moreover, virtually any of those techniques are currently coupled in situ or operando with ancillary equipment such as load rigs, furnaces, or potentiostats. Each of the available techniques is explained and both the current and the potential usage are described with corresponding examples. The potential use is manifold, the examples cover organic materials, composite materials, energy-related materials, biological samples, and materials related to additive manufacturing. The article includes published examples as well as some unpublished applications.
The Measurement- and Model-based Structural Analysis (MeMoS) integrates a finite element model into least squares adjustment and thus allows to evaluate a mechanical model and measurements in a combined analysis. To examine the capability to detect and localise damage using this integrated analysis MeMoS, a small-scale truss bridge made of aluminium profiles is built as a test specimen for this purpose.
To date, there are only very few technologies available for the conversion of low temperature waste heat to electricity. In this talk, we first describe the principle of thermomagnetic generators. Then we focus on the impact of topology of the magnetic circuit within thermomagnetic generators. We demonstrate that the key operational parameters strongly depend on the genus, i.e. the number of holes within the magnetic circuit.
To date, there are only very few technologies available for the conversion of low temperature waste heat to electricity. In this talk, we first describe the principle of thermomagnetic generators. Then we focus on the impact of topology of the magnetic circuit within thermomagnetic generators. We demonstrate that the key operational parameters strongly depend on the genus, i.e. the number of holes within the magnetic circuit.
About the Role of Interfaces on the Fatigue Crack Propagation in Laminated Metallic Composites
(2021)
The influence of gradients in hardness and elastic properties at interfaces of dissimilar materials in laminated metallic composites (LMCs) on fatigue crack propagation is investigated experimentally for three different LMC systems: Al/Al-LMCs with dissimilar yield stress and Al/Steel-LMCs as well as Al/Ti/Steel-LMCs with dissimilar yield stress and Young’s modulus, respectively. The damage tolerant fatigue behavior in Al/Al-LMCs with an alternating layer structure is enhanced significantly compared to constituent monolithic materials. The prevalent toughening mechanisms at the interfaces are identified by microscopical methods and synchrotron X-ray computed tomography. For the soft/hard transition, crack deflection mechanisms at the vicinity of the interface are observed, whereas crack bifurcation mechanisms can be seen for the hard/soft transition. The crack propagation in Al/Steel-LMCs was studied conducting in-situ scanning electron microscope (SEM) experiments in the respective low cycle fatigue (LCF) and high cycle fatigue (HCF) regimes of the laminate. The enhanced resistance against crack propagation in the LCF regime is attributed to the prevalent stress redistribution, crack deflection, and crack bridging mechanisms. The fatigue properties of different Al/Ti/Steel-LMC systems show the potential of LMCs in terms of an appropriate selection of constituents in combination with an optimized architecture. The results are also discussed under the aspect of tailored lightweight applications subjected to cyclic loading.
Der Mangel an Anwendungsrichtlinien und Validierungsverfahren für struktur-eingebettete faseroptische Dehnungssensoren, insbesondere auf Faser-Bragg-Gitter (FBG)-Basis, führte bislang dazu, dass diese Sensoren trotz ihrer hervorragenden Eigenschaften im Bereich der kommerziellen Material- und Strukturüberwachung nur in geringem Umfange eingesetzt wurden. Fragen zur Degradation der Sensoren unter Beanspruchung, Alterung durch klimatische Einflüsse und Enthaftung infolge Belastung der Struktur konnten bisher nur theoretisch simuliert oder anhand exemplarischer Proben für einzelne einflussnehmende Parameter im Labor untersucht werden. Die Erfassung des Sensorverhaltens im Bauteil unter komplexen Umwelteinflüssen während des Bauteilbetriebes, um damit eine Aussage zur Zuverlässigkeit der Sensormessdaten zu gewinnen, war bisher nicht möglich.
Im Forschungsprojekt FAMOS² wurde deshalb von 2014 bis 2018 die Realisierung eines Autodiagnoseverfahrens für faseroptische Dehnungssensoren erarbeitet, um die Funktionszuverlässigkeit und Langzeitstabilität der Sensoren während des Bauteilbetriebes innerhalb einer Bauteilstruktur bewerten zu können. Im Rahmen des Forschungsprojektes wurde gezeigt, dass ein FBG-Sensor mit einer speziell angepassten magnetostriktiven Schicht magnetisch so angeregt werden kann, dass mit einer zugeschnittenen Messmethodik zu jedem Zeitpunkt eine Bewertung der Sensorzuverlässigkeit unter Betriebsbedingungen möglich ist. Die auf den Sensor aufgebrachte magnetostriktive Schicht erzeugt bei Anregung mit einem passenden Magnetfeld eine gepulste, synthetische Dehnung. Diese Dehnung steht in einem definierten Verhältnis zum anregenden Magnetfeld und wird optisch über die Verschiebung der Bragg-Wellenlänge ausgelesen. Die Konstanz dieses Verhältnisses stellt dann ein Maß für die korrekte Funktionsfähigkeit des Sensors dar. Das Beschichtungs-verfahren, das magnetische Anregungs- und optische Ausleseverfahren, wie auch die Validierung des Sensors unter Berücksichtigung faseroptischer Effekte wurden während des Projekts konzeptionell entwickelt, aufgebaut und charakterisiert. Qualitativ kann mit diesem Verfahren zunächst eine Gut-/Schlecht-Beurteilung des Sensors vorgenommen werden. Perspektivisch bietet das Verfahren jedoch auch die Möglichkeit, verschiedene Versagensmechanismen bestimmen und klassifizieren zu können. Es zeichnete sich schon während des Projektverlaufs ab, dass sich aus den erzielten Ergebnissen über das Autodiagnoseverfahren hinaus weitere Anwendungsmöglichkeiten für den Einsatz des kombinierten magnetostriktiv-faseroptischen Sensorprinzips, beispielsweise als reiner Magnetfeldsensor, ergeben.
Nach Abschluss dieses Forschungsprojekts besteht nun die Möglichkeit, den Funktionszustand faseroptischer Dehnungssensoren jederzeit unabhängig von Alter, Belastung oder Kenntnis eines Referenzzustands zu einem bestimmten Zeitpunkt bestimmen zu können. Aufbauend auf diesen Ergebnissen können weiterführende Forschungen die Messmethodik vertiefend charakterisieren und weitere Anwendungsfälle erschließen.
The influence of size effects on the thermoelectric properties of thin platinum films is investigated and compared to the bulk. Structural properties, like the film thickness and the grain size, are varied. We correlate the electron mean free path with the temperature dependence of the electrical conductivity and the absolute Seebeck coefficient SPt of platinum. A measurement platform was developed as a standardized method to determine SPt and show that SPt,film is reduced compared to SPt,bulk. Boundary and surface scattering reduce the thermodiffusion and the phonon drag contribution to SPt,film by nearly the same factor. We discuss in detail on behalf of a model, which describes the temperature dependence of the absolute Seebeck coefficient, the influence of size effects of electron-phonon and phonon-phonon interaction on SPt.
With 8% of man-made CO2 emissions, cement production is an important driver of the climate crisis. By using alkali-activated binders, part of the energy-intensive clinker production process can be dispensed. However, as numerous raw materials are involved in the manufacturing process here, the complexity of the materials increases by orders of magnitude. Finding a properly balanced binder formulation is like looking for a needle in a haystack. We have shown for the first time that artificial intelligence (AI)-based optimization of alkali-activated binder formulations can significantly accelerate research.
The "Sequential Learning App for Materials Discovery" (SLAMD) aims to accelerate practice transfer. With SLAMD, materials scientists have low-threshold access to AI through interactive and intuitive user interfaces. The value added by AI can be determined directly. For example, the CO2 emissions saved per ton of cement can be determined for each development cycle: the more efficient the AI optimization, the greater the savings.
Our material database already includes more than 120,000 data points of alternative binders and is constantly being expanded with new parameters. We are currently driving the enrichment of the data with a life cycle analysis of the building materials.
Based on a case study we show how intuitive access to AI can drive the adoption of techniques that make a real contribution to the development of resource-efficient and sustainable building materials of the future and make it easy to identify when classical experiments are more efficient.
With 8% of man-made CO2 emissions, cement production is an important driver of the climate crisis. By using alkali-activated binders, part of the energy-intensive clinker production process can be dispensed. However, as numerous raw materials are involved in the manufacturing process here, the complexity of the materials increases by orders of magnitude. Finding a properly balanced binder formulation is like looking for a needle in a haystack. We have shown for the first time that artificial intelligence (AI)-based optimization of alkali-activated binder formulations can significantly accelerate research.
The "Sequential Learning App for Materials Discovery" (SLAMD) aims to accelerate practice transfer. With SLAMD, materials scientists have low-threshold access to AI through interactive and intuitive user interfaces. The value added by AI can be determined directly. For example, the CO2 emissions saved per ton of cement can be determined for each development cycle: the more efficient the AI optimization, the greater the savings.
Our material database already includes more than 120,000 data points of alternative binders and is constantly being expanded with new parameters. We are currently driving the enrichment of the data with a life cycle analysis of the building materials.
Based on a case study we show how intuitive access to AI can drive the adoption of techniques that make a real contribution to the development of resource-efficient and sustainable building materials of the future and make it easy to identify when classical experiments are more efficient.
With 8% of man-made CO2 emissions, cement production is an important driver of the climate crisis. By using alkali-activated binders, part of the energy-intensive clinker production process can be dispensed. However, as numerous raw materials are involved in the manufacturing process here, the complexity of the materials increases by orders of magnitude. Finding a properly balanced binder formulation is like looking for a needle in a haystack. We have shown for the first time that artificial intelligence (AI)-based optimization of alkali-activated binder formulations can significantly accelerate research.
The "Sequential Learning App for Materials Discovery" (SLAMD) aims to accelerate practice transfer. With SLAMD, materials scientists have low-threshold access to AI through interactive and intuitive user interfaces. The value added by AI can be determined directly. For example, the CO2 emissions saved per ton of cement can be determined for each development cycle: the more efficient the AI optimization, the greater the savings.
Our material database already includes more than 120,000 data points of alternative binders and is constantly being expanded with new parameters. We are currently driving the enrichment of the data with a life cycle analysis of the building materials.
Based on a case study we show how intuitive access to AI can drive the adoption of techniques that make a real contribution to the development of resource-efficient and sustainable building materials of the future and make it easy to identify when classical experiments are more efficient.
Acoustic Emission
(2018)
Das Phänomen Schallemission (eng. Acoustic Emission, AE) ist eine Begleiterscheinung bei aktiven Mechanismen und Prozessen wie sie in Werkstoffen auftreten, die einer Belastung durch Krafteinwirkung oder durch Änderung der Umgebungsbedingungen ausgesetzt sind. Plastische Verformung, Risswachstum, Korrosion oder der Übergang zu einer anderen Phase generieren u.a. transiente elastische Wellen, die sich im Werkstoff und an der Materialoberfläche ausbreiten. Auftretende Auslenkungen von wenigen hundert Pikometern sind mit piezo-elektrischen AE Sensoren detektierbar. Aufzeichnungsraten von bis zu 40 MHz ermöglichen dabei zeitliche Auflösungen von einigen Nano- bis Mikrosekunden. Die Dechiffrierung der detektierten Informationen ist für die Material- und Versagenscharakterisierung sowie für Anwendungen in der Struktur- oder Prozessüberwachung ein zentraler Forschungsschwerpunkt.
Nach einem kurzen Überblick zu den Grundlagen werden ausgewählte Ansätze der AE Methode vorgestellt und diskutiert:
1) AE Monitoring von Pipelines als Referenzmessung für die Entwicklung eines akustischen faseroptischen Monitorings (AGIFAMOR)
2) Schwellwertfreie AE Messung im 4-Punkt-Rohrbiegeprüfstand BAM_9.1 (AGIFAMOR)
3) Kombination von AE mit Röntgen-Mikrotomografie und die Anwendung der frequenzbasierten Mustererkennung ermöglichen eine Zuordnung von AE und Mechanismen (Ergebnisse aus dem SNSF Projekt Nr. 127'134, Baensch 2014, Diss. ETH No. 22372)
For a better understanding of the damage of glued wood tensile tests on miniature specimens made of glued spruce wood with acoustic emission and in-situ synchrotron-based X-ray computer microtomography has been monitored. As adhesive, urea-formaldehyde resin was used. For comparison purposes, tensile tests were carried out on solid wood and bonded miniature tensile shear samples with acoustic emission. The acoustic emission signals of all experiments were with classified pattern recognition. This resulted in two classes of signals for each two frequency peaks. In one class was the low-frequency, in the other the higher frequency peak of higher intensity, but this essentially independent from the structure (solid wood or plywood) and the size scale of the test specimens. The influence of the adhesive layers was determined on plywood test specimens in laboratory scale and on miniature test specimens with an adhesive layer and selected fiber orientations examined. This gave evidence that the sound emission signals from the failure of the adhesive layer presumably of the class with low frequency signals peak in the range of services can be assigned.
To better understanding the failure of adhesive joints tensile tests were carried out on miniature test specimens from Norway spruce in the synchrotron. Urea-formaldehyde resin was used as adhesive. e. For comparison purposes, tensile tests were carried out on solid wood and on bonded miniature tensile shear samples with acoustic emission. The acoustic emission signals of all the experiments occurred with classified pattern recognition. This resulted in two classes of signals for each two frequency peaks. One class consisted of the low-frequency and the other of the higher-frequency peak of higher intensity, but this was essentially independent from the structure (solid wood or plywood) and size scale of the test specimens. The influence of the adhesive layers was determined on wood test specimens on laboratory scale and on miniature test specimens with an adhesive layer and selected fiber orientations. This gave evidence that the sound emission signals from the failure of the adhesive layer presumably of the class with low frequency signals peak in the range of services can be assigned.
Typically, the near-eutectic Al-Si alloys consist of highly interconnected three-dimensional network of the eutectic Silicon (Si) and intermetallics embedded into Aluminium (Al) matrix. For further improvement of the mechanical properties of such alloys, often, one single ceramic reinforcement phase, e.g. silicon carbide (SiC) or aluminium oxide (Al2O3) in the form of fibres or particles is added. However, hybrid reinforcements (fibres and particles) can further improve wear resistance and fracture toughness, and additionally, reduce anisotropy of the material. The engineering of metal matrix composites (MMC) for specific application requirements benefits from a comprehensive knowledge of the failure behaviour. Therefore, damage evolution under compression was investigated on:
- pure near-eutectic AlSi12CuMgNi matrix alloy
- type I: matrix reinforced with random-planar oriented Al2O3 short fibres (15 vol.%)
- type II: matrix reinforced with random-planar oriented Al2O3 short fibres (7 vol.%) and additional SiC particles (15 vol.%)
The analysis of damage mechanism was carried out in two rather independent but complementary studies. First, selected sister samples of every material were exposed to quasi-static compression (traverse control). The compression tests were interrupted at different strain levels. Miniature cylinders with a diameter of 1mm were extracted from the pre-strained samples and investigated by synchrotron computed tomography (SX-µCT) with a spatial resolution of about 0.7 µm. For the pure matrix alloy, microcracks are confined to the intermetallic particles and to the eutectic Si, hence no damage was observed in the Aluminium. The composite type II revealed a more effective strain accumulation (less damage) than type I at low plastic strain (up to 5 %), but a more catastrophic damage development due to cracking of the SiC clusters at higher strain levels.
The second approach to study the damage initiation and accumulation in the materials subjected to compressive load was Acoustic Emission (AE) analysis. In this case the in-situ monitoring of the acoustic emission signal was performed during compression tests on specimens with dimension of several mm. For all three material types, AE activity set at 2% strain. Differences in AE behaviour of the three materials was proven based on AE hitrate, signal peak amplitudes as well as weighted peak frequencies (WPF). Future work focuses on combination of AE and SX-µCT aiming for more detailed knowledge on damage mechanism of metal matrix composites.
Acoustic emission testing
(2018)
Additively manufactured test specimens made of polyamide 12 (PA 12) by Laser Sintering (LS) as well as of acrylnitril-butadien-styrol (ABS) by Fused Layer Modeling (FLM), were tested with active thermography. For this, two different excitation methods (flash and impulse excitation) were used and compared, regarding the suitability for the detection of constructed and imprinted defects. To increase the quality of the thermograms, data processing methods like thermal signal reconstruction (TSR) and Fourier-Transformation were applied. Furthermore, the long-term stability of the probes towards environmental stress, like UV-radiation, heat, water contact and frost is being investigated in the presented project with artificial weathering tests.
Additively manufactured test specimens made of polyamide 12 (PA 12) by Laser Sintering as well as of acrylonitrile butadiene styrene (ABS) by Fused Layer Modelling, were characterised with active thermography directly after manufacturing and after artificial weathering. For this, two different excitation methods (flash and pulse heating) were used and compared, regarding their suitability for the detection of constructed and imprinted defects inside the test specimens. To increase the quality of the thermograms, data processing methods like thermal signal reconstruction (TSR) and Fourier Transformation after TSR were applied. To further investigate the long-term stability of the additively manufactured test specimens towards environmental stress, like UV radiation, heat, humidity, water contact and frost with active thermography, an artificial weathering test over 2000 hours (~3 months) was applied to the specimens. The monitoring of the changes in the optical properties of the weathered plastics was supplemented by spectral reflectance and UV/VIS spectroscopy.
Es wird ein Verfahren zur Charakterisierung der Beständigkeit und Langzeitstabilität von additiv gefertigten Kunststoff-Bauteilen vorgestellt. Dabei sollen die Prüfkörper über 2000 Stunden künstlich bewittert und währenddessen die Änderungen der Eigenschaften der Bauteile zerstörungsfrei untersucht werden. Die Erkenntnisse dienen für die Entwicklung einer Strategie für eine Qualitätskontrolle von additiv gefertigten Kunststoffteilen.
Es wird ein Verfahren zur Charakterisierung der Beständigkeit und Langzeitstabilität von additiv gefertigten Kunststoff-Bauteilen vorgestellt. Dabei sollen die Prüfkörper über 2000 Stunden künstlich bewittert und währenddessen die Änderungen der Eigenschaften der Bauteile zerstörungsfrei untersucht werden.
Es wird ein Verfahren zur Charakterisierung der Beständigkeit und
Langzeitstabilität von additiv gefertigten Kunststoff-Bauteilen vorgestellt. Dabei sollen die Prüfkörper über 2000 Stunden künstlich bewittert und währenddessen die Änderungen der Eigenschaften der Bauteile zerstörungsfrei untersucht werden.
Additive manufacturing (AM) techniques have risen to prominence in many industrial sectors. This rapid success of AM is due to the freeform design, which offers enormous possibilities to the engineer, and to the reduction of waste material, which has both environmental and economic advantages. Even safety-critical parts are now being produced using AM. This enthusiastic penetration of AM in our daily life is not yet paralleled by a thorough characterization and understanding of the microstructure of materials and of the internal stresses of parts. The same holds for the understanding of the formation of defects during manufacturing. While simulation efforts are sprouting and some experimental techniques for on-line monitoring are available, still little is known about the propagation of defects throughout the life of a component (from powder to operando/service conditions). This Issue was aimed at collecting contributions about the advanced characterization of AM materials and components (especially at large-scale experimental facilities such as Synchrotron and Neutron sources), as well as efforts to liaise on-line process monitoring to the final product, and even to the component during operation. The goal was to give an overview of advances in the understanding of the impacts of microstructure and defects on component performance and life at several length scales of both defects and parts.
Austenitic stainless steel welds as well as dissimilar metal welds with nickel alloy filler material, used in safety relevant parts of nuclear power plants, still challenge the ultrasonic inspection. The weld material forms large oriented grains which lead on the one hand to high sound scattering and on the other hand – to inhomogeneity and to the acoustic anisotropy of the weld structure. The ultrasonic wave fronts propagate not linearly, as in ferritic weld joints, but along the curves, which depend on the specific grain structure of the weld. Due the influence of these phenomena, it is difficult to analyze the inspection results and to classify the ultrasonic indications, which could be both from the weld geometry and from the material defects. A correct flaw sizing is not possible.
In an ongoing research project, different techniques to improve the reliability of ultrasonic testing at these kinds of welds are investigated. In a first step (in the previous research project) two ultrasonic inspection techniques were developed and validated on plane test specimens with artificial and realistic flaws. In the ongoing project, these techniques are applied to circumferential pipe welds with longitudinal and transverse flaws.
The technique developed at the Federal Institute for Materials Research and Testing (BAM) in Germany uses a combination of ray tracing and synthetic aperture focusing technique (SAFT). To investigate the unknown grain structure, the velocity distribution of weld-transmitting ultrasound waves is measured and used to model the weld by ray tracing.
The second technique, developed at the Fraunhofer Institute for Nondestructive Testing (IZFP) in Germany, uses Sampling Phased Array (Full Matrix Capture) combined with the reverse phase matching (RPM) and the gradient elastic constant descent algorithm (GECDM). This inspection method is able to estimate the elastic constants of the columnar grains in the weld and offers an improvement of the reliability of ultrasonic testing through the correction of the sound field distortion. The unknown inhomogeneity and anisotropy are investigated using a reference indication and the special optimization algorithm.
Both reconstruction techniques give quantitative inspection results and allow the defect sizing. They have been compared to conventional ultrasonic testing with techniques, which are state of the art for components in nuclear power plants. The improvement will be quantified by the comparison of the probability of detection (POD) of each technique.
Austenitic stainless steel welds as well as dissimilar metal welds with nickel alloy filler material, used in safety relevant parts of nuclear power plants, still challenge the ultrasonic inspection. The weld material forms large oriented grains which lead on the one hand to high sound scattering and on the other hand – to inhomogeneity and to the acoustic anisotropy of the weld structure. The ultrasonic wave fronts propagate not linearly, as in ferritic weld joints, but along the curves, which depend on the specific grain structure of the weld. Due the influence of these phenomena, it is difficult to analyze the inspection results and to classify the ultrasonic indications, which could be both from the weld geometry and from the material defects. A correct flaw sizing is not possible.
In an ongoing research project, different techniques to improve the reliability of ultrasonic testing at these kinds of welds are investigated. In a first step (in the previous research project) two ultrasonic inspection techniques were developed and validated on plane test specimens with artificial and realistic flaws. In the ongoing project, these techniques are applied to circumferential pipe welds with longitudinal and transverse flaws.
The technique developed at the Federal Institute for Materials Research and Testing (BAM) in Germany uses a combination of ray tracing and synthetic aperture focusing technique (SAFT). To investigate the unknown grain structure, the velocity distribution of weld-transmitting ultrasound waves is measured and used to model the weld by ray tracing.
The second technique, developed at the Fraunhofer Institute for Nondestructive Testing (IZFP) in Germany, uses Sampling Phased Array (Full Matrix Capture) combined with the reverse phase matching (RPM) and the gradient elastic constant descent algorithm (GECDM). This inspection method is able to estimate the elastic constants of the columnar grains in the weld and offers an improvement of the reliability of ultrasonic testing through the correction of the sound field distortion. The unknown inhomogeneity and anisotropy are investigated using a reference indication and the special optimization algorithm.
Both reconstruction techniques give quantitative inspection results and allow the defect sizing. They have been compared to conventional ultrasonic testing with techniques, which are state of the art for components in nuclear power plants. The improvement will be quantified by the comparison of the probability of detection (POD) of each technique.
The additive manufacturing of low elastic modulus alloys that have a certain level of porosity for biomedical needs is a growing area of research. Here, we show the results of manufacturing of porous and dense samples by a laser powder bed fusion (LPBF) of Ti-Nb alloy, using two distinctive fusion strategies. The nanostructured Ti-Nb alloy powders were produced by mechanical alloying and have a nanostructured state with nanosized grains up to 90 nm. The manufactured porous samples have pronounced open porosity and advanced roughness, contrary to dense samples with a relatively smooth surface profile. The structure of both types of samples after LPBF is formed by uniaxial grains having micro- and nanosized features. The inner structure of the porous samples is comprised of an open interconnected system of pores. The volume fraction of isolated porosity is 2 vol. % and the total porosity is 20 vol. %. Cell viability was assessed in vitro for 3 and 7 days using the MG63 cell line. With longer culture periods, cells showed an increased cell density over the entire surface of a porous Ti-Nb sample. Both types of samples are not cytotoxic and could be used for further in vivo studies.
Laser powder bed fusion (LPBF) is an additive manufacturing process for materials which inherently tends to yield various degrees of metastable hierarchical microstructures, defects and high residual stresses in the as-built condition depending on the process parameters. The understanding of the evolution of these typical features during heat treatment and subsequent thermal and mechanical ageing is crucial for the wider acceptance for safety critical structures. A multi-disciplinary research project at BAM studying the development of the microstructure, defects, residual stresses typical of LPBF 316L and their evolution during thermal and mechanical ageing has led to insights into the stability of these inherent features. This presentation aims to give a broad overview of the project with a few specific cases of investigation. Firstly, the formation of residual stresses, the nature of the initial microstructure, the tensile properties and a modelling approach to understand the anisotropy will be presented. This will be followed by examples of studies of their evolution during heat treatment, long term thermal exposure, and room temperature and high temperature mechanical testing compared to a baseline of conventional wrought variant of the same alloy.
An overview of the BAM funed Focus Area Materials Project "AGIL" will be presented. AGIL focussed on the stdiy of the ageing characteristics of additively manufactured austenitic stainless steel with a "powder to mechanical failure" Approach. Recent Highlights are presented and a perspective for future studies.
Modern and energy-efficient materials are essential for innovative designs for aerospace and automotive industries. Current technologies for rapid manufacturing such as additive manufacturing and liquid composite moulding by polymer Extrusion allow innovative ways of creating robust and lightweight constructions. Commercially available printing devices often use polylactide (PLA) or acrylonitrile butadiene styrene (ABS) as raw material. Therefore, parameters like the infill ratio, influencing the ability to resist mechanical stress, may have a beneficial impact on the lifetime of components.
These manufacturing technologies require a good knowledge about materials and even adapted non-destructive testing technologies and methods. Airborne ultrasonic testing has beneficial advantages for testing those lightweight constructions. It is a contact-free testing method, which does not require a liquid couplant. Therefore, it allows fast test cycles without any unwanted alternations of the material properties due to interactions with any coupling liquid. This contribution deals with the characterisation of printed specimens based on PLA by using airborne ultrasound and presents the current edge of non-destructive testing and evaluation using airborne ultrasonic transducers. The specimens, manufactured by polymer extrusion, are printed as thin plates. The infill ratio, as well as the material thickness, were varied to model density imperfections with different geometric shapes and properties. For better understanding of the limits of airborne ultrasonic testing in transmission, we compared own-developed transducers based on different physical principles: on ferroelectrets, on the thermoacoustic effect, as well as a new type of transducers based on gas discharges.
Die zerstörungsfreie Prüfung von metallischen Bauteilen hergestellt mit additiver Fertigung (Additive Manufacturing - AM) gewinnt zunehmend an industrieller Bedeutung. Grund dafür ist die Feststellung von Qualität, Reproduzierbarkeit und damit auch Sicherheit für Bauteile, die mittels AM gefertigt wurden. Jedoch wird noch immer ex-situ geprüft, wobei Defekte (z.B. Poren, Risse etc.) erst nach Prozessabschluss entdeckt werden. Übersteigen Anzahl und/oder Abmessung die vorgegebenen Grenzwerte für diese Defekte, so kommt es zu Ausschuss, was angesichts sehr langer Bauprozessdauern äußerst unrentabel ist. Eine Schwierigkeit ist dabei, dass manche Defekte sich erst zeitverzögert zum eigentlichen Materialauftrag bilden, z.B. durch thermische Spannungen oder Schmelzbadaktivitäten. Dementsprechend sind reine Monitoringansätze zur Detektion ggf. nicht ausreichend.
Daher wird in dieser Arbeit ein Verfahren zur aktiven Thermografie an dem AM-Prozess Laser Powder Bed Fusion (L-PBF) untersucht. Das Bauteil wird mit Hilfe des defokussierten Prozesslasers bei geringer Laserleistung zwischen den einzelnen gefertigten Lagen unabhängig vom eigentlichen Bauprozess erwärmt. Die entstehende Wärmesignatur wird ort- und zeitaufgelöst durch eine Infrarotkamera erfasst. Durch diese der Lagenfertigung nachgelagerte Prüfung werden auch zum Bauprozess zeitversetzte Defektbildungen nachweisbar.
In dieser Arbeit finden die Untersuchungen als Proof-of-Concept, losgelöst vom AM-Prozess, an einem typischen metallischen Testkörper statt. Dieser besitzt eine Nut als oberflächlichen Defekt. Die durchgeführten Messungen finden an einer eigens entwickelten L-PBF-Forschungsanlage innerhalb der Prozesskammer statt. Damit wird ein neuartiger Ansatz zur aktiven Thermografie für L-PBF erforscht, der eine größere Bandbreite an Defektarten auffindbar macht. Der Ansatz wird validiert und Genauigkeit sowie Auflösungsvermögen geprüft. Eine Anwendung am AM-Prozess wird damit direkt forciert und die dafür benötigten Zusammenhänge werden präsentiert.