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Ensuring the purity of air and water is essential for the overall well-being of life on earth and the sustainability of the planet's diverse ecosystems. To achieve the goal of zero pollution, as outlined in the 2020 European Green Deal by the European Commission,[1] significant efforts are in progress. A key aspect of this commitment involves advancing more efficient and economically viable methods for treating wastewater. This includes the systematic monitoring of harmful pollutants such as heavy metals, microplastics, pesticides, and pharmaceuticals.
One example is the presence of the anti-inflammatory drug diclofenac in water systems, primarily originating from its use as a gel or lotion for joint pain treatment. Diclofenac contamination in surface waters has been detected at approximately 10 μg L-1 (0.03 μM)[2] which is not solely due to widespread usage but also because of the drug's resistance to microbial degradation. Conventional wastewater treatment plants (WWTPs), which rely on biodegradation, sludge sorption, ozone oxidation, and powdered activated carbon treatment, struggle to efficiently remove diclofenac from wastewater.[3],[4] For instance, to enable WWTPs to efficiently monitor and optimize their processes, it would be advantageous to develop on-site detection and extraction methods for persistent pharmaceutical residues in aqueous samples.
In this work, a sol-gel process was used to prepare Nile blue-doped silica nanoparticles (dSiO2-NPs) with a diameter of ca. 30 nm that were further functionalized to enable reversible-addition-fragmentation chain-transfer (RAFT) polymerization. To achieve fluorescence detection, a fluorescent monomer was used as a probe for diclofenac in ethyl acetate, generating stable complexes through hydrogen bond formation. The diclofenac/fluorescent monomer complexes were imprinted into thin molecularly imprinted polymer (MIP) shells on the surface of the dSiO2-NPs. Thus, the MIP binding behaviour could be easily evaluated by fluorescence titrations to monitor the spectral changes upon addition of the analyte. Doping the core substrate with Nile blue generates effective dual fluorescent signal transduction. This approach does not solely depend on a single fluorescence emission band in response to analyte recognition. Instead, it enables the fluorescent core to function as an internal reference, minimizing analyte-independent factors such as background fluorescence, instrumental fluctuation, and operational parameters.[5] Rebinding studies showed that the MIP particles have excellent selectivity towards the imprinted template and good discrimination against the competitor ibuprofen, with a discrimination factor of 2.5. Additionally, the limit of detection was determined to be 0.6 μM. Thus, with further optimization of the MIP, there is potential for the development of a MIP-based biphasic extract-&-detect fluorescence assay for simple, sensitive and specific sensing of diclofenac in aqueous samples down to the required concentrations of 0.03 μM.
Per- and polyfluoroalkyl substances (PFAS) represent a class of synthetic organofluorine chemicals extensively utilized in the manufacturing of various materials such as firefighting foams, adhesives, and stain- and oil-resistant coatings. In recent years, PFAS have been considered as emerging environmental contaminants, with particular focus on perfluoroalkyl carboxylic acids (PFCAs), the most prevalent type among PFAS. PFCAs are characterized by a fully fluorinated carbon backbone and a charged carboxylic acid headgroup. Notably, they have been designated as Substances of Very High Concern and added to the REACH Candidate List due to their persistence in the environment, non-biodegradability and toxicological effects.
Conventional techniques for the analysis of PFCA, such as GC-MS, HRMS and HPLC-based methods, are laborious, not portable, costly and require skilled personnel. In contrast, fluorescence assays can be designed as easy-to-operate, portable and cost-effective methods with high sensitivity and fast response, especially when analyte binding leads to a specific increase of a probe’s emission. Integration of such probes with a carrier platform and a miniaturized optofluidic device affords a promising alternative for PFCA monitoring.
Here, a novel guanidine BODIPY fluorescent indicator monomer has been synthesized, characterized, and incorporated into a molecularly imprinted polymer (MIP) for the specific detection of perfluorooctanoic acid (PFOA). The MIP layer was formed on tris(bipyridine)ruthenium(II) chloride doped silica core particles for optical internal reference and calibration-free assays. Such system allows selective and reliable detection of PFCA from surface water samples, with minimum interference by competitors, matrix effects and other factors. Integration of the assay into an opto-microfluidic setup resulted in a miniaturized and easy-to-operate detection system allowing for micromolar detection of PFOA in less than 15 minutes from surface water sample.
Electron microscopy applied in different operating modes, e.g., SEM, TEM or STEM-in-SEM, is the gold standard method to investigate the exact size and shape of individual nanoparticles. However, when fine nanoparticles with a non-monodisperse size distribution and non-spherical shapes are analysed, achieving an accurate result is challenging. Deviations in size measurements of more than 10% may occur. Understanding of the contrasts and sensitivities characteristic to the individual operating modes of an electron microscope is key in interpreting and evaluating quantitatively the measurement uncertainties needed for an eventual certification of specific nanoparticles via traceable results. Further, beyond the pure measurement, the other components in the analysis workflow with significant impact on the overall measurement uncertainties are the sample preparation and the image segmentation. In the present study the same areas of selected iron oxide fine nanoparticles (<25 nm) as reference nanomaterial (candidate) prepared on substrate for electron microscopy imaging are analysed correlatively with SEM, STEM-in-SEM and TEM with respect to their size and shape distribution. Individual significant measurement uncertainties are discussed, e.g., the sensitivity of secondary electron detectors of InLens-type to the surface morphology, particularly to the presence of an ultrathin organic coating or signal saturation effects on the particle edges, to electron beam exposure, to surface contamination, or the selection of the threshold for image segmentation. Another goal of this study is to establish a basis of analysis conditions which shall guarantee accurate results when both manual and particularly (semi-)automated segmentation approaches are applied. Advantages as well as limitations of the use of different electron microscopy operating modes, applied individually and correlatively, are highlighted.
Graphene and graphene-oxide (GO) are advanced materials which – similar to other graphene-related 2D materials (GR-2M) - are already used for instance in catalysis processes, biomedical applications, in inks and resins, or as composite materials for the aviation industry. The lateral/structural characterization of graphene oxide (GO) flakes is a challenging task, with steps like sample preparation, representative image selection and exact determination of the particle size distribution of well-defined size and shape descriptors being crucial for an accurate analysis. To ensure that safe-by-design principles are met within the various application fields, the commercial material must be thoroughly characterized and specified through well-known and standardized procedures.
GO flakes with different degrees of complexity were selected to assess the requirements for an accurate evaluation of their physico-chemical properties. These samples show inherent features with complex nanoscale characteristics such as porosity and edge roughness; further, the lateral size (quantified via equivalent circular diameter (ECD), minimum Feret and maximum Feret) of isolated and overlapping particles deposited on a substrate span over several orders of magnitude (nano to micron scale). The samples showed different degrees of agglomeration (and possible aggregation) with sizes ranging between submicron to a few tens of micrometers.
One focus is the automated segmentation and evaluation of images obtained by electron microscopy. The GO samples appear translucent with well-defined contrast between single and overlapping flakes both with the secondary electron detector of type InLens as well as with SEM in the transmission mode (STEM) utilizing a dedicated sample holder. To this end it is of utmost importance for the accurate image segmentation to carefully select thresholds both manually and through semi-automatic approaches using well-known threshold algorithms such as “IsoData” and pre-defined segmentation applications such as the ParticleSizer software package.
Further specific challenges in identifying and extracting key features of selected graphene oxide flakes are being discussed and approaches towards accurate and representative characterization are presented.
The EU member states have set out ambitious long-term goals for deploying offshore wind energy. The installed offshore wind capacity is set to increase from 14.6 GW in 2021 to around 320 GW in 2050. This signifies the role of offshore wind energy as a major contributor to reaching the EU’s climate and energy goals. To ensure that the defined targets are met, a significant number of new wind farms has to be installed and existing wind farms reaching the end of their planned life need to be reused efficiently. Some of the relevant reuse alternatives are lifetime extension, repowering based on the existing support structures and repowering with new turbines.
As a basis of the decision-making regarding the reuse of existing offshore wind farm, the expected utility of each relevant option should be determined based on the associated expected rewards, costs and risks. The optimal concept maximizes the utility of the decision-maker and fulfills the existing constraints and requirements. To facilitate such a quantitative decision-making, models and methods have to be developed. In particular, models are required that enable predictions of (a) the condition and performance of the turbines and support structures and (b) the renumeration, costs and consequences of adverse events. These predictions have to consider (a) the governing uncertainties, (b) the available information from the planning, construction, installation and operating phase, (b) potential repair, retrofitting and strengthening schemes and (c) possible monitoring, inspection and maintenance regimes for the future operating phase.
Over the past years, several models, methods and tools have been developed at the Bundesanstalt für Materialforschung und -prüfung (BAM) to support the structural integrity management of offshore wind turbine substructures. These include:
(a) a prototype for reliability-based, system-wide, adaptive planning of inspections of welded steel structures in offshore wind farms,
(b) a method for monitoring and risk-informed optimization of inspection and maintenance strategies for jacket structures subject to fatigue, and
(c) a probabilistic cost model of inspection and maintenance of welded steel structures in offshore wind farms.
This contribution provides an overview on these works and discusses how they can be adapted and extended to support the decision-making regarding lifetime extensions and repowering of offshore wind farms.
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.
Die additive Fertigung mittels Schweißverfahren bietet große ökonomische Vorteile für eine ressourceneffiziente Bauteilherstellung. Offene Fragen bezüglich Homogenität, Anisotropie der Schweißgefüge und den damit verbundenen Bauteileigenschaften stehen einer wirtschaftlichen Verarbeitung oftmals im Wege. Finale Bauteilgeometrie und Oberflächengüte erfordern meist komplementäre subtraktive Fertigungsschritte. Werkstoffe für hochbelastbare Komponenten sind oftmals schwer spanbar. In einem Vorhaben der BAM und des ISAF wurde untersucht, wie die Modifikation der AM-Schweißzusätze und das ultraschallunterstützte Fräsen (US) die Zerspanungssituation verbessern. Der vorliegende Artikel stellt wesentliche Zusammenhänge zwischen Legierung, Gefüge und Zerspanung zweier schwer spanbarer Hochleistungslegierungen (FeNi und CoCr) dar. Großes Potenzial zeigte neben dem US die Modifikation mit Zr und Hf bei Zulegierung in das Schweißgut mittels Beschichtung von Massivdrähten bzw. Herstellung von Fülldrähten.
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 determination of residual stress in additively manufactured materials is a challenge, even after decades from the establishment of the basics of residual stress analysis. This is due to the peculiar microstructure of such materials. In fact, researchers have discovered that conventional methods for the determination of RS in materials do not properly work for AM materials. In this tutorial, the basics of RS analysis will be explained, together with the basics of AM manufacturing techniques. The microstructure of the peculiar materials (AM) dealt with here will be elucidated. Successively, the necessary modifications to the conventional approaches to RS analysis will be explained and case studies will be displayed, for the attendant to touch with hands the peculiarities of the approaches. Finally, a few experimental and theoretical tips will be given on dos and don’ts for a correct determination of RS in AM materials.
Bruno, Giovanni ; Fritsch, Tobias ; Schröder, Jakob ; Mishurova, Tatiana ; Ulbricht, Alexander ; Evans, alexander ; Serrano-Munoz, Itziar
The experimental determination of residual stress becomes more complicated with increasing complexity of the structures investigated. Unlike the conventional and most of the additive manufacturing (AM) fabrication techniques, laser powder bed fusion (PBF-LB) allows the production of complex structures without any additional manufacturing step. However, due to the extremely localized melting and solidification, internal stress-induced deformation and cracks are often observed. In the best case, significant residual stress is retained in the final structures as a footprint of the internal stress during manufacturing.
Here we report solutions to the most prevalent challenges when dealing with the diffraction-based determination of residual stress in AM structures, in particular the choice of the correct diffraction elastic constants. We show that for Nickel-based alloys, the diffraction elastic constants of AM material significantly deviate from their conventional counterparts. Furthermore, measurement strategies to overcome the hurdles appearing when applying diffraction-based techniques to complex-shaped lattice structures are presented: a) proper sample alignment within the beam, b) the proper determination of the residual stress field in a representative part of the structure (i.e., with an engineering meaning). Beyond the principal stress magnitude, the principal direcions of residual stress are discussed for different geometries and scan strategies, as they are relevent for failure criteria.
We show that the RS in the lattice struts can be considered to be uniaxial and to follow the orientation of the strut, while the RS in the lattice knots is more hydrostatic. Additionally, we show that strain measurements in at least seven independent directions are necessary for the correct estimation of the principal stress directions. The measurement directions should be chosen according to the sample geometry and to an informed choice on the possible strain field (i.e., reflecting the scan strategy).
We finally show that if the most prominent direction is not measured, the error in the calculated stress magnitude increases in such a manner that no reliable assessment of RS state can be made.
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.
The determination of residual stress in additively manufactured materials is a challenge, even after decades from the establishment of the basics of residual stress analysis. This is due to the peculiar microstructure of such materials. In fact, researchers have discovered that conventional methods for the determination of RS in materials do not properly work for AM materials. In this tutorial, the basics of RS analysis will be explained, together with the basics of AM manufacturing techniques. The microstructure of the peculiar materials (AM) dealt with here will be elucidated. Successively, the necessary modifications to the conventional approaches to RS analysis will be explained and case studies will be displayed, for the attendant to touch with hands the peculiarities of the approaches. Finally, a few experimental and theoretical tips will be given on dos and don’ts for a correct determination of RS in AM materials.
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.
A damaging action of HNO3-55% only occurs in combination with its decomposition into nitrous gases, which can be caused by UV radiation. In a laboratory test, transparent HDPE jerrycans have been exposed to both UV radiation and 55 wt-% nitric acid solution at (41 ± 2)°C, for up to 20 days. For comparison, UV radiant exposure (21 days) and nitric acid exposure (up to 6 weeks) were performed separately, at nearly equal temperatures. The respective damages are compared with FTIR spectroscopy in ATR and HT-gel permeation chromatography (GPC) on a molecular level and with hydraulic internal pressure testing as a component test. For the used jerrycans, relevant oxidation can only be found after the combined exposure. The gradual increase in oxidative damage shows the good reproducibility of the lab exposure. The decomposition of nitric acid into nitrous gases by UV radiation – as well as the jerrycan oxidation – is also observed at lower HNO3 concentration (28 wt- %). Similar results are obtained after outdoor tests. Again, the damage occurs only after combined exposure, in contrast to the exposures to UV only and to HNO3 only, which were conducted in parallel. Outdoor exposures are most readily accepted as they represent possible end-use conditions. However, the reproducibility of these exposures is poor due to the large temporal variations in weather. There are also several safety risks, which is why the number of replicates remains limited. Since the outdoor and lab exposure tests show the same qualitative results, it is appropriate to conduct systematic studies in the laboratory. After 6 days of lab exposure, the oxidation damage is rated as critical, which corresponds to about 1/10 year in Central Europe, according to the UV radiant exposure. It should be noted that this amount can also occur in two sunny weeks.
A common engineering practice is to optimize the geometry of a structure by an iterative process, in which an objective function is minimized by systematically choosing the value of design variables and computing the value of the objective function many times.
However, regarding multiscale problems, this direct numerical approach is not feasible for a number of reasons.
The model has to take into account both the structural and unit cell (UC) scale, because the objective function to be minimized is a global quantity, while the parameters are related to the shape or material parameters of the UC.
In the absence of a clear separation of scales, the direct resolution of both scales in the numerical model leads to a significant increase in computational cost, which makes it impossible to repeatedly evaluate the model during the optimization process.
The main goal of this contribution is to overcome the aforementioned limitations and develop a new efficient computational framework for the optimal design of lattice structures.
To this end, parametric MOR is combined with DD methods.
The change in geometry of each UC within the lattice is modelled by introducing a transformation that maps the reference to the physical domain.
In offline simulations, suitable localized approximation spaces, that account for the change in geometry of the UC and its neighbours, are constructed using the concept of oversampling and random sampling.
These are then integrated into a dual DD framework to derive a robust and scalable solver, i.e. a fast-to-evaluate reduced order model (ROM).
The ROM is validated on the example of optimizing a concrete arc or pre-stressed multi beam structure minimizing its mass.
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.
Non-Destructive Testing (NDT) of type 4 composite pressure vessels can be seen as key to better understanding the behaviour of the composite structure and the impact of the manufacturing process on its quality. In this presentation, NDT methods used in the “Trustworthy Hydrogen” project are introduced. A brief discussion of the observed phenomena is provided.
Society is currently confronted with two global challenges, climate change and sustainable development. This reality reverberates amongst the leading nations of the world and is articulated as a priority by the United Nations through the Framework Convention on Climate Change and its seventeen Sustainable Development Goals. In 2016, under the Paris Accord, Mission Innovation, MI, emerged as a global response to climate change and developed eight innovation challenges to mitigate its effect, including Clean Energy Materials, IC6. This innovation challenge focused its efforts on accelerating the development and deployment of clean energy materials by more than a factor of ten through Materials Acceleration Platforms, MAPs – autonomous, self-driving materials laboratories and renewed itself under the current mandate as Materials for Energy, M4E.
Self-driving labs deploy artificial intelligence, robotic automation and high-performance simulation and modeling in a closed loop system of material synthesis and characterization. An international ecosystem for accelerated materials discovery has been established and finds applications in many enabling materials technologies, including nanomaterials. The importance of nanomaterials to catalysis for hydrogen production and carbon dioxide conversion as well as energy storage in batteries is well known. In this work, the international efforts under Materials for Energy will be elaborated including the development of MINERVA - MAP for Intelligent Nanomaterial synthesis Enabled by Robotics for Versatile Applications. MINERVA was specifically built to include the specialized equipment required for the synthesis, characterization and closed-loop optimization of various nano- and advanced materials, ranging from simple inorganic (silica, metal, metal oxide) or polymeric nanoparticles to more complex core-shell architectures and materials with well-defined porosity or surface chemistry. Currently, we are investigating materials for applications in antimicrobial and antibiofouling surface coatings, sensor materials, as well as the reproducible synthesis of reference materials with this platform.
Material Acceleration Platforms (MAPs) represent a transformative approach to the development of resilient and sustainable technology value chains. These platforms can identify candidate chemistries and structures via simulations, and database searches and leverage machine learning-based rapid screening to accelerate the discovery and deployment of novel materials, thereby addressing critical challenges in modern technology sectors.
Incorporating high-fidelity advanced characterization in the early phases of material development is crucial for early de-risking. Advanced characterization techniques, such as X-ray diffraction, advanced electrochemical and spectroscopic techniques provide comprehensive insights into the structural, chemical, and physical properties of materials. Long-term testing further contributes to the de-risking process by evaluating the durability and stability of materials under various environmental and operational conditions. Early identification of potential degradation mechanisms enables the refinement of material compositions and processing methods, ultimately leading to the development of more resilient materials.
Early upscaling attempts are integral to assessing the feasibility of material leads generated through machine learning-based rapid screening to evaluate the scalability of synthesis and processing techniques. This step is critical for identifying potential challenges in manufacturing, such as issues related to reproducibility, yield, and cost-effectiveness. Process design has to be a major part of the MAP-based material design to cope with the increasing share of secondary raw materials in supply chains.
This presentation will briefly summarize possible strategies to address these issues and provide deep-dives on best practices. As the demand for advanced materials continues to grow, MAPs will play an increasingly vital role in driving technological advancements and addressing global challenges.