5 Werkstofftechnik
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Metal additive manufacturing (Metal AM) continues to gain momentum. Many companies explore the manufacturing of innovative products, including components for safety critical applications. Despite the intensive research of recent years, a fundamental understanding of the process‑structure‑property relationships remains challenging due to, i.a., the inherently complex and highly hierarchical microstructures arising from the wide range of build process parameter variability. This contribution presents the resu lts of an experimental study on the creep behavior of an austenitic 316L stainless steel produced by laser powder bed fusion (PBF LB/M/316L) with an emphasis on understanding the effects of microstructure on creep mechanisms. Hot tensile tests and constant force creep tests at 600 °C and 650 °C, X ray computed tomography, as well as optical and electron microscopy were performed. The produced PBF LB/M/316L exhibits a low void population 0.01 %) resulting from the manufacturing parameters used and which a llowed us to understand the effects of other microstructural aspects on creep behavior, e.g., grain morphology and dislocation substructure. A hot‑rolled variant of 316L hwas also tested as a reference. The produced PBF LB/M/316L possesses shorter primary and secondary creep stages and times to rupture and smaller creep stress exponents than the hot‑rolled variant. Overall, the creep damage is more extensive in the PBF LB/M/316L and is characterized as predominantly intergranular. It is considered that the damage behavior is mainly impacted by the formation of precipitates at the grain boundaries combined with their unfavorable orientation. The dislocation substructure and local elemental segregation appear to have a decisive impact on the overall creep behavior.
In times of digital data processing and sharing, a central challenge for the Materials Science and Engineering (MSE) community is the complete digital representation of materials, including their relevant processing and microstructure details and the resulting properties. This digital representation, supported by digital infrastructures, enables entirely new qualities of collaborative work and is central to how we will conduct MSE research and develop products in the future. The main challenges are the composition, shaping, and description of the data so that it can be easily interpreted, trusted, and re-used. This presentation introduces our current effort to develop a best practice framework for generating and distributing creep reference datasets for Ni-based superalloys, which builds on previous approaches. Researchers can use such datasets to compare their own experimental or simulation results, used, for instance, to perform simulation-based alloy design and optimization or in the verification of the own testing equipment. The concept includes building an easily accessible digital infrastructure to annotate and discover the datasets and the integration of an ontology that aligns with the necessary metadata schema. With the help of an ontology, the reference dataset for creep can be semantically described, thus enabling the digital representation and reusage of shared concepts from domain experts and the community. To achieve this, it is necessary to establish a defined vocabulary with corresponding relations and annotations. The interplay between a digital infrastructure, the agreement on the necessary metadata and related metadata schema, and an underlying ontology will ensure that data and results can be easily shared, taken up, and re-used, thus fulfilling the FAIR principles (Findable, Accessible, Interoperable, Reusable). Furthermore, we aim to develop a widely accepted definition of reference data and data quality levels and to reach a self-supported community process. We intend to motivate the discussion about reference material datasets, necessary metadata, and future collaborations within the creep community.
Non-equilibrium microstructure evolution in additive manufacturing (AM) is a major barrier for establishing a safe and sustainable application of AM in industrial processes. The constant heat source in the AM continuously affects the just-solidified grains beneath the melting pool, leading to directional grain growth (DGG). While real-time measurements of the non-equilibrium microstructure evolution is challenging, here developing a computational framework to systematically explore DGG becomes imperative.
We have advanced a comprehensive approach, integrating mean-field modeling and phase-field simulations, to elucidate the dynamics of DGG under an external driving force. Our simulations unveil a steady-state power-law grain growth kinetics during DGG, characterized by the interplay between curvature-driven dynamics at grain boundary junctions and directional driving forces.
Low-Temperature High Stress (LTHS) creep plays a crucial role in Ni-base Superalloys, particularly affecting components like blades near the root. Below 850°C, the precipitate microstructure remains stable, characterized by periodically arranged ’ cubic precipitates surrounded by the -matrix. In these conditions, macroscopic traces of cubic slip have been observed in <111> oriented tensile specimens, whereas their microscopic origin has been a topic of debate. Furthermore, in LTHS conditions, Superlattice Intrinsic, Extrinsic Stacking Faults (SISF/SESF), or micro-twins are also frequently reported in crept specimens. Usually, these mechanisms are investigated separately, so that a unified picture and a detailed understanding of these mechanisms and their activation conditions have only recently emerged in the literature, despite the intensive investigations of the last decades.
The objective of this work is to develop a dislocation-based constitutive law that includes these recent developments. In particular, the pseudo-cubic slip mechanism is considered as resulting from the lack of hardening in <111> oriented tensile specimens and is represented by a novel estimate of the back-stresses based on the spectral decomposition of a tensorial representation of the back-stress. An additional novelty is that SISF- and SESF-related slip systems are accounted for as distinct slip systems with corresponding dislocation densities. The model has been implemented as a user-defined constitutive law for commercial Finite Element codes and identified as well as validated with data from the literature obtained with <001>, <011> and <111> oriented crystals tested in tension and compression creep.
Grain boundary embrittlement in medium-Mn steels and liquid metal embrittlement (LME) in Zn-coated high strength steels are among key challenges on the way of safe application of sustainable steels for automotive industry. Using a novel density-based model for grain boundaries, we reveal that the affinity of a grain boundary to attract Mn and Zn atoms result in a segregation transition accompanied by interfacial structural changes. In case of the Zn, the simulations show that the amount of segregation abruptly increases with decreasing temperature, while the Zn content in the alloy, required for triggering the segregation transition, decreases. The results are discussed in the context of CALPHAD-integrated density-based grain boundary phase diagrams.
This talk addresses aging induced property changes of metallic glasses. Priority is given thermally and mechanically induced structural changes, of which the time-dependent dynamics is tracked using coherent scattering. Strong intermittency is observed and accelerated transport is seen at the smallest applied stresses. These findings have significant implications for how metallic glass components respond in realistic service conditions.
Following the new paradigm of materials development, design and optimization, digitalization is the main goal in materials sciences (MS) which imposes a huge challenge. In this respect, the quality assurance of processes and output data as well as the interoperability between applications following FAIR (findability, accessibility, interoperability, reusability) principles are to be ensured. For storage, processing, and querying of data in contextualized form, Semantic Web Technologies (SWT) are used since they allow for machine-actionable and human-readable knowledge representations needed for data management, retrieval, and (re)use.
In this respect, the motivation for digital transformation in materials sciences stemming from the need to handle the ever-increasing volume and complexity of data will be elaborated on. By embracing digital tools and methodologies, researchers can enhance the efficiency, accuracy, and reproducibility of their work. The benefits of digital transformation in materials sciences are manifold, including improved data management, enhanced collaboration, and accelerated innovation. Being a core component of this transformation, ensuring data reliability and reproducibility is critical for the advancement of the field, enabling researchers to build on each other's work with confidence. Implementing FAIR data principles facilitates this by making data more accessible and usable across different platforms and studies. Furthermore, Semantic Web technologies (SWT) and ontologies play a crucial role in achieving these goals. Ontologies, typically consisting of the T-Box (terminological component) and A-Box (assertional component), provide a structured framework for representing knowledge. This presentation will outline the path of ontology creation and the formal transformation procedure, highlighting the various ontology levels that organize data into meaningful hierarchies.
Real-world use cases presented, such as the Tensile Test Ontology (TTO) and the Orowan Demonstrator, illustrate the practical applications of these technologies. These examples will demonstrate how ontologies can be leveraged to standardize data and facilitate interoperability between different systems and research groups. Finally, in this presentation, Ontopanel is introduced, a tool designed to aid in the creation and management of ontologies. Ontopanel simplifies the process of developing and maintaining ontologies, making it accessible to researchers and practitioners in the field. By integrating these technologies and principles, the materials science community can move towards a more digital, interconnected, and efficient future making the knowledge and education on these topics very valuable.
Intermittent microplasticity via dislocation avalanches indicates scale-invariance, which is a paradigm shift away from traditional bulk deformation. Recently, we have developed an experimental method to trace the spatiotemporal dynamics of correlated dislocation activity (dislocation avalanches) in microcrystals (Phys. Rev. Mat. 2 (2018) 120601; Phys. Rev. Mat. 3 (2019) 080601). Here we exploit the temperature sensitive deformation of bcc metals. A marked change of the slip-size distribution is observed in the studied microcrystals, with increasingly small event-sizes dominating with decreasing temperature. This shows how a reduction in thermal energy increasingly suppresses the length-scale of dislocation avalanches, indicating how long-range correlations become gradually limited to the scale of the lattice. Our results further show that the stress-strain response is composed of strain-increments that are either thermally activated or essentially athermal. Temperature-dependent small-scale testing in combination with state-of-the-art discrete dislocation dynamics (DDD) simulations of Nb microcrystals are used to reveal these insights.
Quenching a metallic liquid sufficiently fast can give rise to an amorphous solid, typically referred to as a metallic glass. This out-of-equilibrium material has a long suite of remarkable mechanical and physical properties but suffers from property deterioration via structural relaxation. As a function of time, relaxation may indeed constitute significant threads to safe applications. Consequently, relaxation of glasses has a long history across different amorphous materials and typical characterization methods promote a picture of gradually evolving and smooth relaxation, as for example obtained from mechanical spectroscopy. However, the true structural dynamics and underlying mechanisms remain far from understood and have hampered a physically informed atomic-scale picture of transport and physical aging of glasses.
Here we exploit the ability to track atomic-scale dynamics with x-ray photon correlation spectroscopy (XPCS) and resolve an unprecedented spectrum of short- and long-term relaxation time scales in metallic glasses. Conducted across temperatures and under the application of stress, the results reveal anything else than smooth aging and gradual energy minimization. In fact, temporal fluctuations persist throughout isothermal conditions over several hundred thousand of seconds, demonstrating heterogeneous dynamics at the atomic scale. In concert with microsecond molecular dynamic simulations, we identify possible mechanisms of correlated atomic-scale dynamics that can underly the temporal fluctuations and structural decorrelations. Despite temporally heterogeneous, the Kohlrausch-Williams-Watts functions is well suited to capture the average intermediate relaxation time regime, but at very long time scales an asymptotic power-law emerges. This indicates anomalous diffusion and gives overall strong evidence for temporal fractional diffusion in metallic glasses. We discuss these results in terms of the structural fast and slow relaxation modes as well as a true microstructure in metallic glasses.
Inspired by the ability to track atomic-scale dynamics with x-ray photon correlation spectroscopy (XPCS)1 and recent results of long-term atomistic simulations on material transport2, we reveal here an unprecedented spectrum of short- and long-term relaxation dynamics. Tracked along a 300 000 s long isotherm at 0.98Tg, a Zr-based bulk metallic glass exhibits temporal fluctuations that persist throughout the entire isotherm, demonstrating a continuous heterogeneous dynamics at the probed length scale. In concert with microsecond molecular dynamic simulations, we identify intermittent cluster dynamics as the origin for temporal signatures in the corresponding intensity cross-correlations. Despite temporally heterogeneous aging, the Kohlrausch-Williams-Watts functions is well suited to capture the average intermediate relaxation time regime, but at very long time scales an asymptotic power-law better describes the data. This indicates anomalous diffusion and gives overall strong evidence for temporal fractional diffusion in metallic glasses. We discuss these results in terms of the underlying structural fast and slow relaxation modes and their manifestation in the temporal form of the structural decorrelations.
Metallic glasses (MGs) are disordered solids that exhibit a range of outstanding mechanical, thermomechanical, and functional properties. Whilst being a promising class of structural materials, well-defined and exploitable structure-property relationships are still lacking. This offsets them strongly from the crystalline counterparts, for which length-scale based property determination has been key for decades.
In recent years, both atomistic simulations and experiments have nurtured the view of heterogeneities that manifest themselves either as a structural partitioning into well-relaxed percolated network components and more frustrated domains in atomistic simulations, or as spatially-resolved property fluctuations revealed with atomic force microscopy. These signatures depend sensitively on the processing history and likely reflect emerging medium-range order fluctuations at the scale of 1-10 nanometers.
Here we demonstrate and discuss the emergence of spatially resolved property fluctuations at length scales that are one to two orders of magnitude larger. Such long-range decorrelation length scales are hard to reconcile in a monolithic glass but may offer the perspective of experimentally easy-to-access length-scale based structure-property relationships. Whilst long-range property fluctuations can be seen in both the plastic and elastic response, we focus here on high-throughput elastic nanoindentation mapping across the surface of a Zr-based model glass. After a deconvolution of surface topography and curvature effects, the spatially-resolved elastic response reveals an elastic microstructure with a correlation length of ca. 150-170 nm. Analytical scanning-transmission electron microscopy (STEM) is used to link the elastic property fluctuations to the chemistry and structure of the MG. In concert, nano-elastic mapping and STEM suggests that structural variations in the glass are responsible for the unexpectedly large length scales. We discuss these findings in terms of the materials processing history and the perspective of exploiting nanoindentation-based spatial mapping to uncover structural length scales in atomically disordered solids.
Advanced light weight applications like aircrafts and wind turbine blades are made of fibre reinforced plastics (FRP) with continuous fibre reinforcement and must withstand a high thermo-mechanical cyclic loading. The quality of the fibre matrix interface has a high impact on the fatigue life and was continuously improved over the years since the 50th. The fatigue life of glass fibre reinforced plastics (GFRP) used in aircraft industry is 10 to 100 times higher compared to glass fibre non crimp fabrics used for wind turbine blades.
To assure a constant and reliable high quality and strength of reinforcement fibres, synthetic fibre production is state of the art (CF, GF). There is a need for recycling GFRP and CFRP waste due to the upcoming use. Pyrolysis and solvolysis are more expensive than the mechanical route however enable a more sustainable recycling. Natural fibres and recycled synthetic fibres have a high scatter in quality and strength. Hence it is a challenge to optimize the production / recycling processes to get a reliable quality for any demanding (second life) application.
Chemical routes for using renewables resources and recycling, is going to be a good approach especially for polymer-matrix systems to get 100% quality (back) compared to the state of the art.
Finally, a proper design, life-time extension and repair is preferable to recycling to keep the carbon footprint as low as possible.
The BAMline at the synchrotron X-ray source BESSY II (Berlin, Germany) is supporting researchers especially in materials science [1]. As a non-destructive characterization method, synchrotron X-ray imaging, especially tomography (SXCT) with hard X-Rays, plays an important role in structural 3D characterization. The imaging capabilities allow for in-situ and operando experiments. In this presentation the equipment, data handling pipeline as well as various examples from material science are presented.
In series-connected lithium-ion cells are susceptible to an electrical safety hazard called over-discharge. Here the behavior of copper dissolution and deposition during over-discharge is presented, which leads to irreversible loss of capacity and internal short circuits. The concentration of dissolved and deposited copper is quantified. Also, a non-uniform distribution pattern of copper deposition on the cathode is shown.
The second example deals with an Al alloy 7017 customized for a 3d-printing process by means of laser-based powder bed fusion (PBF-LB) technique. These advanced alloys have a significantly higher modulus of elasticity than conventional Al alloys, making them attractive for applications requiring high stiffness. SXCT during In-situ tensile tests confirmed that fracture initiation strongly depends on defects created during printing. However, the cracks are deflected from decohesion around inclusions/precipitates embedded in the Al matrix, increasing ductility.
Low temperature cofired ceramic (LTCC) multilayer housings offer 3D-circuits for a wide range of applications in telecommunications, microsystems and sensor technology. Such housings are produced by combining structured and metallized ceramic layers using tape-casting and multilayer technology. The characterization of the integrity, deformation, defects, and positioning of the internal metal features was carried out using in-situ SXCT at up to 950°C.
A high-precision nail penetration tool was developed to characterize the mechanically induced thermal runaway (TR) of lithium-ion battery (LIB) cells in a dynamic temperature range down to -190 °C. To investigate safety-specific low-temperature transport conditions, the damaged cells were tomographically imaged during thawing.
Planning an academic career is a bit like enjoying a box of chocolate – you never know what you are going to get next. In this talk, I will begin with sharing how luck, difficult decisions, fate, and family constraints affected my career path across continents, universities, the private sector, and to becoming a director at a national laboratory. This journey was certainly not planned and highlights how opportunities and compromises together allow you to make much more out of your engineering degree than you ever have dreamed of.
After this unusual journey as a materials scientist, I am transitioning to the technical part of my talk, where we will discuss transport in metallic glasses. This out-of-equilibrium material has a long suite of remarkable mechanical and physical properties but suffers from property deterioration via physical aging. As a function of time, relaxation may indeed constitute significant threads to safe applications, such as a complete loss of toughness.
In the search for a physical understanding of aging, we exploit here the ability to track atomic-scale dynamics with coherent x-ray scattering. Conducted across temperatures and under the application of stress, the results reveal unexpected transport. In concert with microsecond molecular dynamic simulations, we identify possible mechanisms of atomic-scale dynamics that underly physical aging of metallic glasses. We find that classical Kohlrausch-Williams-Watts behavior is only suited for the short relaxation-time regime, whereas anomalous diffusion emerges at practically relevant times. We discuss these results in terms of the structural relaxation modes and propose a picture of a true microstructure in metallic glasses.
Plastic deformation in crystals is mediated by the motion of line defects known as dislocations. For decades, dislocation activity has been treated as a homogeneous, smooth continuous process that relies on well-average quantities. However, it is now recognized that plasticity can be determined by long-range correlated and intermittent collective dislocation activity, known as avalanches. These abrupt plastic fluctuations often exhibit pure power-law scaling or truncated power-law scaling, which indicates at least some degree of scale-free dislocation behavior. Intriguingly, such statistical signatures can persist across scales exceeding those of the material’s microstructure, raising the question of what relationship there may be between structure and long-range correlated dislocation activity that underlie power-law scaling.
In this talk, we address this question by highlighting examples in which a transition from scale-free to scale-dependent plastic deformation is observed either due to changing external testing conditions (stress-state or temperature) or by tuning the microstructure. In particular, we will focus on the details of the temperature-driven change, that demonstrates how scale-free intermittent flow in body-centered cubic Nb is progressively quenched out with decreasing temperature. The plastic response of Nb is shown to be bimodal across the studied temperature regime, with conventional thermally-activated smooth plastic flow coexisting with sporadic bursts controlled by athermal screw dislocation activity, thereby violating the classical notion of temperature-dependent screw dislocation motion at low temperatures. An abrupt increase of the athermal avalanche component is identified at the critical temperature of the material. We combine the experimental observations with 3D dislocation dynamics simulations, identify a possible origin to athermal screw activity, and discuss the co-existence scale-free and scale-dependent plasticity.
One contribution of materials science to energy efficiency is the continuous development of novel high-performance structural materials that push the strength-ductility envelope. A prominent example are modern advanced high-strength steels (AHSSs), which have enabled considerable weight reductions in the automotive sector, thereby enabling greenhouse emission reductions. To protect such advanced alloys from property degradation via corrosion, zinc (Zn) coatings are often applied through galvanization. Whilst protective, a Zn-coating comes with problems – the AHSS substrate becomes susceptible for liquid-metal embrittlement (LME) than can be the origin of significant mechanical property degradation when liquified Zn infiltrates into the steel substrate. Being for from understood, we focus here on non-cracked environments to capture the early stages of LME. This approach revealed the nucleation and growth of nano-scale intermetallic phases inside uncracked GBs (Materials Today Advances 13, 100196, 2022), highlighting the complex multi-phase microstructure developing before cracking occurs. To shed further light on the early stages of LME in AHSSs, we also consider the microstructural evolution of interrupted welds. We discuss our findings in the context of the time-resolved substructure evolution right beneath the interface between the AHSS and the Zn-based coating and track how Zn progressively infiltrates the substrate along phase and grain boundaries. The experimental results are further corroborated with thermodynamic simulations.
Fatigue test ontology (FTO)
(2024)
Fatigue Test Ontology (FTO) has developed for representing the fatigue testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 12106 standard.
Versions info:
V2 developed using PROVO+PMDco top-level ontologies.
V3 developed using BFO+IOF top-level ontologies.
Repositories:
GitLab: https://gitlab.com/kupferdigital/process-graphs/lcf-test
GitHub: https://github.com/HosseinBeygiNasrabadi/Fatigue-Test-Ontology-FTO-
MatPortal: https://matportal.org/ontologies/FTO
IndustryPortal: https://industryportal.enit.fr/ontologies/FTO
Tensile Stress Relaxation Test Ontology (TSRTO) has developed for representing the tensile stress relaxation testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 10319-1 standard.
Versions info:
V1 developed using BFO+CCO top-level ontologies.
V3 developed using PROV+PMDco top-level ontologies.
Repositories:
GitLab: https://gitlab.com/kupferdigital/process-graphs/relaxation-test
GitHub: https://github.com/HosseinBeygiNasrabadi/Tensile-Stress-Relaxation-Test-Ontology-TSRTO
MatPortal: https://matportal.org/ontologies/TSRTO
IndustryPortal: https://industryportal.enit.fr/ontologies/TSRTO
Tensile test ontology (TTO)
(2024)
Tensile Test Ontology (TTO) has developed for representing the Tensile testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 6892-1 standard.
Versions info:
V2 developed using BFO+CCO top-level ontologies.
V3 developed using PROVO+PMDco top-level ontologies.
Repositories:
GitLab: https://gitlab.com/kupferdigital/process-graphs/tensile-test
GitHub: https://github.com/HosseinBeygiNasrabadi/Tensile-Test-Ontology-TTO-
MatPortal: https://matportal.org/ontologies/TTO
IndustryPortal: https://industryportal.enit.fr/ontologies/TTO
Vickers test ontology (VTO)
(2024)
Vickers Test Ontology (VTO) has developed for representing the Vickers testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 6507-1 standard.
Versions info:
V2 developed using BFO+CCO top-level ontologies.
Repositories:
GitLab: https://gitlab.com/kupferdigital/process-graphs/vickers-hardness-test
GitHub: https://github.com/HosseinBeygiNasrabadi/Vickers-Test-Ontology-VTO-
MatPortal: https://matportal.org/ontologies/VTO
IndustryPortal: https://industryportal.enit.fr/ontologies/VTO
Brinell test ontology (BTO)
(2024)
Brinell Test Ontology (BTO) has developed for representing the Brinell testing process, testing equipment requirements, test pieces charactristics, and related testing parameters and their measurement procedure according to DIN EN ISO 6506-1 standard.
Versions info:
V2 developed using BFO+CCO top-level ontologies.
V3 developed using EMMO+CHAMEO top-level ontologies.
V4 developed using PROVO+PMDco top-level ontologies.
V5 developed using BFO+IOF top-level ontologies.
Repositories:
GitLab: https://gitlab.com/kupferdigital/process-graphs/brinell-hardness-test
GitHub: https://github.com/HosseinBeygiNasrabadi/Brinell-Test-Ontology-BTO-
MatPortal: https://matportal.org/ontologies/BTO
IndustryPortal: https://industryportal.enit.fr/ontologies/BTO
Due to the advantages of Laser Powder Bed Fusion (PBF-LB), i.e., design freedom and the possibility to manufacture parts with filigree structures, and the considerable amount of knowledge available for 316L in its conventional variant, the mechanical behavior, and related microstructure-property relationships of PBF-LB/316L are increasingly subject of research. However, many aspects regarding the - application-relevant - mechanical behavior at high temperatures are not yet fully understood. Here, we present the results of an experimental study on the LCF behavior of PBF-LB/316L featuring a low defect population, which makes this study more microstructure-focused than most of the studies in the literature. The LCF tests were performed between room temperature (RT) and 600 °C. The mechanical response is characterized by strain-life curves, and hysteresis and cyclic deformation curves. The damage and deformation mechanisms are studied with X-ray computed tomography, and optical and electron microscopy. The PBF-LB/M/316L was heat treated at 450 °C for 4 h, and a hot‑rolled (HR) 316L variant with a fully recrystallized equiaxed microstructure was tested as a reference. Besides, selected investigations were performed after a subsequent heat treatment at 900 °C for 1 h. The PBF-LB/316L exhibits higher cyclic stresses than HR/316L for most of the fatigue life, especially at room temperature. At the smallest strain amplitudes, the fatigue lives of PBF-LB/M/316L are markedly shorter than in HR/316L. The main damage mechanisms are multiple cracking at slip bands (RT) and intergranular cracking (600 °C). Neither the melt pool boundaries nor the gas porosity have a significant influence on the LCF damage mechanism. The cyclic stress-strain deformation behavior of PBF-LB/M/316L features an initial hardening followed by a continuous softening. The additional heat treatment at 900 °C for 1 h led to decreased cyclic stresses, and a longer fatigue life.
The strength of age-hardenable aluminum alloys is based on the controlled formation of nm-sized precipitates, which represent obstacles to dislocation movement. Transmission electron microscopy (TEM) is generally used to identify precipitate types and orientations and to determine their size. This geometric quantification (e.g., length, diameter) is often performed by manual image analysis, which is very time consuming and sometimes poses reproducibility problems. The present work aims at the digital representation of this characterization method by proposing an automatable digital approach. Based on DF-TEM images of different precipitation states of alloy EN AW-2618A, a modularizable digital workflow is described for the quantitative analysis of precipitate dimensions. The integration of this workflow into a data pipeline concept is also presented. The semantic structuring of data allows data to be shared and reused for other applications and purposes, which enables interoperability.
The influence of test temperature and frequency on the fatigue life of the alloy EN AW-2618A (2618A) was characterized. The overaged condition (T61 followed by 1000 h/230 °C) was investigated in load-controlled tests with a stress ratio of R = -1 and two test frequencies (0.2 Hz, 20 Hz) at room temperature and at 230°C, respectively. An increase in the test temperature reduces fatigue life, whereby this effect is more pronounced at lower stress amplitudes. Decreasing the test frequency in tests at high temperatures further reduces the service life.
Modern high-pressure H2 tanks consist of fiber-reinforced composite materials and a plastic lining on the inside. The use of glass would drastically increase the H2 barrier effect. This could be achieved with glass liners or fiber-reinforced polymer-bonded glass capillary storage tanks and would enable lower wall thicknesses, higher gravimetric storage densities and variable designs and thus a much more effective use of space.
However, the decisive material parameters for the development of these technologies, such as the hydrogen permeation, are unknown. This study focuses on H2 diffusion in glasses of different chemical compositions.
H2 permeation is measured by mass spectrometry. For this purpose, the mass spectrometer (MS), which is located in a high vacuum, is separated from the pressure side by the test specimen. Pure H2 gas is present on the pressure side, so that the mass flow is recorded qualitatively and quantitatively in the MS. The permeation coefficients are calculated from the sample geometry and the mass flow rates. The very low H2 permeation of glass is measured on bundles of thin-walled commercially available glass capillaries and compared with the hydrogen permeation data of the glass powder method.
Optical glasses and glass ceramics are present in many devices often used in our daily routine, such as the mobile phones and tablets. Since the 1960´s with the development of glass lasers, and more recently, within the search for efficient W-LEDs, sensors and solar converters, this class of materials has experienced extreme research progress. In order to tailor a material for such applications, it is very important to understand and characterize optical properties such as refractive index, transmission window, absorption and emission cross sections, quantum yields, etc. These properties can often be tuned by appropriate compositional choice and post-synthesis processing. In this lecture we will discuss the optical properties of glasses and glass ceramics, relevant to that end.
Following the new paradigm of materials development, design and optimization, digitalization is the main goal in materials sciences (MS) which imposes a huge challenge. In this respect, the quality assurance of processes and output data as well as the interoperability between applications following FAIR (findability, accessibility, interoperability, reusability) principles are to be ensured. For storage, processing, and querying of data in contextualized form, Semantic Web Technologies (SWT) are used since they allow for machine-understandable and human-readable knowledge representations needed for data management, retrieval, and (re)use.
The project ‘platform MaterialDigital’ (PMD) is part of an initiative that aims to bring together and support interested parties from both industrial and academic sectors in a sustainable manner in solving digitalization tasks and implementing digital solutions. Therefore, the establishment of a virtual material data space and the systematization of the handling of hierarchical, process-dependent material data are focused. Core points to be dealt with are the development of agreements on data structures and interfaces implemented in distinct software tools and to offer users specific added values in their projects. Furthermore, the platform contributes to a standardized description of data processing methods in materials research. In this respect, selected MSE methods are ontologically represented which are supposed to serve as best practice examples with respect to knowledge representation and the creation of knowledge graphs used for material data.
Accordingly, this presentation shows the efforts taken within the PMD project to store data in accordance with a testing standard compliant ontological representation of a tensile test of metals at room temperature (ISO 6892-1:2019-11). This includes the path from developing an ontology in accordance with the respective standard up to connecting the ontology and data. The semantic connection of the ontology and data leads to interoperability and an enhanced ability of querying. For further enhanced reusability of data and knowledge from synthesis, production, and characterization of materials, the PMD core ontology (PMDco) was developed as mid-level ontology in the field of MSE. The semantic connection of the tensile test ontology (TTO) to the PMDco leads to enhanced expressivity and interoperability.
Moreover, as a best practice example, generation and acquisition of test data semantically connected to the ontology (data mapping) was realized by applying an electronic laboratory notebook (ELN). Corresponding tensile tests were performed by materials science students at university. This enabled a fully digitally integrated experimental procedure that can be transferred to other test series and experiments. In addition to facilitating the acquisition, analysis, processing, and (re)usability of data, this also raises the awareness of students with respect to data structuring and semantic technologies in the sense of education and training. The entire data pipeline is further seamlessly integrable in a laboratory information management system (LIMS). More specifically, the integration of semantic conceptualization and knowledge graphs may become essential parts in LIMS as this would be very beneficial. Therefore, some first approaches of SWT integration in LIMS will also be presented briefly.
The digital era has led to a significant increase in innovation in scientific research across diverse fields and sectors. Evolution of data-driven methodologies lead to a number of paradigm shifts how data, information, and knowledge is produced, understood, and analyzed. High profile paradigm shifts in the field of materials science (MS) include exploitative usage of computational tools, machine learning algorithms, and high-performance computing, which unlock novel avenues for investigating materials. In these presentations, we highlight prototype solutions developed in the context of the Platform MaterialDigital (PMD) project that addresses digitalization challenges. As part of the Material Digital Initiative, the PMD supports the establishment of a virtual materials data space and a systematic handling of hierarchical processes and materials data using a developed ontological framework as high priority work items. In particular, the mid-level ontology PMDco and its augmentation through application-specific ontologies are illustrated. As part of the conclusion, a discussion encompasses the evolutionary path of the ontological framework, taking into account standardization efforts and the integration of modern AI methodologies such as natural language processing (NLP). Moreover, demonstrators illustrated in these presentations highlight: The integration and interconnection of tools, such as digital workflows and ontologies, Semantic integration of diverse data as proof of concept for semantic interoperability, Improved reproducibility in image processing and analysis, and Seamless data acquisition pipelines supported by an ontological framework. In this context, concepts regarding the application of modern research data management tools, such as electronic laboratory notebooks (ELN) and laboratory information management systems (LIMS), are presented and elaborated on. Furthermore, the growing relevance of a standardized adoption of such technologies in the future landscape of digital initiatives is addressed. This is supposed to provide an additional basis for discussion with respect to possible collaborations.
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.
Digital Transformation in Materials Science: Insights From the Platform MaterialDigital (PMD)
(2024)
The digital era has led to a significant increase in innovation in scientific research across diverse fields and sectors. Evolution of data-driven methodologies lead to a number of paradigm shifts how data, information, and knowledge is produced, understood, and analyzed. High profile paradigm shifts in the field of materials science (MS) include exploitative usage of computational tools, machine learning algorithms, and high-performance computing, which unlock novel avenues for investigating materials. In these presentations, we highlight prototype solutions developed in the context of the Platform MaterialDigital (PMD) project that addresses digitalization challenges. As part of the Material Digital Initiative, the PMD supports the establishment of a virtual materials data space and a systematic handling of hierarchical processes and materials data using a developed ontological framework as high priority work items. In particular, the mid-level ontology PMDco and its augmentation through application-specific ontologies are illustrated. As part of the conclusion, a discussion encompasses the evolutionary path of the ontological framework, taking into account standardization efforts and the integration of modern AI methodologies such as natural language processing (NLP). Moreover, demonstrators illustrated in these presentations highlight: The integration and interconnection of tools, such as digital workflows and ontologies, Semantic integration of diverse data as proof of concept for semantic interoperability, Improved reproducibility in image processing and analysis, and Seamless data acquisition pipelines supported by an ontological framework. In this context, concepts regarding the application of modern research data management tools, such as electronic laboratory notebooks (ELN) and laboratory information management systems (LIMS), are presented and elaborated on. Furthermore, the growing relevance of a standardized adoption of such technologies in the future landscape of digital initiatives is addressed. This is supposed to provide an additional basis for discussion with respect to possible collaborations.
Gläser zeichnen sich durch eine breite und kontinuierlich abstimmbare chemische Zusammensetzung sowie einzigartige Formgebungstechniken aus, was sie oft zur Schlüsselkomponente moderner Hochtechnologien macht. Die Glasentwicklung ist jedoch oft noch zu kosten-, zeit- und energieintensiv. Der Einsatz von robotergestützten Schmelzsystemen, eingebettet in eine Ontologie-basierte digitale Umgebung, soll diese Probleme in Zukunft überwinden. Im Rahmen der BMBF Forschungsinitiative MaterialDigital unternimmt das Verbundprojekt GlasDigital „Datengetriebener Workflow für die beschleunigte Entwicklung von Glas“ erste Schritte in diese Richtung. Das Projektkonsortium, an dem das Fraunhofer ISC in Würzburg, die Friedrich-Schiller-Universität Jena (OSIM), die Technische Universität Clausthal (INW) und die Bundesanstalt für Materialforschung und -prüfung (BAM, Fachgruppe Glas) beteiligt sind, will alle wesentlichen Basiskomponenten für eine beschleunigte datengetriebene Glasentwicklung zusammenführen. Zu diesem Zweck wird ein robotergestütztes Hochdurchsatz-Glasschmelzsystem mit neuartigen Inline-Sensoren zur Prozessüberwachung, auf maschinellem Lernen (ML) basierenden adaptiven Algorithmen zur Prozessüberwachung und -optimierung, neuartigen Werkzeugen für die Hochdurchsatz-Glasanalyse sowie ML-basierten Algorithmen zum Glasdesign, Data Mining sowie Eigenschafts- und Prozessmodellierung ausgestattet. Der Vortrag gibt einen Überblick darüber, wie all diese Komponenten miteinander verzahnt sind, und veranschaulicht ihre Nutzbarkeit anhand einiger Beispiele.
Age-hardenable aluminum alloys undergo precise heat treatments to yield nanometer-sized precipitates that increase their strength and durability by hindering the dislocation mobility. Tensile tests provide mechanical properties, while microstructure evaluation relies on transmission electron microscopy (TEM), specifically the use of dark-field TEM images for precise dimensional analysis of the precipitates. However, this manual process is time consuming, skill dependent, and prone to errors and reproducibility issues.
Our primary goal is to digitally represent these processes while adhering to FAIR principles. Ontologies play a critical role in facilitating semantic annotation of (meta)data and form the basis for advanced data management. Publishing raw data, digital workflows, and ontologies ensures reproducibility.
This work introduces innovative solutions to traditional bottlenecks and offers new perspectives on digitalization challenges in materials science. We support advanced data management by leveraging knowledge graphs and foster collaborative and open data ecosystems that potentially revolutionize materials research and discovery.
Spectroscopy Lectures
(2024)
As a guest professor of FUNGLASS, I delivered 3 lectures on spectroscopy to the Graduate School Program, the postdoctoral fellows and other researchers: 1) Introduction to spectroscopy applied to solid state materials (with focus on glass and glass ceramics); 2) Vibrational spectroscopy (Infrared and Raman); 3) Electron Paramagnetic Resonance
lasses 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. As part of the German research initiative MaterialDigital, the joint project GlasDigital takes first steps in this direction. The project consortium involves 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) and aims to combine all main basic components required for accelerated data driven glass development. 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, including software tools for data mining as well as property and process modelling. The talk gives an overview how all these tools are interconnected and illustrates their usability with some examples.
When it comes to dental treatments, success is not only measured by attained functionality but, to a large extent, the associated aesthetics. This can become challenging for certain restorations and implants due to the complex optical characteristic of a tooth, which reflects, absorbs, diffuses, transmits, and even emits light. Thus, to get acceptable aesthetic results, favourable shade matching of ceramic restorations and implants should be achieved by strict control of optical response, which translates into a materials design question. Optical response is affected by several factors such as the composition, crystalline content, porosity, additives, grain size and the angle of incidence of light on the dental ceramics. The properties to be characterized are colour (and its stability), translucency, opalescence, refractive index, and fluorescence. Several techniques can be applied for the characterization of these properties and in this presentation, an overview will be given. Moreover, particular emphasis will be given on the capacitation of less familiarized public to UV-Vis absorption and photoluminescence (PLE) spectroscopies that are versatile and widely employed for functional and structural characterization of glasses and glass ceramic materials.
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.
Suitable material solutions are of key importance in designing and producing components for engineering systems – either for functional or structural applications. Materials data are generated, transferred, and introduced at each step along the complete life cycle of a component. A reliable
materials data space is therefore crucial in the digital transformation of an industrial branch.
A great challenge in establishing a materials data space lies in the complexity and diversity of materials science and engineering. It must be able to handle data from different knowledge areas over several magnitudes of length scale.
The Platform MaterialDigital (PMD) is expected to network a large number of repositories of materials data, allowing the direct contact of different stakeholders as materials producers, testing labs, designers and end users. Following the FAIR principles, it will promote the semantic
interoperability across the frontiers of materials classes. In the frame of a large joint initiative, PMD works intensively together with currently near 20 research consortia in promoting this exchange (www.material-digital.de).
In this presentation we will describe the status of our Platform MaterialDigital. We will also present in more detail the activities of GlasDigital, one of the joint projects mentioned above dealing with the digitalization of glass design and manufacturing.
(https://www.bam.de/Content/EN/Projects/GlasDigital/glasdigital.html)
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. As part of the German research initiative MaterialDigital, the joint project GlasDigital takes first steps in this direction. The project consortium involves 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) and aims to combine all main basic components required for accelerated data driven glass development. 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, including software tools for data mining as well as property and process modelling. The talk gives an overview how all these tools are interconnected and illustrates their usability with some examples.
The research carried out at the Laboratory of Spectroscopy of Functional Materials at IFSC/USP, in Brazil, is focused on the synthesis and structural-property correlation of luminescent materials including rare-earth (RE) doped glasses, ceramics and hybrid host-guest materials. For the past five years, we have been particularly interested in the development of single- and multifunctional nanosystems based on core-shell upconversion nanoparticles (UCNP) associated with dyes, organometallic complexes and other organic molecules, for biophotonic and sensing applications. In these systems, we take advantage of energy transfer between the UCNPs and the molecules to either supress or enhance luminescent response. Examples include the possibility of bioimaging and photodynamic therapy of bacteria and cancer cells, simultaneous magnetothermia and thermometry, localized O2 sensing, fast detection and quantification of biological markers (e.g. kidney disease) and microorganisms. On what concerns the development of luminescent sensors - a recently started project, our aim is to develop paper-based platforms for point-of-care devices. In this presentation, an overview of our contributions for the past years and our future aims will be presented with several examples.
Recently, detection and conversion of high energy radiation such as ultraviolet and X-rays has gained renewed attention. In part, technological applications in radioimaging and tomography have developed considerably as to allow lower dosages and higher resolutions, which require optimized scintillators and dosimeters. On the other hand, the increasing effort to reduce carbon footprint in energy production has triggered an intensive search for materials that can be excited with sunlight, ranging from photocatalysts to solar concentrators. At LEMAF – Laboratory of Spectroscopy of Functional Materials at IFSC/USP, we have been developing bulk glasses, polycrystalline and composite materials designed to target both challenges and, in this work an overview of recent progresses and of the state of art of these materials will be given.
For instance, the few available comercial scintillators are crystalline materials with costly and time consuming growth which hinders the development of new compositions. Glasses and glass ceramics, such as the NaPGaW composition developed in our lab, present high density, very good optical properties and high chemical stability which allow them radioluminescent response when doped with low concentrations of Ce3+, Eu3+ and Tb3+ offering a promise as alternatives to crystal scintillators. On the other hand, phosphor in glass (PiG) composites based on the persistent luminescent polycrystalline material Sr2MgSi2O7:Eu2+,Dy3+ (SMSO) embedded into NaPGa glasses offer interesting perspectives for the of UV light into visible, useful for white light generation (lighting), improved harvesting and conversion of solar light when coupled to c-Si PV cells and photocatalysis. These and other examples will be discussed.
The glasses are prepared through the conventional melt quenching technique, followed by controlled heating when glass ceramics are desired. The persistent luminescent phosphor is prepared by the microwave assisted technique (MAS) much faster and with considerable energy consumption reduction than in the usual solid state synthesis. The materials are characterized from the structural, morphological and spectroscopic (optical – UV-Vis, PL, PLE, and structural – NMR, EPR) points of view such that structure-property correlations are constantly sought to feedback synthesis and processing. Fig. 1, illustrates two examples of scintillator glasses doped with Tb3+ and PiG composites doped with Eu2+ and Dy3+.