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Paper des Monats
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AbstractMicroplastics (MP) can be detected in all environmental systems. Marine and terrestrial aquatic systems, especially the transported suspended solids, have often been the focus of scientific investigations in the past. Sediments of aquatic river systems, on the other hand, were often ignored due to the time‐consuming sample preparation and analysis procedures. Spectroscopic measurement methods counting particle numbers are hardly suitable as detection methods, because there are plenty of natural particles next to a small number of MP particles. Integral methods, such as thermoanalytical methods are determining the particle mass independently of the inorganic components.In this study, a workflow for sample preparation via density separation and subsequent analysis by thermal extraction desorption‐gas chromatography/mass spectrometry is presented, which leads to representative and homogeneous samples and allows fast and robust MP mass content measurements suitable for routine analysis. Polymers were identified and quantified in all samples. Polyethylene and styrene‐butadiene rubber are the dominant polymers, besides polypropylene and polystyrene. Overall, total polymer masses between 1.18 and 337.0 µg/g could be determined. Highest MP concentrations in riverbed sediment are found in sites characterized by low flow velocities in harbors and reservoirs, while MP concentrations in sandy/gravelly bed sediments with higher flow velocities are small.
The BAM Data Store
(2023)
As a partner in several NFDI consortia, the Bundesanstalt für Materialforschung und -prüfung (BAM, German federal institute for materials science and testing) contributes to research data standardization efforts in various domains of materials science and engineering (MSE). To implement a central research data management (RDM) infrastructure that meets the requirements of MSE groups at BAM, we initiated the Data Store pilot project in 2021. The resulting infrastructure should enable researchers to digitally document research processes and store related data in a standardized and interoperable manner. As a software solution, we chose openBIS, an open-source framework that is increasingly being used for RDM in MSE communities.
The pilot project was conducted for one year with five research groups across different organizational units and MSE disciplines. The main results are presented for the use case “nanoPlattform”. The group registered experimental steps and linked associated instruments and chemicals in the Data Store to ensure full traceability of data related to the synthesis of ~400 nanomaterials. The system also supported researchers in implementing RDM practices in their workflows, e.g., by automating data import and documentation and by integrating infrastructure for data analysis.
Based on the promising results of the pilot phase, we will roll out the Data Store as the central RDM infrastructure of BAM starting in 2023. We further aim to develop openBIS plugins, metadata standards, and RDM workflows to contribute to the openBIS community and to foster RDM in MSE.
Abstract
In the post-processing of large maritime components, a considerable amount of waste in the form of milling and grinding chips is produced. At the same time, additive manufacturing technologies have shown great potential in producing high-volume parts for maritime applications, allowing novel design approaches and short lead times. In this context, this study presents a sustainable approach to recycle and use aluminium bronze waste material, generated during post-processing of large cast ship propellers, as feedstock for laser-powder directed energy deposition. The recycling technology used to produce powder batches is inductive re-melting in combination with ultrasonic atomization. The derived metal powders are characterized using digital image analysis, powder flowability tests, scanning electron microscopy as well as energy dispersive X-ray spectroscopy. Compared to conventional metal powders produced by gas atomization, the recycled material shows excellent sphericity and a powder size distribution with a higher content of finer and coarser particles. Metallographic sections of deposited additively produced specimens show an increased hardness and reduced ductility, but also competitive densities and higher yield and ultimate tensile strength compared to cast material. The process chain shows high potential for the maritime sector to enable circular and sustainable manufacturing.
Die neue Generation von bainitischen Schmiedestählen bietet auf der einen Seite ein erhebliches Festigkeitspotenzial, das es im Sinne des Leichtbaus auch für zyklisch belastete Sicherheitsbauteile zu heben gilt. Auf der anderen Seite geht mit dieser Festigkeitssteigerung im Vergleich zu Vergütungsstählen ein Verlust an Duktilität und Zähigkeit einher. Am Beispiel des Demonstratorbauteils Achsschenkel ging das Forschungsvorhaben der Frage nach, wie ein Freigabeprozess zu gestalten ist, damit das Festigkeitspotenzial der neuen Stähle zuverlässig ausgenutzt werden kann. Als Ergebnis wird eine Vorgehensweise dargestellt, die den Eigenschaften der neuen Generation von Schmiedestählen Rechnung trägt, um den sicheren Betrieb der Komponenten zu gewährleisten.
Laser powder bed fusion of metallic components (PBF-LB/M) is gaining acceptance in industry. However, the high costs and lengthy qualification processes required for printed components create the need for more effective in-situ monitoring and testing methods. This article proposes multispectral Optical Tomography (OT) as a new approach for monitoring the PBF-LB/M process. Compared to other methods, OT is a low-cost process monitoring method that uses long-time exposure imaging to observe the build process. However, it lacks time resolution compared to expensive thermographic sensor systems. Monochromatic OT (1C-OT) is already commercially available and observes the building process layer-wise using a single wavelength window in the NIR range. Multispectral OT (nC-OT) utilizes a similar setup but can measure multiple wavelength ranges per location simultaneously. By comparing the classical 1C-OT and nC-OT approaches, this article examines the advantages of nC-OT (two channel OT and RGB-OT) in reducing the false positive rate for process deviations and approximating maximum temperatures for a better comparison between different build processes and materials. This could ultimately reduce costs and time for part qualification. The main goal of this contribution is to assess the advantages of nC-OT compared to 1C-OT for in-situ process monitoring of PBF-LB/M.
REALight ‐ Leichtgranulate und REA‐Gips aus feinkörnigen sulfatbelasteten Bau‐ und Abbruchabfällen
(2023)
Ziel des Projekts REALight ist die Entwicklung einer Referenzanlage zur Herstellung von Leichtgranulaten (leichte Gesteinskörnungen) aus Bau‐ und Abbruchabfällen und zur Gipsrückgewinnung. Als Rohstoffe werden bisher ungenutzte oder auf niedrigem Niveau eingesetzte Bau‐ und Abbruchabfälle und industrielle Nebenprodukte verwendet. Als Produkte werden leichte Gesteinskörnungen hergestellt. Die Sulfatabtrennung durch eine thermische Zersetzung bildet die Grundlage für die zusätzliche Gewinnung von Rauchgasentschwefelungs‐Gips (REA‐Gips). Das Projekt wird im Rahmen der Fördermaßnahme „Ressourceneffiziente Kreislaufwirtschaft – Bauen und Mineralische Stoffkreisläufe (ReMin)” gefördert. ReMin ist eine Maßnahme zur Umsetzung des BMBF‐Forschungskonzepts „Ressourceneffiziente Kreislaufwirtschaft” als Teil der BMBF Strategie „Forschung für nachhaltige Entwicklung – FONA”. Ziel der Förderung ist es, den Ausbau der Kreislaufwirtschaft voranzutreiben. Im Mittelpunkt steht dabei die Bauwirtschaft mit ihrer hohen Nachfrage nach Rohstoffen und gleichzeitig großen Mengen an anfallenden mineralischen Abfällen. Am Projekt REALight sind 12 Partner aus verschiedenen Bereichen der Baustoffherstellung und ‐anwendung, Abfallaufbereitung, Verfahrenstechnik sowie Forschung und Entwicklung beteiligt.
The digitalization of quality control processes and the underlying data infrastructures for safety relevant components, such as hydrogen pressure vessels, plays a significant role in the transition towards Industry 4.0. In the current safety regulations for hydrogen pressure vessels, there is no established concept for structural health monitoring. The development of a reliable structural health monitoring methodology for monitoring the structural integrity of pressure vessels enables a fast-forward transition from personnel- and costintensive recurring inspections, a.k.a. periodic maintenance, to predictive maintenance. In the work presented; we investigated the application of ultrasonic guided wave propagation to monitor and assess the condition of Type IV composite overwrapped pressure vessel (COPV). A sensor network of fifteen piezo-electric wafers is placed on the carbon fibre reinforced composite cylinder. Five different artificial damage configurations are created by gluing two different weight blocks on three different locations. The database containing measured guided wave data sets is enriched by two different boundary conditions. We utilized an open-source software, openBIS labnotebook, to store and analyse experimental datasets. The guided wave ultrasonic signals were investigated and analysed by using commonly used ultrasonic features (e.g., amplitude, frequency, time of flight) as well as non-traditional time-series features (kurtosis, skewness, variance). The features were used to calculate damage index and the detection performance for the results has been evaluated. The results suggest that both traditional and non-traditional features assume significant importance in artificial damage detection. The future works will additionally involve the impacts of operational conditions, such as periodic pressure variations temperature loadings as well as material degradations.
The application of composite overwrapped pressure vessels (COPV) to store hydrogen and other compressed gases, especially when operating at high pressures, imposed the need for an innovative and reliable approach to ensure the safe operation of the system. Continuous structural health monitoring (SHM) based on ultrasonic guided waves (GWs) is a promising approach due to the ability of the wave to propagate for long distances and go around complex structures, moreover the high sensitivity to various failure modes such as delamination, matrix cracking and debonding. In this study, we scrutinize the behavior of (GWs) within the COPV using a network of PZT elements that are used for excitation and sensing. A laser doppler vibrometer (LDV) was also used to scan the surface of the vessel in various directions. L(0,1) and L(0,2) were observed in the captured signal. The L(0, 2) appeared to be a dominant mode in the COPV and was capable of propagating along the entire length and maintaining a good signal-to-noise ratio. The L(0,2) mode maintained the same phase velocity when it is captured at various excitation angles (0, 45, and 90 degrees). The reduced effect of the orthotropy of the materials on the propagating waves is an important result as it will reduce the complexity in data processing when performing damage identification.
The applications of composite overwrapped pressure vessels (COPVs) in extreme conditions, such as storing hydrogen gases at very high pressure, impose new requirements related to the system's integrity and safety. The development of a structural health monitoring (SHM) system that allows for continuous monitoring of the COPVs provides rich information about the structural integrity of the component. Furthermore, the collected data can be used for different purposes such as increasing the periodic inspection intervals, providing a remaining lifetime prognosis, and also ensuring optimal operating conditions. Ultimately this information can be complementary to the development of the envisioned digital twin of the monitored COPVs. Guided waves (GWs) are preferred to be used in continuous SHM given their ability to travel in complex structures for long distances. However, obtained GW signals are complex and require advanced processing techniques. Machine learning (ML) is increasingly utilized as the main part of the processing pipeline to automatically detect anomalies in the system's integrity. Hence, in this study, we are scrutinizing the potential of using ML to provide continuous monitoring of COPVs based on ultrasonic GW data. Data is collected from a network of sensors consisting of fifteen Piezoelectric (PZT) wafers that were surface mounted on the COPV. Two ML algorithms are used in the automated evaluation procedure (i) a long short-term memory (LSTM) autoencoder for anomaly detection (defects/impact), and (ii) a convolutional neural network (CNN) model for feature extraction and classification of the artificial damage sizes and locations. Additional data augmentation steps are introduced such as modification and addition of random noise to original signals to enhance the model's robustness to uncertainties. Overall, it was shown that the ML algorithms used were able to detect and classify the simulated damage with high accuracy.
LIBS‐ConSort: Development of a sensor‐based sorting method for construction and demolition waste
(2023)
AbstractA joint project of partners from industry and research institutions approaches the challenge of construction and demolition waste (CDW) sorting by investigating and testing the combination of laser‐induced breakdown spectroscopy (LIBS) with near‐infrared (NIR) spectroscopy and visual imaging. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3‐cotaining building materials (gypsum, aerated concrete, etc.)Focusing on Berlin as an example, the entire value chain will be analyzed to minimize economic / technological barriers and obstacles at the cluster level and to sustainably increase recovery and recycling rates.The objective of this paper is to present current progress and results of the test stand development combining LIBS with NIR spectroscopy and visual imaging. In the future, this laboratory prototype will serve as a fully automated measurement setup to allow real‐time classification of CDW on a conveyor belt.
Im Rahmen des BMBF-geförderten Forschungsprojekts ReMin – REALight werden in einem Projektteam aus Industriepartnern und Forschungseinrichtungen unter Koordination der Bauhaus-Universität Weimar leichte Gesteinskörnungen aus Bau- und Abbruchabfällen und industriellen Nebenprodukten auf thermischem Weg hergestellt. Die Aufgabe der Bundesanstalt für Materialforschung und -prüfung (BAM) ist es, diese im Drehrohrofen erzeugten Blähgranulate für gebundene Anwendungen in Beton und Mörtel umfassend zu charakterisieren. Gemeinsam mit der Opus Denkmalpflege GmbH wird die Applikation feiner, gebrochener Blähgranulate in leichten Steinergänzungsmörteln für die Restaurierung von Sandsteinobjekten untersucht. Hierzu wird ein zweischichtiges Mörtelsystem bestehend aus einem Füll- und einem Deckmörtel entwickelt. Erste Ergebnisse der Rezepturentwicklung verschiedener kalkhaltiger Leichtmörtel mit gebrochenen Blähgranulaten werden vorgestellt. Die neuen Leichtmörtel sind hinsichtlich der entwickelten Druckfestigkeit gleichwertig gegenüber herkömmlichen Restauriermörteln.
In recent decades, the number of components in concrete has grown, particularly in formulations aimed at reducing carbon footprints. Innovations include diverse binders, supplementary cementitious materials, activators, concrete admixtures, and recycled aggregates. These developments target not only the enhancement of material properties but also the mitigation of the ecological and economic impacts of concrete — the most extensively used material by humankind. However, these advancements also introduce a greater variability in the composition of raw materials. The material’s behavior is significantly influenced by its nanoscale properties, which can pose challenges in accurate characterization. Consequently, there’s an increasing need for experimental tuning of formulations. This is accompanied by a more inconsistent composition of raw materials, which makes an experimental tuning of formulations more and more necessary. However, the increased complexity in composition presents a challenge in finding the ideal formulation through trial and error. Inverse design (ID) techniques offer a solution to this challenge by allowing for a comprehensive search of the entire design space to create new and improved concrete formulations. In this publication, we introduce the concept of ID and demonstrate how our open-source app “SLAMD” provides all necessary steps of the workflow to adapt it in the laboratory, lowering the application barriers. The intelligent screening process, guided by a predictive model, leads to a more efficient and effective data-driven material design process resulting in reduced carbon footprint and improved material quality while considering socio-economic factors in the materials design.
Titanium and its alloys are known to allow the straightforward laser-based manufacturing of ordered surface nanostructures, so-called high spatial frequency laser-induced periodic surface structures (HSFL). These structures exhibit sub-100 nm spatial periods – far below the optical diffraction limit. The resulting surface functionalities are usually enabled by both, topographic and chemical alterations of the nanostructured surfaces. For exploring these effects, multi-method characterizations were performed here for HSFL processed on Ti–6Al–4V alloy upon irradiation with near-infrared ps-laser pulses (1030 nm, ≈1 ps pulse duration, 1–400 kHz) under different laser scan processing conditions, i.e., by systematically varying the pulse repetition frequency and the number of laser irradiation passes. The sample characterization involved morphological and topographical investigations by scanning electron microscopy (SEM), atomic force microscopy (AFM), tactile stylus profilometry, as well as near-surface chemical analyses hard X-ray photoelectron spectroscopy (HAXPES) and depth-profiling time-of-flight secondary ion mass spectrometry (ToF-SIMS). This provides a quantification of the laser ablation depth, the geometrical HSFL characteristics and enables new insights into the depth extent and the nature of the non-ablative laser-induced near-surface oxidation accompanying these nanostructures. This allows to answer the questions how the processing of HSFL can be industrially scaled up, and whether the latter is limited by heat-accumulation effects.
The degradation of a single-site atomically dispersed, model Fe–N–C powder catalyst with high activity is investigated using cryo-Mössbauer spectroscopy. The results indicate a degradation initiated by an Fe2+ to Fe3+ oxidation due to coordination of oxygen to tetrapyrrolic Fe–N4 sites at atmospheric conditions (change between characteristic doublets) before iron(III) oxide is formed (sextet). Thermal reactivation can be used to restore substantial catalytic activity of aged Fe–N–C powders.
The process of viscous flow sintering is a phenomenon that is closely linked to the surface properties of the glass particles. In this work, we studied the extreme case of acid-leaching of soda-lime-silicate glass beads of two different particle size distributions and its effects on non-isothermal viscous sintering of powder compacts. Depth profiling of the chemical composition after leaching revealed a near-surface layer depleted in alkali and alkaline earth ions, associated with concurrent hydration as mass loss was detected by thermogravimetry. Heating microscopy showed that acid treatment of glasses shifted the sinter curves to higher temperatures with increasing leaching time. Modelling of the shrinkage with the cluster model predicted a higher viscosity of the altered surface layer, while analysis of the time scales of mass transport of mobile species (Na+, Ca2+ and H2O) during isochronous sintering revealed that diffusion of Na+ can compensate for concentration gradients before sintering begins. Also, exchanged water species can diffuse out of the altered layer, but the depletion of Ca2+ in the altered surface layer persists during the sinter interval, resulting in a glass with higher viscosity, which causes sintering to slow down.
The permeation of hydrogen gas was studied in meta-aluminous (tectosilicate) glass powders of Li2O×Al2O3×SiO2 (LAS), Na2O×Al2O3×SiO2 (NAS) and MgO×Al2O3×SiO2 (MAS) systems by pressure loading and vacuum extraction in the temperatures range 210–310 °C. With this method, both the solubility S and the diffusivity D were determined, while the permeability was given by the product SD. For all glasses, S was found to decrease with temperature, while D increased. Since the activation energy of diffusion of H2 molecules exceeded that of dissolution, permeation increased slightly with temperature. When extrapolated to standard conditions (25 °C), the permeability of tectosilicate glasses was found to be only 10-22–10-24 mol H2 (m s Pa)-1, which is 8–10 magnitudes lower than most polymers. Thin glass liners of these compositions are expected to be the most effective barrier for tanks of pressurised hydrogen.
Simulation-based digital twins have emerged as a powerful tool for evaluating the mechanical response of bridges. As virtual representations of physical systems, digital twins can provide a wealth of information that complements traditional inspection and monitoring data. By incorporating virtual sensors and predictive maintenance strategies, they have the potential to improve our understanding of the behavior and performance of bridges over time. However, as bridges age and undergo regular loading and extreme events, their tructural characteristics change, often differing from the predictions of their initial design. Digital twins must be continuously adapted to reflect these changes. In this article, we present a Bayesian framework for updating simulation-based digital twins in the context of bridges. Our approach integrates information from measurements to account for inaccuracies in the simulation model and quantify uncertainties. Through its implementation and assessment, this work demonstrates the potential for digital twins to provide a reliable and up-to-date representation of bridge behavior, helping to inform decision-making for maintenance and management.
Inputs of plastic impurities into the environment via the application of fertilizers are regulated in Germany and the EU by means of ordinances. Robust and fast analytical methods are the basis of legal regulations. Currently, only macro- and large microplastic contents (>1 mm) are measured. Microplastics (1–1,000 µm), are not yet monitored. Thermal analytical methods are suitable for this purpose, which can determine the mass content and can also be operated fully automatically in routine mode. Thermal extraction desorption-gas chromatography/mass spectrometry (TED-GC/MS) allows the identification of polymers and the determination of mass contents in solid samples from natural environments. In accordance with the German or European Commission (EC) Fertiliser Ordinance, composting plants should be monitored for microplastic particles with this method in the future. In this context a compost plant was sampled. At the end of the rotting process, the compost was sieved and separated in a coarse (>1 mm) and a fine fraction (<1 mm). The fine fraction was processed using density separation comparing NaCl and NaI as possible salt alternative and screened for microplastic masses by TED-GC/MS with additional validation and quality assurance experiments. With TED-GC/MS total microplastics mass contents of 1.1–3.0 μg/mg in finished compost could be detected with polyethylene mainly. What differs much to the total mass of plastics in the coarse fraction with up to 60 μg/mg, which were visually searched, identified via ATR-FTIR and gravimetrically weighted.