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Paper des Monats
- ja (71)
In addition to sensitivity, selectivity, and portability, chemical sensing systems must generate reliable signals and offer modular configurability to address various small molecule targets, particularly in environmental applications. We present a versatile, modular strategy utilizing ratiometric molecularly imprinted particle probes based on BODIPY indicators and dyes for recognition and internal referencing. Our approach employs polystyrene core particles doped with a red fluorescent BODIPY as an internal standard, providing built-in reference for environmental influences. A molecularly imprinted polymer (MIP) recognition shell, incorporating a green-fluorescent BODIPY indicator monomer with a thiourea binding site for carboxylate containing analytes, is grafted from the core particles in the presence of the analyte as the template. The dual-fluorescent MIP probe detects fexofenadine as the model analyte with a change in green emission signal referenced against a stable red signal, achieving a detection limit of 0.13 μM and a broad dynamic range from 0.16 μM to 1.2 mM, with good discrimination against other antibiotics in acetonitrile. By selecting a versatile dye scaffold and recognition element, this approach can be extended to other carboxylate-containing analytes and/or wavelength combinations, potentially serving as a robust multiplexing platform.
Atmospheric deposition of particulate matter is an important indicator of air pollution and a significant factor in material surface fouling. The elemental composition of this nutrient-containing dust depends largely on the exposure region and time as well as on climate. Therefore, in this paper we report an analysis of atmospheric pollutions with a self-made low-cost bulk deposition sampler directed at sampling deposition via air transport and rainfall. We used the device in diverse environments - thus comparing an urban region, an area surrounded by forest and an area mainly dominated by agriculture. The total organic carbon (TOC) and total nitrogen (TN) amounts were selected as indicator parameters and analyzed in a biweekly rhythm for three and a half and two years, respectively. The TOC value responded to particulate matter in the urban area, especially significant were the influences of the New Year's firework in urban and pollen in the rural forest area. In contrast, the TN value was more under the influence of the nitrogen emissions in the agriculture-dominated area. However, the TN value did not correlate with the NOx values in the urban area because the atmospheric nitrogen emissions in the city might originate from various emission sources. Summarizing, the TOC and TN values of the self-made low-cost bulk deposition sampler were in good agreement with environmental events of their immediate surrounding. Moreover, the selected containers and sampling procedures are universally applicable to monitor and analyze organic as well as inorganic parameters (e.g. metal ions) of atmospheric deposition.
The chemical reaction between CO2 and a blended Portland cement concrete, referred to as carbonation, can lead to reduced performance, particularly when concrete is exposed to elevated levels of CO2 (i.e., accelerated carbonation conditions). When slight changes in concrete mix designs or testing conditions are adopted, conflicting carbonation results are often reported. The RILEM TC 281-CCC ‘Carbonation of Concrete with Supplementary Cementitious Materials’ has conducted a critical analysis of the standardised testing methodologies that are currently applied to determine carbonation resistance of concrete in different regions. There are at least 17 different standards or recommendations being actively used for this purpose, with significant differences in sample curing, pre-conditioning, carbonation exposure conditions, and methods used for determination of carbonation depth after exposure. These differences strongly influence the carbonation depths recorded and the carbonation coefficient values calculated. Considering the importance of accurately determining carbonation potential of concrete, not just for predicting their durability performance, but also for determining the amount of CO2 that concrete can re-absorb during or after its service life, it is imperative to recognise the applicability and limitations of the results obtained from different tests. This will enable researchers and practitioners to adopt the most appropriate testing methodologies to evaluate carbonation resistance, depending on the purpose of the conclusions derived from such testing (e. g. materials selection, service life prediction, CO2 capture potential).
The integration of additive manufacturing with traditional processes, termed hybrid additive manufacturing, has expanded its application domain, particularly in the repair of gas turbine blade tips. However, process-related defects in additively manufactured materials, interface formation, and material property mismatches in dual-material structures can significantly impact the fatigue performance of components. This investigation examines the low cycle fatigue and fatigue crack growth behaviors in dual-material specimens of nickel-based alloys, specifically the additively manufactured STAL15 and the cast alloy 247DS, at elevated temperatures. Low cycle fatigue experiments were conducted at temperatures of 950 °C and 1000 °C under a range of strain levels (0.3%–0.8%) and fatigue crack growth tests were conducted at 950 °C with stress ratios of 0.1 and −1. Fractographic and microscopic analyses were performed to comprehend fatigue crack initiation and crack growth mechanisms in the dual-material structure. The results consistently indicated crack initiation and fatigue fracture in the additively manufactured STAL15 material. Notably, fatigue crack growth retardation was observed near the interface when the crack extended from the additively manufactured STAL15 material to the perpendicularly positioned interface. This study highlights the importance of considering yield strength mismatch, as well as the potential effects of residual stresses and grain structure differences, in the interpretation of fatigue crack growth behavior at the interface.
During an extensive test programme at the Bundesanstalt für Materialforschung und prüfung, material property changes of EPDM O-rings were investigated at different ageing times and two ageing temperatures of 125 ◦ C and 150 ◦ C. To exclude possible diffusion-limited oxidation (DLO) effects that can distort the data, IRHD microhardness measurements were taken over the cross section of compressed O-rings. Continuous stress relaxation measurements were taken on samples free of DLO effects. The additional effect of physical processes to irreversible chemical ones during a long-term thermal exposure is quantified by the analysis of compression set measurements under various test conditions. By combining the different experimental methods, characteristic times relative to the degradation processes were determined. On the basis of experimental data, a microphysically motivated model that takes into account reversible and irreversible processes was developed. The parameter identification strategy of the material model is based on our experimental investigations on homogeneously aged elastomer O-rings. The simulated results are in good agreement with the experiments.
Performance Prediction of Anchors in SFRC using Minimally Invasive and Non‐Destructive Techniques
(2023)
AbstractFastenings are crucial for the upgrade of existing structures, by either enhancing structural components or modernising and expanding structures and structural systems. Whilst concrete is prevailing in the existing building stock, new types of concrete composites are increasingly used to improve the sustainability and overall structural performance of built assets. The addition of short dispersed fibres is a material technology with several applications. This paper addresses the synergy of fastening elements, introducing localised loads in concrete substrates, and of fibres, particularly in terms of the fibre orientation and density in the load application area, which is a significant quality aspect. The possibility to forecast this synergy based on non‐destructive or minimally invasive testing methods is an efficient tool to increase confidence in the design load‐bearing performance of the anchorages. Initially, previous literature and own investigations on such techniques are presented. Furthermore, a methodology is presented on associating such information to predict a single anchor's resistance on the basis of sophisticated non‐linear analyses and testing with engineered fibres alignments.
Advanced ceramics printed with photon-based additive manufacturing deals with anisotropic mechanical properties from the layer-by-layer manufacturing. Motivated by the success in using highly filled transparent slurries containing nanoparticles for powder-based two-photon-polymerization (2PP) for advanced ceramic printing, this works approach is the transfer to Xolography, a volumetric additive manufacturing technology based on linear two-photon excitation and without recoating steps. This paper reports the results of a preliminary investigation optimizing the photocurable slurry to the requirements of Xolography in terms of transparency, over a significantly larger mean free path, compared to 2PP. A feedstock filled with 70 % weight fraction of ceramic particles (∼30 vol%) exhibiting an exceptionally high degree of transparency in the relevant wavelength range of 400–800 nm was prepared from 5 nm zirconia nanoparticles. The high transparency of the photocurable slurry is attributed to the near-monomodal particle size distribution of the zirconia nanoparticles used.
AbstractTwo‐photon polymerization (2PP) additive manufacturing (AM) utilizes feedstocks of ceramic nanoparticles of a few nanometers in diameter, enabling the fabrication of highly accurate technical ceramic design with structural details as small as 500 nm. The performance of these materials is expected to differ from conventional AM ceramics, as nanoparticles and three‐dimensional printing at high resolution introduce new microstructural aspects. This study applies 2PP‐AM of yttria‐stabilized zirconia to investigate the mechanical response behavior under compressive load, probing the influence of smallest structural units induced by the line packing during the printing process, design of sintered microblocks, and sintering temperature and thereby microstructure. We find a dissipative mechanical response enhanced by sintering at lower temperatures than conventional. The pursued 2PP‐AM approach yields a microstructured material with an increased number of grain boundaries that proposedly play a major role in facilitating energy dissipation within the here printed ceramic material. This microplastic response is further triggered by the filigree structures induced by hollow line packing at the order of the critical defect size of ceramics. Together, these unique aspects made accessible by the 2PP‐AM approach contribute to a heterogeneous nano‐ and microstructure, and hint toward opportunities for tailoring the mechanical response in future ceramic applications.
A long-term study was conducted on double-lap spruce wood-concrete joints to investigate their shear strength and stiffness over a 12-month period. These joints were manufactured using both wet and dry processes, each incorporating two adhesive types for bonding the wood to the concrete: a brittle epoxy and a ductile polyurethane (PUR). The experimental design exposed the joints to three specific long-term environments: (1) outdoor exposure, (2) indoor conditions with applied load, and (3) outdoor conditions with applied load. The wood concrete joints exposed to outdoor conditions were subjected to destructive shear testing at intervals of 0 (serving as the reference sample), 2, 4, 6, and 12 months, respectively. For joints subjected to both indoor and outdoor conditions with shear loading, the shear deformation of joints was monitored continuously over the 12 months before performing the destructive tests. A gradual reduction in the shear stiffness and strength of dry joints (produced using the dry bond method) exposed to outdoor conditions was observed over a 12-month period, primarily due to bond failure at the concrete-adhesive interface. The wet joints exhibited no degradation in shear stiffness and strength across long-term conditions over the same period. The bond failure observed in dry joints was predominantly associated with stresses arising from dimensional changes in the wood. No degradation was found in the cross-linking density of the adhesive or in the concrete’s compressive stiffness and strength.
AbstractUnderstanding the origin of low thermal conductivities in ionic conductors is essential for improving their thermoelectric efficiency, although accompanying high ionic conduction may present challenges for maintaining thermoelectric device integrity. This study investigates the thermal and ionic transport in Cu7PSe6, aiming to elucidate their fundamental origins and correlation with the structural and dynamic properties. Through a comprehensive approach including various characterization techniques and computational analyses, it is demonstrated that the low thermal conductivity in Cu7PSe6 arises from structural complexity, variations in bond strengths, and high lattice anharmonicity, leading to pronounced diffuson transport of heat and fast ionic conduction. It is found that upon increasing the temperature, the ionic conductivity increases significantly in Cu7PSe6, whereas the thermal conductivity remains nearly constant, revealing no direct correlation between ionic and thermal transport. This absence of direct influence suggests innovative design strategies in thermoelectric applications to enhance stability by diminishing ionic conduction, while maintaining low thermal conductivity, thereby linking the domains of solid‐state ionics and thermoelectrics. Thus, this study attempts to clarify the fundamental principles governing thermal and ionic transport in Cu+‐superionic conductors, similar to recent findings in Ag+ argyrodites.
Mechanochemistry is drawing attention from the pharmaceutical industry given its potential for sustainable material synthesis and manufacture. Scaling mechanochemical processes to industrial level remains a challenge due to an incomplete understanding of their underlying mechanisms. We here show how time-resolved in situ powder X-ray diffraction data, coupled with analytical kinetic modelling, provides a powerful approach to gain mechanistic insight into mechanochemical reactions. By using the ibuprofen–nicotinamide co-crystal mechanosynthesis as a benchmark system, we investigate the behaviour of the solids involved and identify the factors that promote the reaction. As mechanochemical mechanisms become increasingly clear, it promises to become a breakthrough in the industrial preparation of advanced pharmaceuticals.
The ultrasonic echo technique is broadly applied in non‐destructive testing (NDT) of concrete structures involving tasks such as measuring thickness, determining geometry and locating built‐in elements. To address the challenge of enhancing ultrasonic imaging for complex concrete constructions, we adapted a seismic imaging algorithm – reverse time migration (RTM) – for NDT in civil engineering. Unlike the traditionally applied synthetic aperture focusing technique (SAFT), RTM takes into account the full wavefield including primary and reflected arrivals as well as multiples. This capability enables RTM to effectively handle all wave phenomena, unlimited by changes in velocity and reflector inclinations. This paper concentrates on applying and evaluating a two‐dimensional elastic RTM algorithm that specifically addresses horizontally polarized shear (SH) waves only, as these are predominantly used in ultrasonic NDT of concrete structures. The elastic SH RTM algorithm was deployed for imaging real ultrasonic echo SH‐wave data obtained at a concrete specimen exhibiting a complex back wall geometry and containing four tendon ducts. As these features are frequently encountered in practical NDT scenarios, their precise imaging holds significant importance. By applying the elastic SH RTM algorithm, we successfully reproduced nearly all reflectors within the concrete specimen. In particular, we were capable of accurately reconstructing all vertically oriented reflectors as well as the circular cross sections of three tendon ducts, which was not achievable with traditional SAFT imaging. These findings demonstrate that elastic SH RTM holds the ability to considerably improve the imaging of complex concrete geometries, marking a crucial advancement for accurate, high‐quality ultrasonic NDT in civil engineering.
Non‐targeted screenings (NTS) are essential tools in different fields, such as forensics, health and environmental sciences. NTSs often employ mass spectrometry (MS) methods due to their high throughput and sensitivity in comparison to, for example, nuclear magnetic resonance–based methods. As the identification of mass spectral signals, called annotation, is labour intensive, it has been used for developing supporting tools based on machine learning (ML). However, both the diversity of mass spectral signals and the sheer quantity of different ML tools developed for compound annotation present a challenge for researchers in maintaining a comprehensive overview of the field.In this work, we illustrate which ML‐based methods are available for compound annotation in non‐targeted MS experiments and provide a nuanced comparison of the ML models used in MS data analysis, unravelling their unique features and performance metrics. Through this overview we support researchers to judiciously apply these tools in their daily research. This review also offers a detailed exploration of methods and datasets to show gaps in current methods, and promising target areas, offering a starting point for developers intending to improve existing methodologies.
Characteristics of environmental stress cracking of PE-HD induced by biodiesel and diesel fuels
(2024)
In the context of the increasing effect of carbon dioxide emissions on the global climate biodiesel produced from renewable sources has emerged as a promising contender replacing fossil fuels, especially in long-range transport vehicles, using existing engines and infrastructure.
High-density polyethylene is one of the prevailing materials for pipe and container applications for storage and transport of such fuels, both, from fossil and renewable resources. The contact with the respective fuels raises questions concerning material compatibility as biodiesel exhibits significant differences compared to conventional diesel fuel affecting its sorption and plasticization behavior in polyethylene. In this study, its behavior with respect to environmental stress cracking, considered one of the most frequent damage mechanisms leading to failure of polymer parts and packaging, was evaluated using the well-established Full Notch Creep Test. This
approach allows for a detailed fracture surface analysis using imaging techniques, such as optical and laser scanning microscopy, as well as infrared spectroscopy. Comparing the environmental stress cracking behavior in standard surfactant solutions with that in biodiesel and diesel, respective crack propagation rates, showing different levels of acceleration, were determined and details of the underlying mechanisms could be revealed.
Furthermore, the specific infrared absorption of the biodiesel’s ester functionality allows its semi-quantitative determination on the fracture surface of the tested specimens after failure. Thus, a preferred uptake of sorptive fluids in the fracture zone due to local morphological changes of the polyethylene could be directly evidenced by infrared spectroscopy.
Microalloying elements such as Nb and Ti are essential to increase the strength of quenched and tempered high-strength low alloy (HSLA) structural steels with nominal yield strength ≥ 690 MPa and their welded joints. Standards such as EN 10025–6 only specify limits or ranges for chemical composition, which leads to variations in specific compositions between steel manufacturers. These standards do not address the mechanical properties of the material, and even small variations in alloy content can significantly affect these properties. This makes it difficult to predict the weldability and integrity of welded joints, with potential problems such as softening or excessive hardening of the heat-affected zone (HAZ). To understand these metallurgical effects, previous studies have investigated different microalloying routes with varying Ti and Nb contents using test alloys. The high-strength quenched and tempered fine-grained structural steel S690QL is the basic grade regarding chemical composition and heat treatment. To evaluate weldability, three-layer welds were made using high-performance MAG welding. HAZ formation was investigated, and critical microstructural areas were identified, focusing on phase transformations during cooling and metallurgical precipitation behavior. Isothermal thermodynamic calculations for different precipitations were also carried out. Mechanical properties, especially Charpy notch impact toughness, were evaluated to understand the influence of different microalloys on the microstructure of the HAZ and mechanical properties.
Safety and reliability are the major challenges to face for the development and acceptance of hydrogen technology. It is therefore crucial to deeply study material compatibility, in particular for tribological components that are directly in contact with hydrogen. Some of the most critical parts are sealing materials that need increased safety requirements. In this study, the fretting behavior of several elastomer materials were evaluated against 316L stainless steel in an air and hydrogen environment up to 10 MPa. Several grades of cross-linked hydrogenated acrylonitrile butadiene (HNBR), acrylonitrile butadiene (NBR) and ethylene propylene diene monomer rubbers (EPDM) were investigated. Furthermore, aging experiments were conducted for 7 days under static contions in 100 MPa of hydrogen followed by rapid gas decompression. Fretting tests revealed that the wear of these compounds is significantly affected by the hydrogen environment compared to air, especially with NBR grades. After the aging experiment, the friction response of the HBNR grades is characterized by increased adhesion due to elastic deformation, leading to partial slip.
Glassy solids evolve towards lower-energy structural states by physical aging. This can be characterized by structural relaxation times, the assessment of which is essential for understanding the glass’ time-dependent property changes. Conducted over short times, a continuous increase of relaxation times with time is seen, suggesting a time-dependent dissipative transport mechanism. By focusing on micro-structural rearrangements at the atomic-scale, we demonstrate the emergence of sub-diffusive anomalous transport and therefore temporal fractional diffusion in a metallic glass, which we track via coherent x-ray scattering conducted over more than 300,000 s. At the longest probed decorrelation times, a transition from classical stretched exponential to a power-law behavior occurs, which in concert with atomistic simulations reveals collective and intermittent atomic motion. Our observations give a physical basis for classical stretched exponential relaxation behavior, uncover a new power-law governed collective transport regime for metallic glasses at long and practically relevant time-scales, and demonstrate a rich and highly non-monotonous aging response in a glassy solid, thereby challenging the common framework of homogeneous aging and atomic scale diffusion.
The development of multi‐principal‐element alloys (MPEAs) with unique characteristics such as high work hardening capacity similar to well‐known alloy systems like Hadfield steel X120Mn12 (ASTM A128) is a promising approach. Hence, by exploiting the core effects of MPEAs, the application range of conventional alloy systems can be extended. In the present study, work‐hardening MPEAs based on the equimolar composition CoFeNi are developed. Mn and C are alloyed in the same ratio as for X120Mn12. The production route consists of cast manufacturing by an electric arc furnace and surface functionalization via mechanical finishing using ultrasonic‐assisted milling (USAM) to initiate work hardening. The microstructure evolution, the hardness as well as the resulting oscillating wear resistance are detected. A pronounced lattice strain and grain refinement due to the plastic deformation during the USAM is recorded for the MPEA CoFeNi‐Mn12C1.2. Consequently, hardness increases by ≈380 HV0.025 in combination with a higher oscillating wear resistance compared to the X120Mn12. This shows the promising approach for developing work‐hardening alloys based on novel alloy concepts such as MPEAs.
Machine learning in non-destructive testing (NDT) offers significant potential for efficient daily data analysis and uncovering previously unknown relationships in persistent problems. However, its successful application heavily depends on the availability of a diverse and well-labeled training dataset, which is often lacking, raising questions about the transferability of trained algorithms to new datasets. To examine this issue closely, the authors applied classifiers trained with laboratory Ground Penetrating Radar (GPR) data to categorize on-site moisture damage in layered building floors. The investigations were conducted at five different locations in Germany. For reference, cores were taken at each measurement point and labeled as (i) dry, (ii) with insulation damage, or (iii) with screed damage. Compared to the accuracies of 84 % to 90 % within the laboratory training data (504 B-Scans), the classifiers achieved a lower overall accuracy of 53 % for on-site data (72 B-Scans). This discrepancy is mainly attributable to a significantly higher dynamic of all signal features extracted from on-site measurements compared to laboratory training data. Nevertheless, this study highlights the promising sensitivity of GPR for identifying individual damage cases. In particular the results showing insulation damage, which cannot be detected by any other non-destructive method, revealed characteristic patterns. The accurate interpretation of such results still depends on trained personnel, whereby fully automated approaches would require a larger and diverse on-site data set. Until then, the findings of this work contribute to a more reliable analysis of moisture damage in building floors using GPR and offer practical insights into applying machine learning to non-destructive testing for civil engineering (NDT-CE).
Introduction
Glacier ice algae, mainly Ancylonema alaskanum and Ancylonema nordenskiöldi, bloom on Greenland Ice Sheet bare ice surfaces. They significantly decrease surface albedo due to their purple-brown pigmentation, thus increasing melt. Little is known about their metabolic adaptation and factors controlling algal growth dynamics and pigment formation. A challenge in obtaining such data is the necessity of melting samples, which delays preservation and introduces bias to metabolomic analysis. There is a need to evaluate the physiological response of algae to melting and establish consistent sample processing strategies for metabolomics of ice microbial communities.
Objectives
To address the impact of sample melting procedure on metabolic characterization and establish a processing and analytical workflow for endometabolic profiling of glacier ice algae.
Methods
We employed untargeted, high-resolution mass spectrometry and tested the effect of sample melt temperature (10, 15, 20 °C) and processing delay (up to 49 h) on the metabolome and lipidome, and complemented this approach with cell counts (FlowCam), photophysiological analysis (PAM) and diversity characterization.
Results and Conclusion
We putatively identified 804 metabolites, with glycerolipids, glycerophospholipids and fatty acyls being the most prominent superclasses ( 50% of identified metabolites). Among the polar metabolome, carbohydrates and amino acid-derivatives were the most abundant. We show that 8% of the metabolome is affected by melt duration, with a pronounced decrease in betaine membrane lipids and pigment precursors, and an increase in phospholipids. Controlled fast melting at 10 °C resulted in the highest consistency, and is our recommendation for future supraglacial metabolomics studies.
Viscous crack healing in soda–lime–magnesium–silicate–ZrO<sub>2</sub> glass matrix composites
(2024)
AbstractThe present study investigates the influence of the crystal volume content on viscous crack healing in glass ceramic glass sealants. To ensure constant microstructure during healing, soda–lime–magnesium silicate glass matrix composites with varied volume fractions of ZrO2 filler particles were used. Crack healing was studied on radial cracks induced by Vickers indentation, which were stepwise annealed to monitor the healing progress by confocal laser scanning microscopy. Confirming previous studies, healing of radial cracks in pure glass was found delayed by global flow phenomena like crack widening and crack edge and tip rounding to minimize the sample surface. With increasing ZrO2 filler content, these global flow phenomena were progressively inhibited whereas local flow phenomena like sharp crack tip healing could still occur. As a result, crack healing was even accelerated by filler particles up to a maximum filler content of 17 vol% whereas crack healing was fully suppressed only at 33 vol% filler content.
Gas Distribution Mapping (GDM) is a valuable tool for monitoring the distribution of gases in a wide range of applications, including environmental monitoring, emergency response, and industrial safety. While GDM is actively researched in the scope of gas-sensitive mobile robots (Mobile Robot Olfaction), there is a potential for broader applications utilizing sensor networks. This study aims to address the lack of deep learning approaches in GDM and explore their potential for improved mapping of gas distributions. In this paper, we introduce Gas Distribution Decoder (GDD), a learning-based GDM method. GDD is a deep neural network for spatial interpolation between sparsely distributed sensor measurements that was trained on an extensive data set of realistic-shaped synthetic gas plumes based on actual airflow measurements. As access to ground truth representations of gas distributions remains a challenge in GDM research, we make our data sets, along with our models, publicly available. We test and compare GDD with state-of-the-art models on synthetic and real-world data. Our findings demonstrate that GDD significantly outperforms existing models, demonstrating a 35% improvement in accuracy on synthetic data when measured using the Root Mean Squared Error over the entire distribution map. Notably, GDD appears to have superior capabilities in reconstructing the edges and characteristic shapes of gas plumes compared to traditional models. These potentials offer new possibilities for more accurate and efficient environmental monitoring, and we hope to inspire other researchers to explore learning-based GDM.
This work studies the influence of the adsorbed layer on the glass transition of thin films of polysulfone. Therefore, the growth kinetics of the irreversibly adsorbed layer of polysulfone on silicon substrates was first investigated using the solvent leaching approach, and the thickness of the remaining layer was measured with atomic force microscopy. Annealing conditions before leaching were varied in temperature and time (0–336 h). The growth kinetics showed three distinct regions: a pre-growth step where it was assumed that phenyl rings align parallel to the substrate at the shortest annealing times, a linear growth region, and a crossover from linear to logarithmic growth observed at higher temperatures for the longest annealing times. No signs of desorption were observed, pointing to the formation of a strongly adsorbed layer.
Second, the glass transition of thin polysulfone films was studied in dependence on the film thickness using spectroscopic ellipsometry. Three annealing conditions were compared: two with only a tightly bound layer formed in the linear growth regime and one with both tightly bound and loosely adsorbed layers formed in the logarithmic growth regime. The onset thickness and increase in the glass transition temperature increases with annealing time and temperature. These differences were attributed to the distinct conformations of the formed adsorbed layers.
Knufia petricola is a black fungus that colonizes sun-exposed surfaces as extreme and oligotrophic environments. As ecologically important heterotrophs and biofilm-formers on human-made surfaces, black fungi form one of the most resistant groups of biodeteriorating organisms. Due to its moderate growth rate in axenic culture and available protocols for its transformation and CRISPR/Cas9-mediated genome editing, K. petricola is used for studying the morpho-physiological adaptations shared by extremophilic and extremotolerant black fungi. In this study, the bacteria-derived tetracycline (TET)-dependent promoter (Tet-on) system was implemented to enable controllable gene expression in K. petricola. The functionality i.e., the dose-dependent inducibility of TET-regulated constructs was investigated by using GFP fluorescence, pigment synthesis(melanin and carotenoids) and restored uracil prototrophy as reporters. The newly generated cloning vectors containing the Tet-on construct, and the validated sites in the K. petricola genome for color-selectable or neutral insertion of expression constructs complete the reverse genetics toolbox. One or multiple genes can be expressed on demand from different genomic loci or from a single construct by using 2A self-cleaving peptides, e.g., for localizing proteins and protein complexes in the K. petricola cell or for using K. petricola as host for the expression of heterologous genes.
AbstractRecently, we have developed an algorithm to quantitatively evaluate the roughness of spherical microparticles using scanning electron microscopy (SEM) images. The algorithm calculates the root-mean-squared profile roughness (RMS-RQ) of a single particle by analyzing the particle’s boundary. The information extracted from a single SEM image yields however only two-dimensional (2D) profile roughness data from the horizontal plane of a particle. The present study offers a practical procedure and the necessary software tools to gain quasi three-dimensional (3D) information from 2D particle contours recorded at different particle inclinations by tilting the sample (stage). This new approach was tested on a set of polystyrene core-iron oxide shell-silica shell particles as few micrometer-sized beads with different (tailored) surface roughness, providing the proof of principle that validates the applicability of the proposed method. SEM images of these particles were analyzed by the latest version of the developed algorithm, which allows to determine the analysis of particles in terms of roughness both within a batch and across the batches as a routine quality control procedure. A separate set of particles has been analyzed by atomic force microscopy (AFM) as a powerful complementary surface analysis technique integrated into SEM, and the roughness results have been compared.
Structural health monitoring (SHM) using ultrasonic-guided waves (UGWs) enables continuous monitoring of components with complex geometries and provides extensive information about their structural integrity and their overall condition. Composite overwrapped pressure vessels (COPVs) used for storing hydrogen gases at very high pressures are an example of a critical infrastructure that could benefit significantly from SHM. This can be used to increase the periodic inspection intervals, ensure safe operating conditions by early detection of anomalies, and ultimately estimate the remaining lifetime of COPVs. Therefore, in the digital quality infrastructure initiative (QI-Digital) in Germany, an SHM system is being developed for COPVs used in a hydrogen refueling station. In this study, the results of a lifetime fatigue test on a Type IV COPV subjected to many thousands of load cycles under different temperatures and pressures are presented to demonstrate the strengths and challenges associated with such an SHM system. During the cyclic testing up to the final material failure of the COPV, a sensor network of fifteen surface-mounted piezoelectric (PZT) wafers was used to collect the UGW data. However, the pressure variations, the aging process of the COPV, the environmental parameters, and possible damages simultaneously have an impact on the recorded signals. This issue and the lack of labeled data make signal processing and analysis even more demanding. Thus, in this study, semi-supervised, and unsupervised deep learning approaches are utilized to separate the influence of different variables on the UGW data with the final aim of detecting and localizing the damage before critical failure.
Alcohol-initiated polymerizations of glycolide (GL) catalyzed by tin(II) 2-ethylhexanoate (SnOct2) were carried out in bulk with variation of GA/In ratio, temperature and time. Due to a rather strong competition of cyclization polyglycolide (PGA) free of cycles were never obtained. When the cyclic catalysts 2,2-dibutal-2-stanna − 1,3-dithiolane (DSTL) or 2-stanna 1,3-dioxo-4,5,6,7 bibenzepane (SnBiph) were used in combination with 1,4-butanediol the influence of cyclization was even stronger. Furthermore, the degrees of polymerization were higher than the GA/alcohol ratio due to rapid polycondensation in the solid state. At 160 °C or below, the matrixassisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectra indicated separate crystallization of low molar mass cyclic and linear PGAs from the same reaction mixture (also observed for poly(L-lactide)s).
Pressure-sensitive adhesive tapes are used in a variety of applications such as construction, aircrafts, railway vehicles, and ships, where flame retardancy is essential. Especially in these applications, phosphorus-based flame retardants are often chosen over halogenated ones due to their advantages in terms of toxicity. Although there are pressure-sensitive adhesives with phosphorus flame retardants available on the market, their flame-retardant modes of action and mechanisms are not entirely understood. This research article provides fundamental pyrolysis research of three phosphorus-based flame retardants that exhibit different mechanisms in a pressuresensitive adhesive matrix. The flame-retardants modes of action and mechanisms of a 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) derivate, an aryl phosphate, and a self-synthesized, covalently bonded DOPO derivate (copolymerized) are investigated. The blended DOPO derivate is volatilized at rather low temperatures while the covalently bonded DOPO derivate decomposes together with the polymer matrix at the same temperature. Both DOPO derivates release PO radicals which are known for their flame inhibition. The aryl phosphate decomposes at higher temperatures, releases small amounts of aryl phosphates into the gas phase, and acts predominantly the condensed phase. The aryl phosphate acts as precursor for phosphoric acid and improves the charring of the pressure sensitive adhesive matrix. All flame retardants enhance the flammability of the adhesives depending on their individual mode of action while the covalently bonded flame retardant additionally improves the mechanical properties at elevated temperatures making it a promising future technology for pressure-sensitive adhesives.
This work provides an investigation of the influence of low temperature heat treatments on the fatigue behavior of a PBF-LB AlSi10Mg alloy. Fatigue specimens are produced in form of round bars on a build platform preheated at 200 ◦C. The specimens have been tested in three different conditions: as-built, and after heat treatments at 265 ◦C for 1 h and 300 ◦C for 2 h. Prior to the fatigue testing, the defect distribution is analyzed by means of micro computed tomography. Subsequently, the peak over threshold method is successfully applied to provide a prediction of the size of killer defect. The defect population was of gas porosity type. No clear improvement of the fatigue performance is observed after the heat treatments. The fatigue strength predicted using fracture mechanics-based approaches is in good agreement with the experimental data. Among the studied approaches, short crack models provided the most conservative predictions.
This article presents a method to use the dispersive behavior of ultrasonic guided waves and neural networks to determine the isotropic elastic constants of plate-like structures through dispersion images. Therefore, two different architectures are compared: one using convolutions and transfer learning based on the EfficientNetB7 and a Vision Transformer-like approach. To accomplish this, simulated and measured dispersion images are generated, where the first is applied to design, train, and validate and the second to test the neural networks. During the training of the neural networks, distinct data augmentation layers are employed to introduce artifacts appearing in measurement data into the simulated data. The neural networks can extrapolate from simulated to measured data using these layers. The trained neural networks are assessed using dispersion images from seven known material samples. Multiple variations of the measured dispersion images are tested to guarantee the prediction stability. The study demonstrates that neural networks can learn to predict the isotropic elastic constants from measured dispersion images using only simulated dispersion images for training and validation without needing an initial guess or manual feature extraction, independent of the measurement setup. Furthermore, the suitability of the different architectures for generating information from dispersion images in general is discussed.
Most high capacity anode materials for lithium-ion batteries (LiB) require a carbonaceous matrix. In this context one promising material is reduced graphene oxide (rGO). Herein, we present the influence of different reduction degrees of rGO on its physico-chemical properties, such as crystallinity, specific surface area, electrical conductivity and electrochemical lithiation/delithiation behavior. It is found that a heat treatment under inert and reducing atmospheres increases the long-range order of rGO up to a temperature of 700 °C. At temperatures around 1000 °C, the crystallinity decreases. With decreasing oxygen content, a linear decrease in irreversible capacity during cycle 1 can be observed, along with a significant increase in electrical conductivity. This decrease in irreversible capacity can be observed despite an increase in specific surface area indicating the more significant influence of the oxygen content on the capacity loss. Consequently, the reversible capacity increases continuously up to a carbon content of 84.4 at% due to the thermal reduction. Contrary to expectations, the capacity decreases with further reduction. This can be explained by the loss of functional groups that will be lithiated reversibly, and a simultaneous reduction of long-range order, as concluded from dq/dU analysis in combination with XRD analysis.
AbstractRecent studies have hypothesized that the reinforcing effects of boehmite nanoparticles (BNPs) in polymer nanocomposites (PNCs) are partly related to the particles themselves and partly to the water released from the BNP during curing. In this work, PNCs made from dried BNP (dBNP) with concentrations up to 15 wt% are investigated to differentiate particle and water related effects. The observed trend of the storage modulus in dynamic mechanical thermal analysis measurements was found to be independent of the drying procedure. Stiffness maps from intermodulation atomic force microscopy showed that dBNP leads to a stiffening of the interphase surrounding the particles compared with the unaffected epoxy matrix, while a softer interphase was reported for PNCs with as received BNP. A slight decrease in the glass transition temperature was observed by broadband dielectric spectroscopy related to a lowered crosslink density due to the particles. A significantly higher decrease was reported for PNCs with BNP, attributed to water influencing the curing process. In conclusion, the stiffening of PNC with BNP is related to the particles themselves, while the release of water causes the formation of a soft interphase in the vicinity of the particles and a significant decrease in crosslink density.
Cryomyces antarcticus, a melanized cryptoendolithic fungus endemic to Antarctica, can tolerate environmental conditions as severe as those in space. Particularly, its ability to withstand ionizing radiation has been attributed to the presence of thick and highly melanized cell walls, which—according to a previous investigation—may contain both 1,8‐dihydroxynaphthalene (DHN) and L‐3,4 dihydroxyphenylalanine (L‐DOPA) melanin. The genes putatively involved in the synthesis of DHN melanin were identified in the genome of C. antarcticus. Most important is capks1 encoding a non‐reducing polyketide synthase (PKS) and being the ortholog of the functionally characterized kppks1 from the rock‐inhabiting fungus Knufia petricola. The co‐expression of CaPKS1 or KpPKS1 with a 4′‐phosphopantetheinyl transferase in Saccharomyces cerevisiae resulted in the formation of a yellowish pigment, suggesting that CaPKS1 is the enzyme providing the precursor for DHN melanin. To dissect the composition and function of the melanin layer in the outer cell wall of C. antarcticus, non‐melanized mutants were generated by CRISPR/Cas9‐mediated genome editing. Notwithstanding its slow growth (up to months), three independent non‐melanized Δcapks1 mutants were obtained. The mutants exhibited growth similar to the wild type and a light pinkish pigmentation, which is presumably due to carotenoids. Interestingly, visible light had an adverse effect on growth of both melanized wild‐type and non‐melanized Δcapks1 strains. Further evidence that light can pass the melanized cell walls derives from a mutant expressing a H2B‐GFP fusion protein, which can be detected by fluorescence microscopy. In conclusion, the study reports on the first genetic manipulation of C. antarcticus, resulting in non‐melanized mutants and demonstrating that the melanin is rather of the DHN type. These mutants will allow to elucidate the relevance of melanization for surviving extreme conditions found in the natural habitat as well as in space.
Defects are still common in metal components built with Additive Manufacturing (AM). Process monitoring methods for laser powder bed fusion (PBF-LB/M) are used in industry, but relationships between monitoring data and defect formation are not fully understood yet. Additionally, defects and deformations may develop with a time delay to the laser energy input. Thus, currently, the component quality is only determinable after the finished process.
Here, active laser thermography, a nondestructive testing method, is adapted to PBF-LB/M, using the defocused process laser as heat source. The testing can be performed layer by layer throughout the manufacturing process. We study our proposed testing method along experiments carried out on a custom research PBF-LB/M machine using infrared (IR) cameras.
Our work enables a shift from post-process testing of components towards in-situ testing during the AM process. The actual component quality is evaluated in the process chamber and defects can be detected between layers.
In this work, the thermoelectric material calcium cobaltite Ca3Co4O9 (CCO), a promising p-type conducting thermoelectric oxide with anisotropic properties, was processed by the powder aerosol deposition method (PAD) to form a dense ceramic CCO film with a thickness in the µm range. The prepared films were characterized regarding their microstructure and thermoelectric properties between room temperature and 900 °C. After heat treatment at 900 °C, the CCO PAD film in-plane shows excellent properties in terms of electrical conductivity (280 S/cm at 900 °C) and Seebeck coefficient (220 µV/K at 900 °C). The calculated power factor in-plane (ab) reaches with 1125 µW/(m K2) 40 % of the single crystal value, surpassing the known-properties of CCO bulk ceramics. Examination of the microstructure shows a strong fiber texture of the film as well as a strong coarsening of the grains during the first heat treatment up to 900 °C.
Development and fundamental understanding of precious-group-metal-free electrocatalysts is hampered by limitations in the quantification of the intrinsic activity of different catalytic sites and understanding the different reaction mechanisms. Comparing isomorphic nitrogen-doped carbons, Zn-N-Cs and Fe-N-Cs with the common tetrapyrrolic motif, a catalyst-independent outer-sphere rate-determining step in the alkaline oxygen reduction reaction is observed. Density functional theory (DFT) simulations on tetrapyrrolic model structures indicate the highest occupied molecular orbital (HOMO) level as a good descriptor for the catalytic activity. Contour plots suggest that the electron transfer occurs directly from the tetrapyrrolic coordination site, rather than from the metal center. Metal-free tetrapyrrolic N4 sites are discovered to be highly active oxygen reduction reaction (ORR) active sites in alkaline that reach turnover frequencies (TOF) of 0.33 and 1.84 s−1 at 0.80 and 0.75 VRHE in the order of magnitude of tetrapyrrolic Fe–N4 sites in the acidic ORR. While Zn-coordination lowers the HOMO level and therefore the catalytic activity, Fe-coordination lifts the HOMO level resulting in TOF values of 0.4 and 4 s−1 for tetrapyrrolic Fe–N4 sites at 0.90 and 0.85 VRHE, respectively. At higher mass activities, the peroxide reduction becomes rate-limiting, where highest peroxide production rates are observed for the nitrogen-doped carbon.
L-Lactide (LA) was polymerized with neat tin(II) 2-ethylhexanoate (SnOct2) in toluene at 115 °C at low concentration with variation of the LA/Cat ratio. Cyclic polylactides (cPLAs) with number average molecular weights (Mn) between 7 000 and 17 000 were obtained. MALDI-TOF mass spectrometry also revealed the formation of a few percent of linear chains. Crystalline cPLAs with Mn around 9 000 and 14 000 were annealed at 140 °C in the presence of ScOct2 or dibutyl-2-stanna-1,3-dithiolane (DSTL). Simultaneously, crystallites of extended linear chains and crystallites of extended cycles were formed regardless of the catalyst, indicating that transesterification reaction proceeded different for linear chains and for cycles, governed by thermodynamic control. The formation of extended chain crystallites with low dispersity indicates the existence of symproportionation of short and long chains. A complementary experiment was carried out with a PLA ethyl ester composed mainly of linear chains with a small fraction of cycles
This research was aimed at comparing the fire characteristics of different types of pepper in the context of explosion prevention. The following characteristics were studied: explosion pressure Pmax and Kst at selected concentrations, ignition temperature of the deposited dust layer from the hot surface, and minimum ignition energy. The comparison of the chemical properties of the used types of pepper was performed using TG/DSC. The results of the measurements suggest that different types of peppers exhibit different explosion characteristics. Each sample reached the maximum value of the explosion pressure and rate of pressure rise at different concentrations. The volume of the explosion chamber used also influenced the explosion characteristics. It is a consequence of the fact that the explosion characteristics strongly depend on the mechanism of action of a particular igniter. The minimum effect on the safety characteristics was observed when measuring the minimum ignition energy and the minimum ignition temperature of the dust layer from the hot surface. The results of the measurements suggest that different types of peppers exhibit different explosion characteristics. This information should then be considered in explosion prevention.
The Great Pacific Garbage Patch, a significant collection of plastic introduced by human activities, provides an ideal environment to study bacterial lifestyles on plastic substrates. We proposed that bacteria colonizing the floating plastic debris would develop strategies to deal with the ultravioletexposed substrate, such as the production of antioxidant pigments. We observed a variety of pigmentation in 67 strains that were directly cultivated from plastic pieces sampled from the Garbage Patch. The genomic analysis of four representative strains, each distinct in taxonomy, revealed multiple pathways for carotenoid production. These pathways include those that produce
less common carotenoids and a cluster of photosynthetic genes. This
cluster appears to originate from a potentially new species of the Rhodobacteraceae family. This represents the first report of an aerobic anoxygenic photoheterotrophic bacterium from plastic biofilms. Spectral analysis showed that the bacteria actively produce carotenoids, such as betacarotene and beta-cryptoxanthin, and bacteriochlorophyll a. Furthermore, we discovered that the genetic ability to synthesize carotenoids is more common in plastic biofilms than in the surrounding water communities. Our findings suggest that plastic biofilms could be an overlooked source of bacteria-produced carotenoids, including rare forms. It also suggests that photoreactive molecules might play a crucial role in bacterial biofilm communities in surface water.
The synergistic behavior of different silicon compounds is investigated in flame retardant biocomposites with aluminum trihydroxide (ATH) as the main flame retardant. The paper shows a new approach towards sustainable biocomposites through the implementation of thermoplastic starch (TPS), leather fibers from industrial waste streams, and non-hazardous flame retardants and synergists. In these multicomponent systems, the different components address different modes of action in the fire scenario. When ATH is partially substituted by glass frits or layered silicates, fire performance is enhanced without changing the total amount of filler in the polymer. In a biocomposite with 25 phr of fiber and 90 phr of ATH, substituting 5 phr of ATH for layered silicates increased the LOI from 31.5 vol % to 34.8 vol %, decreased the peak of heat release by 20%, and increased the UL 94 rating from V-1 to V-0.
The affinity constant, also known as the equilibrium constant, binding constant, equilibrium association constant, or the reciprocal value, the equilibrium dissociation constant (Kd), can be considered as one of the most important characteristics for any antibody–antigen pair. Many methods based on different technologies have been proposed and used to determine this value. However, since a very large number of publications and commercial datasheets do not include this information, significant obstacles in performing such measurements seem to exist. In other cases where such data are reported, the results have often proved to be unreliable. This situation may indicate that most of the technologies available today require a high level of expertise and effort that does not seem to be available in many laboratories. In this paper, we present a simple approach based on standard immunoassay technology that is easy and quick to perform. It relies on the effect that the molar IC50 approaches the Kd value in the case of infinitely small concentrations of the reagents. A two-dimensional dilution of the reagents leads to an asymptotic convergence to Kd. The approach has some similarity to the well-known checkerboard titration used for the optimization of immunoassays. A well-known antibody against the FLAG peptide, clone M2, was used as a model system and the results were compared with other methods. This approach could be used in any case where a competitive assay is available or can be developed. The determination of an affinity constant should belong to the crucial parameters in any quality control of antibody-related products and assays and should be mandatory in papers using immunochemical protocols.
Ceramic additive manufacturing (AM) requires a complex process chain with various post-processing steps that require expensive machines and special expertise. The key to further market penetration is AM that makes it possible to integrate into an already established ceramic process chain. Most successful AM technologies for ceramics are, however, based on processes that initially have been developed for polymeric materials. For ceramics AM, polymers or precursors are loaded with ceramic particles. This strategy facilitates the entry into AM, however the introduction of organic additives into the ceramic process chain represents a considerable technological challenge to ultimately obtain a ceramic component after additive shaping. In the present communication, two technologies based on ceramic suspensions will be introduced, the “layerwise slurry deposition” (LSD) and “laser induced slip casting” (LIS) technology. Both technologies take advantage of the high packing densities reached by conventional slip casting and moreover enable the processing of fines, even nanoparticles.
A key aspect in the development of multilayer inductors is the magnetic permeability of the ferrite layers. Here, the effects of different processing steps on the permeability of a NiCuZn ferrite is investigated. Dry pressed, tape cast, and co‐fired multilayer samples are analyzed. An automated data pipeline is applied to structure the acquired experimental data according to a domain ontology based on PMDco (Platform MaterialDigital core ontology). Example queries to the ontology show how the determined process‐property correlations are accessible to non‐experts and thus how suitable data for component design can be identified. It is demonstrated how the inductance of co‐fired multilayer inductors is reliably predicted by simulations if the appropriate input data corresponding to the manufacturing process is used.This article is protected by copyright. All rights reserved.
The classification of incineration bottom ash (IBA) as hazardous or non-hazardous according to ecotoxic hazard property HP14 is still under debate. In this context, only the compounds of Zn and Cu with the hazard statement code H410 are of relevance. With an approach based on the grouping of substances, it was shown that such substances are either readily water-soluble or slightly and sparingly soluble. The concentrations of readily soluble Cu and Zn compounds in IBA are far below the cut-off value of 0.1%. Slightly and sparingly soluble Zn and Cu compounds could be quantified in the first fraction of a four-step sequential extraction procedure. With the results from the complete sequence, the dimensionless synthesis toxicity index (STI) was calculated and was in the range of 494 to 1218 for the four investigated IBA samples. It was concluded that IBA can usually be classified as non-hazardous.
For industrial applications dealing with hydrogen, the definition of safety distances and the assessment of possible hazards emanating from releases is mandatory. Since hydrogen is usually stored and transported under pressure, one scenario to be considered is the momentum driven release of hydrogen from a leakage with subsequent ignition. In this scenario, the emitted heat radiation from the resulting jet flame to the surroundings has to be determined to define adequate safety distances. For hydrocarbon flames, different jet flame models are available to assess the hazards resulting from an ignited jet release. Since hydrogen flames differ from hydrocarbon flames in their combustion behavior, it has to be checked if these models are also applicable for hydrogen. To evaluate the accuracy of these models for hydrogen jet flames, tests at real-scale are carried out at the BAM Test Site for Technical Safety (BAM-TTS). Herein, the flame geometry and the heat radiation at defined locations in the surroundings are recorded for varying release parameters such as leakage diameter (currently up to 30 mm), release pressure (currently up to max. 250 bar) and mass flow (up to max. 0.5 kg/s). The challenge here is the characterization of the flame geometry in an open environment and its impact on the thermal radiation. Existing heat radiation data from the literature are mostly based on unsteady outflow conditions. For a better comparability with the steady state jet flame models, the experiments presented here are focused on ensuring a constant mass flow over the release duration to obtain a (quasi) stationary jet flame. In addition, stationary outflow tests with hydrocarbons (methane) were also carried out, which are intended to serve as reference tests for checking flame models based on hydrocarbon data.
The Bundesanstalt für Materialforschung und -prüfung (BAM) collaborates with TNO to develop a software framework for automated calibration of structural models based on monitoring data. The ultimate goal is to include such models in the asset management process of engineering structures. As a basis for developing the framework, a multi-span road bridge consisting of ten simply supported steel box girders was selected as a test case. Our group measured output-only vibration data from one box girder under ambient conditions. From the data, we determined eigenfrequencies and mode shapes. In parallel, we developed a preliminary structural model of the box girder for the purpose of predicting its modal properties. In this contribution, we provide an overview of the measurement campaign, the operational modal analysis, the structural modeling and qualitatively compare the identified with the predicted modes. As an outlook, we discuss the further steps in the calibration process and future applications of the calibrated model.
Managing aging engineering structures requires damage identification, capacity reassessment, and prediction of remaining service life. Data from structural health monitoring (SHM) systems can be utilized to detect and characterize potential damage. However, environmental and operational variations impair the identification of damages from SHM data. Motivated by this, we introduce a Bayesian probabilistic framework for building models and identifying damage in monitored structures subject to environmental variability. The novelty of our work lies (a) in explicitly considering the effect of environmental influences and potential structural damages in the modeling to enable more accurate damage identification and (b) in proposing a methodological workflow for model‐based structural health monitoring that leverages model class selection for model building and damage identification. The framework is applied to a progressively damaged reinforced concrete beam subject to temperature variations in a climate chamber. Based on deflections and inclinations measured during diagnostic load tests of the undamaged structure, the most appropriate modeling approach for describing the temperature‐dependent behavior of the undamaged beam is identified. In the damaged state, damage is characterized based on the identified model parameters. The location and extent of the identified damage are consistent with the cracks observed in the laboratory. A numerical study with synthetic data is used to validate the parameter identification. The known true parameters lie within the 90% highest density intervals of the posterior distributions of the model parameters, suggesting that this approach is reliable for parameter identification. Our results indicate that the proposed framework can answer the question of damage identification under environmental variations. These findings show a way forward in integrating SHM data into the management of infrastructures.
This data article presents a set of primary, analyzed, and digitalized mechanical testing datasets for nine copper alloys. The mechanical testing methods including the Brinell and Vickers hardness, tensile, stress relaxation, and low-cycle fatigue (LCF) testing were performed according to the DIN/ISO standards. The obtained primary testing data (84 files) mainly contain the raw measured data along with the testing metadata of the processes, materials, and testing machines. Five secondary datasets were also provided for each testing method by collecting the main meta- and measurement data from the primary data and the outputs of data analyses. These datasets give materials scientists beneficial data for comparative material selection analyses by clarifying the wide range of mechanical properties of copper alloys, including Brinell and Vickers hardness, yield and tensile strengths, elongation, reduction of area, relaxed and residual stresses, and LCF fatigue life. Furthermore, both the primary and secondary datasets were digitalized by the approach introduced in the research article entitled “Toward a digital materials mechanical testing lab” [1]. The resulting open-linked data are the machine-processable semantic descriptions of data and their generation processes and can be easily queried by semantic searches to enable advanced data-driven materials research.
Nowadays geotechnical engineering firms have powerful software tools to extent their consult-ing business also into dynamic soil-structure interaction, which before has been restricted to a rather small community of specialized experts in this field, and they certainly do. This is par-ticularly true with respect to non-seismic sources, that is all kinds of human induced vibrations. Hence, there is a demand from clients as well as from contractors to have guidance on the re-quirements as well as the limits of numerical modelling of soil-structure interaction. From the literature as well as from relevant standards, recommendations for the numerical modelling of soil-structure interaction problems involving seismic actions are well known, e. g. ASCE/SEI 4-16. There are, however, some particularities when dealing with human-induced vibrations, which are absent in seismic analyses. For human-induced excitations very little specific guid-ance has been published in the past. A machine foundation on a homogeneous half space ex-cited by harmonic loads with excitation frequency between 4 Hz and 64 Hz has been ana-lysed by means of several commercially available software packages. Parametric studies have been performed to verify if recommendations for seismic soil-structure analyses are valid for non-seismic analyses as well. This paper provides details on the benchmark example and the most important conclusions from the undertaken parametric studies.
AbstractTwo‐photon polymerization (2PP) additive manufacturing (AM) utilizes feedstocks of ceramic nanoparticles of a few nanometers in diameter, enabling the fabrication of highly accurate technical ceramic design with structural details as small as 500 nm. The performance of these materials is expected to differ from conventional AM ceramics, as nanoparticles and three‐dimensional printing at high resolution introduce new microstructural aspects. This study applies 2PP‐AM of yttria‐stabilized zirconia to investigate the mechanical response behavior under compressive load, probing the influence of smallest structural units induced by the line packing during the printing process, design of sintered microblocks, and sintering temperature and thereby microstructure. We find a dissipative mechanical response enhanced by sintering at lower temperatures than conventional. The pursued 2PP‐AM approach yields a microstructured material with an increased number of grain boundaries that proposedly play a major role in facilitating energy dissipation within the here printed ceramic material. This microplastic response is further triggered by the filigree structures induced by hollow line packing at the order of the critical defect size of ceramics. Together, these unique aspects made accessible by the 2PP‐AM approach contribute to a heterogeneous nano‐ and microstructure, and hint toward opportunities for tailoring the mechanical response in future ceramic applications.
ISO 14837-32:2015 and DIN EN 1998-1/NA:2021 as well as prEN 1997-2:2022 allow for us-ing correlations between the results of in-situ soil penetration tests and shear wave velocity (or shear modulus) to determine soil properties to be used in dynamic analyses. While the ISO and prEN standards even provide some recommendations on specific correlations to be used, the DIN standard does not. Due to the statistical nature of such correlations their general applica-bility has to be verified. We collected data sets from test sites from Germany as well as New Zealand at which cone penetration tests (CPT) as well as seismic site investigation methods were conducted. These sites comprise sandy soils as well as clayey soils, mixed soils as well as glacial soils. We compare the results of several correlations between CPT results and shear wave velocity. The accuracy of such correlations is assessed with respect to the accuracy of seismic in-situ tests. It turns out that for clean sands such correlations between CPT and Vs have a similar order of variability as seismic in-situ tests conducted at the same site. The higher the fines portion of the soil, the higher the variability of the statistical correlations, and conse-quently the less the general applicability. For glacial soils and other special soil types usage of statistical correlations to determine dynamic soil properties is not recommended.
The design of bridges often overlooks the vertical component of earthquakes or considers it of secondary importance, despite compelling evidence indicating specific structural damage caused by primary earthquake waves. Conversely, during the operational phase, the combined influence of ground motion and moving loads from vehicles can significantly impact the structural health monitoring (SHM) of bridges. This study aims to evaluate the simultaneous effect of vertical earthquake vibrations and moving vehicle loads on simply supported bridges. The research employs a practical methodology based on the eigenfunction expansion method to analyze change of deflection due to the effect of these concurrent forces under seven different earthquake records. It is shown that within a realistic range of vehicle mass and velocity, the average of changing the maximum deflection at the mid-span of the main beam (denoted as M_n) reaches up to 163% under various scenarios. Subsequently, the seismic parameters influencing this phenomenon are identified through a statistical analysis of set of 100 different earthquake records with unique features. A linear regression equation is presented to predict the M_n based on the earthquake specific properties. Additionally, to control the vertical vibration of bridge systems, a novel vibration suppression system utilizing steel pipe dampers is introduced, and its reliability is examined across a broad spectrum of bridge flexural rigidity. The results indicate that the system's efficiency depends on M_n and the soil type of the bridge construction, enabling a reduction in structural sections (up to 27%) while achieving the same maximum target deflection in the initial state. This efficiency leads to a more economical design solution, emphasizing the potential benefits of the proposed system for practical application.
NDT Data-Supported Structural Reassessments based on Regression Relations in Measuring Data Analysis
(2024)
Non-destructive Testing (NDT) provides valuable data about structural elements, supporting the assessment of existing infrastructures without incurring additional structural damage from inspections. Simultaneously, the uncertainty in measurement, which quantifies the quality of measurement results, plays a crucial role in decisions aimed at, e.g., optimizing maintenance strategies, rehabilitation works and Structural Health Monitoring (SHM) implementations. The Guide to the Expression of Uncertainty in Measurement (GUM) framework has already been considered for non-destructive concrete testing. Regarding that, extensive measurements with sophisticated scopes need to be conducted by experts as an obligatory process.
This study illustrates how NDT results describing the inner structure of a concrete element can effectively support the reassessment of bridges in operation. To achieve this, the study considers the various measurable positions of the resisting longitudinal tendons of a bridge structure to investigate the displacement change under dynamic service loads.
Furthermore, this study aims to simplify and optimize existing NDT data analysis procedures by employing regression analysis, enabling the detection of structural features. This regression analysis yields a modifier for determining the correct depth of an object within the structural element. The method is validated through laboratory experiments, including the use of an ultrasonic measurement system. As a result, it provides unbiased and accurately measured results, while ensuring that the measurement data can remain uncorrelated. Major advantages include efficient computation, a wider scope, and avoiding redundant information about the measuring process.
The findings demonstrate that employing the proposed NDT analysis method, with its enhanced practicability, can significantly augment the efficiency of NDT data-supported structural reassessments across various scenarios.
Automated computational workflows are a powerful concept that can improve the usability and reproducibility of simulation and data processing approaches. Although used very successfully in bioinformatics, workflow environments in materials science are currently commonly applied in the field of atomistic simulations. This work showcases the integration of a discrete element method (DEM) simulation of powder pressing in the convenient SimStack workflow environment. For this purpose, a Workflow active Node (WaNo) was developed to generate input scripts for the DEM solver using LIGGGHTS Open Source Discrete Element Method Particle Simulation code. Combining different WaNos in the SimStack framework makes it possible to build workflows and loop over different simulation or evaluation conditions. The functionality of the workflows is explained, and the added user value is discussed. The procedure presented here is an example and template for many other simulation methods and issues in materials science and engineering.
The injection of hydrogen into the natural-gas grid is an alternative during the process of a gradual decarbonization of the heat and power supply. When dealing with hydrogen-enriched natural gas mixtures, the performance of the reference equations of state habitually used for natural gas should be validated by using high-precision experimental thermophysical data from multicomponent reference mixtures prepared with the lowest possible uncertainty in composition. In this work, we present experimental density data for an 11-compound high-calorific (hydrogen-free) natural gas mixture and for two derived hydrogen-enriched natural gas mixtures prepared by adding (10 and 20) mol-% of hydrogen to the original standard natural gas mixture. The three mixtures were prepared gravimetrically according to ISO 6142–1 for maximum precision in their composition and thus qualify for reference materials. A single-sinker densimeter was used to determine the density of the mixtures from (250–350) K and up to 20 MPa. The experimental density results of this work have been compared to the densities calculated by three different reference equations of state for natural gas related mixtures: the AGA8-DC92 EoS, the GERG-2008 EoS, and an improved version of the GERG-2008 EoS. While relative deviations of the experimental density data for the hydrogen-free natural gas mixture are always within the claimed uncertainty of the three considered equations of state, larger deviations can be observed for the hydrogen-enriched natural gas mixtures from any of the three equations of state, especially for the lowest temperature and the highest pressures.
The systematic transfer of solvent-free, additive flame retardant (FR) formulations from epoxy resins to glass fiber-reinforced epoxy composites (GFRECs) through prepregs is difficult. Additionally, obtaining data on their post-fire mechanics is often challenging. Utilizing melamine polyphosphate (MPP), ammonium polyphosphate (APP), and silane-coated ammonium polyphosphate (SiAPP) FRs with low-melting inorganic silicates (InSi) in an 8:2 proportion and 10% loading by weight in a diglycidyl ether of bisphenol A (DGEBA) resin, a systematic investigation of the processing properties, room-temperature mechanics, and temperature-based mechanics of the systems was performed. The resin was cured with a dicyandiamide hardener (DICY) and a urone accelerator. The results revealed no substantial impact of these FRs at the current loading on the resin's glass transition temperature or processability. However, the fire residues from cone calorimetry tests of the composites containing FRs were found to be only 15-20% of the thickness of the resins, implying a suppression of intumescence upon transfer. At room temperature, the decrease in the flexural modulus for the composites containing FRs was negligible. Exposure of the composites in a furnace at 400°C as a preliminary study before ignition tests was shown to cause significant flexural moduli reductions after 2.5 min of exposure and complete delamination after 3 min making further testing unviable. This study emphasizes the need for future research on recovering modes of action upon transfer of FR formulations from resins to composites. Based on the challenges outlined in this investigation, sample adaptation methods for post-fire analysis will be developed in a future study.
Addressing a strategy for publishing open and digital research data, this article presents the approach for streamlining and automating the process of storage and conversion of research data to those of semantically queryable data on the web. As the use case for demonstrating and evaluating the digitalization process, the primary datasets from low‐cycle‐fatigue testing of several copper alloys are prepared. The fatigue test ontology (FTO) and ckan.kupferdigital data management system are developed as two main prerequisites of the data digitalization process. FTO has been modeled according to the content of the fatigue testing standard and by reusing the basic formal ontology, industrial ontology foundry core ontology, and material science and engineering ontology. The ckan.kupferdigital data management system is also constructed in such a way that enables the users to prepare the protocols for mapping the datasets into the knowledge graph and automatically convert all the primary datasets to those machine‐readable data which are represented by the web ontology language. The retrievability of the converted digital data is also evaluated by querying the example competency questions, confirming that ckan.kupferdigital enables publishing open data that can be highly reused in the semantic web.
Ultra-High-Performance Fiber-Reinforced Cementitious Composite (UHPFRC) offers several advantages compared to concrete, notably due to the strain hardening behavior under tensile actions. Structures made of this composite material are lightweight and highly durable, thanks to the UHPFRC waterproofing quality. Nonetheless, the tensile behavior leads to a different cracking pattern than conventional concrete and is not fully understood yet. This paper presents a combined approach using both passive ultrasonic (US) stress wave (or acoustic emission) and active US stress wave monitoring to localize and quantify damage progression in a full-scale UHPFRC beam during experimental load testing. The proposed monitoring approach involves 24 US transducers that are embedded randomly throughout a 4.2- meter-long laboratory UHPFRC T-beam. Continuous monitoring enabled accurate localization of US stress sources caused by loading-induced cracking as well as from pulses generated by the embedded US transducers. This study shows that it is possible to predict the location and shape of the macro-crack that is linked to structural failure early on, i.e., just after the end of the elastic domain. This combined approach opens new possibilities to monitor the structural behavior and detect damage on UHPFRC structures before they affect the structural behavior in terms of deflection and strain.
To safely dispose of nuclear waste in underground facilities, engineered barrier systems are needed to seal shafts and galleries. The material used in these barriers must be adapted to the host rock parameters. Shrinking and cracking must be avoided to provide a barrier with almost zero permeability. For repositories in salt rock environments, several types of salt concrete (SC) are possible construction materials. Within the project SealWasteSafe, we compared the behavior of an innovative alkali-activated material (AAM) with standard SC in their hydration and hardening phase. To monitor the microstructural changes within the two materials SC and AAM, acoustic emission (AE) signals have been recorded for up to ~250 days on 340-litercubic specimens. The phenomenon of AE is defined as the emission of elastic waves in materials due to the release of localized internal energy. Such energy release can be caused by the nucleation of micro-fracture, e.g., in concrete while curing or when exposed to load. The occurrence of AE events gives first rough indications of microstructural changes and potentially occurring cracking and thus, provides insights for structural health monitoring (SHM). The results show, that for the first 28 days after casting, less AE activity was detected in the AAM compared to SC. After 61 days, in the AAM material, the number of AE events exceeded those observed in the SC. However, the majority of the AE detected and located in AAM was related to surface effects, and not to microstructural changes or occurring cracks within the bulk volume. Additionally, the source location analysis indicated, that despite lower activity in SC, we observed some clustering of the events. In contrast, in AAM, the activity inside the specimen is randomly distributed over the whole volume. The monitoring results help to estimate the material’s sealing properties which are crucial to assess their applicability as sealing material for engineered barriers.
Combined passive ultrasonic (US) stress wave [better known as acoustic emission (AE)] and active US stress wave monitoring has been shown to provide a more holistic picture of ongoing fracture processes, damage progression, as well as slowly occurring aging and degradation mechanisms in concrete structures. Traditionally, different data analysis techniques have been used to analyze the data generated from these two monitoring techniques. For passive US stress wave monitoring, waveform amplitudes, hit rates, source localization, and b-value analysis, among others, have been used to detect and locate cracking. On the other hand, amplitude tracking, magnitude squared coherence (MSC), and coda wave interferometry (CWI) are examples of analyses that have been employed for active US stress wave monitoring. In this paper, we explore some of these data analysis techniques and show where their respective applications and limitations might be. After providing an overview of the monitoring approach and the different data analysis techniques, results and observations from selected laboratory experiments are discussed. Finally, suggestions for further work are proposed.
Manufacturing and Application of Lightweight Aggregates from Construction and Demolition Waste
(2024)
The objective of the REALight project is the development of a thermal process to produce lightweight aggregates in pilot scale and the implantation of a method to recover gypsum. Beside construction and demolition waste, various industrial by‐products are studied as raw materials. The raw materials have so far been unused or used in applications with lower quality requirements. To prove the performance of the lightweight aggregates, their technical properties are tested and their use in different applications is studied, e.g., for lightweight mortars as well as lightweight concretes.
Despite the physiological and pathophysiological significance of microenvironmental gradients, e.g., for diseases such as cancer, tools for generating such gradients and analyzing their impact are lacking. Here, we present an integrated microfluidic-based workflow that mimics extracellular pH gradients characteristic of solid tumors while enabling high-resolution live imaging of, e.g., cell motility and chemotaxis, and preserving the capacity to capture the spatial transcriptome. Our microfluidic device generates a pH gradient that can be rapidly controlled to mimic spatiotemporal microenvironmental changes over cancer cells embedded in a 3D matrix. The device can be reopened allowing immunofluorescence analysis of selected phenotypes, as well as the transfer of cells and matrix to a Visium slide for spatially resolved analysis of transcriptional changes across the pH gradient. This workflow is easily adaptable to other gradients and multiple cell types and can therefore prove invaluable for integrated analysis of roles of microenvironmental gradients in biology.
AbstractThe correlation between altered extracellular pH and various pathological conditions, including cancer, inflammation and metabolic disorders, is well known. Bulk pH measurements cannot report the extracellular pH value at the cell surface. However, there is a limited number of suitable tools for measuring the extracellular pH of cells with high spatial resolution, and none of them are commonly used in laboratories around the world. In this study, a versatile ratiometric nanosensor for the measurement of extracellular pH was developed. The nanosensor consists of biocompatible polystyrene nanoparticles loaded with the pH-inert reference dye Nile red and is surface functionalized with a pH-responsive fluorescein dye. Equipped with a targeting moiety, the nanosensor can adhere to cell membranes, allowing direct measurement of extracellular pH at the cell surface. The nanosensor exhibits a sensitive ratiometric pH response within the range of 5.5–9.0, with a calculated pKa of 7.47. This range optimally covers the extracellular pH (pHe) of most healthy cells and cells in which the pHe is abnormal, such as cancer cells. In combination with the nanosensors ability to target cell membranes, its high robustness, reversibility and its biocompatibility, the pHe nanosensor proves to be well suited for in-situ measurement of extracellular pH, even over extended time periods. This pH nanosensor has the potential to advance biomedical research by improving our understanding of cellular microenvironments, where extracellular pH plays an important role.
AbstractLithium‐ion batteries, essential for electronics and electric vehicles, predominantly use cathodes made from critical materials like cobalt. Sulfur‐based cathodes, offering a high theoretical capacity of 1675 mAh g−1 and environmental advantages due to sulfur's abundance and lower toxicity, present a more sustainable alternative. However, state‐of‐the‐art sulfur‐based electrodes do not reach the theoretical capacities, mainly because conventional electrode production relies on mixing of components into weakly coordinated slurries. Consequently, sulfur‘s mobility leads to battery degradation—an effect known as the “sulfur‐shuttle”. This study introduces a solution by developing a microporous, covalently‐bonded, imine‐based polymer network grown in situ around sulfur particles on the current collector. The polymer network (i) enables selective transport of electrolyte and Li‐ions through pores of defined size, and (ii) acts as a robust host to retain the active component of the electrode (sulfur species). The resulting cathode has superior rate performance from 0.1 C (1360 mAh g−1) to 3 C (807 mAh g−1). Demonstrating a high‐performance, sustainable sulfur cathode produced via a simple one‐pot process, our research underlines the potential of microporous polymers in addressing sulfur diffusion issues, paving the way for sulfur electrodes as viable alternatives to traditional metal‐based cathodes.
High‐Entropy Alloys and Their Affinity with Hydrogen: From Cantor to Platinum Group Elements Alloys
(2024)
AbstractProperties of high‐entropy alloys are currently in the spotlight due to their promising applications. One of the least investigated aspects is the affinity of these alloys to hydrogen, its diffusion, and reactions. In this study, high pressure is applied at ambient temperature and stress‐induced diffusion of hydrogen is investigated into the structure of high‐entropy alloys (HEA) including the famous Cantor alloy as well as less known, but nevertheless important platinum group (PGM) alloys. By applying X‐ray diffraction to samples loaded into diamond anvil cells, a comparative investigation of transition element incorporating HEA alloys in Ne and H2 pressure‐transmitting media is performed at ambient temperature. Even under stresses far exceeding conventional industrial processes, both Cantor and PGM alloys show exceptional resistance to hydride formation, on par with widely used industrial grade Cu–Be alloys. The observations inspire optimism for practical HEA applications in hydrogen‐relevant industry and technology (e.g., coatings, etc), particularly those related to transport and storage.
Revolutionizing our polymer industry for adaption to a sustainable carbon circular economy has become one of today’s most demanding challenges. Exploiting renewable resources to replace fossil-fuel—based plastics with biopolymers such as poly(lactic acid) (PLA) is inevitable while using waste streams as a raw material resource at least is promising. When it comes to using PLA as technical polymer, its high flammability must be addressed by flame retardants compatible with the thermoplastic processing of PLA and its compostability. This study proposes microalgae enriched with phosphorus from wastewater (P-Algae) as an elegant way towards a kind of sustainable organophosphorus flame retardant. The concept is demonstrated by investigating the processing, pyrolysis, flammability, and fire behavior of PLA/P-Algae, while varying the P-Algae content and comparing P-Algae with four alternative bio-fillers (phosphorylated lignin, biochar, thermally treated sewage sludge, and metal phytate) with different P-contents as meaningful benchmarks.
Polymers of intrinsic microporosity exhibit a combination of high gas permeability and reasonable permselectivity, which makes them attractive candidates for gas separation membrane materials. The diffusional selective gas transport properties are connected to the molecular mobility of these polymers in the condensed state. Incoherent quasielastic neutron scattering was carried out on two polymers of intrinsic microporosity, PIM-EA-TB(CH3) and its demethylated counterpart PIM-EA-TB(H2), which have high Brunauer–Emmett–Teller surface area values of 1030 m2 g-1 and 836 m2 g-1, respectively. As these two polymers only differ in the presence of two methyl groups at the ethanoanthracene unit, the effect of methyl group rotation can be investigated solely. To cover a broad dynamic range, neutron time-of-flight was combined with neutron backscattering. The demethylated PIM-EA-TB(H2) exhibits a relaxation process with a weak intensity at short times. As the backbone is rigid and stiff this process was assigned to bendand-flex fluctuations. This process was also observed for the PIM-EA-TB(CH3). A further relaxation process is found for PIM-EA-TB(CH3), which is the methyl group rotation. It was analyzed by a jump-diffusion in a three-fold potential considering also the fact that only a fraction of the present hydrogens in PIM-EATB(CH3) participate in the methyl group rotation. This analysis can quantitatively describe the q dependence of the elastic incoherent structure factor. Furthermore, a relaxation time for the methyl group rotation can be extracted. A high activation energy of 35 kJ mol-1 was deduced. This high activation energy evidences a strong hindrance of the methyl group rotation in the bridged PIM-EA-TB(CH3) structure.
Multicomponent reactions (MCRs) offer a platform to create different chemical structures and linkages for highly stable covalent organic frameworks (COFs). As an illustrative example, the multicomponent Povarov reaction generates 2,4-phenylquinoline from aldehydes and amines in the presence of electron-rich alkenes. In this study, we introduce a new domino reaction to generate unprecedented 2,3-phenylquinoline COFs in the presence of epoxystyrene. This work thus presents, for the first time, structural isomeric COFs produced by multicomponent domino and Povarov reactions. Furthermore, 2,3-phenylquinolines can undergo a Scholl reaction to form extended aromatic linkages. With this approach, we synthesize two thermally and chemically stable MCR-COFs and two heteropolyaromatic COFs using both domino and in situ domino and Scholl reactions. The structure and properties of these COFs are compared with the corresponding 2,4-phenylquinoline-linked COF and imine-COF, and their activity toward benzene and cyclohexane sorption and separation is investigated. The position of the pendant phenyl groups within the COF pore plays a crucial role in facilitating the industrially important sorption and separation of benzene over cyclohexane. This study opens a new avenue to construct heteropolyaromatic COFs via MCR reactions.
In materials science, traditional techniques for analyzing layered structures are essential for obtaining information about local structure, electronic properties and chemical states. While valuable, these methods often require high vacuum environments and have limited depth profiling capabilities. The grazing exit x-ray absorption near-edge structure (GE-XANES) technique addresses these limitations by providing depth-resolved insight at ambient conditions, facilitating in situ material analysis without special sample preparation. However, GE-XANES is limited by long data acquisition times, which hinders its practicality for various applications. To overcome this, we have incorporated Bayesian optimization (BO) into the GE-XANES data acquisition process. This innovative approach potentially reduces measurement time by a factor of 50. We have used a standard GE-XANES experiment, which serve as reference, to validate the effectiveness and accuracy of the BO-informed experimental setup. Our results show that this optimized approach maintains data quality while significantly improving efficiency, making GE-XANES more accessible to a wider range of materials science applications.
Flexible anisotropic magnetoresistive sensors for novel magnetic flux leakage testing capabilities
(2024)
Rigid magnetic field sensors such as anisot Hall sensors have been used for years and have become industry standard for electromagnetic non-destructive testing (NDT). Recent technological developments in the field of flexible electronics allow for the fabrication of reshapeable magnetic field sensors on flexible substrates via thin-film deposition or printing. The magnetic properties of these sensors have comparable characteristics to industry-standard rigid magnetic field sensors, with the added ability of adapting to the surface of complex components and scanning in contact with the sample surface. This improves defect detectability and magnetic signal strength by minimizing the scanning lift-off (LO) distance. In this article flexible AMR sensors mounted on a rotative mechanical holder were used to scan a semi-circular ferromagnetic sample with 3 reference defects via magnetic flux leakage (MFL) testing, thus demonstrating the applicability of this type of sensors for the scanning of curved samples. In order to benchmark the performance of these sensors in comparison to industry standard rigid magnetic field sensors, a ferromagnetic sample with 10 reference defects of different depths was scanned employing flexible AMR and rigid GMR sensors. Defects with depths ranging from 110 μm up to 2240 μm were detected with an signal-tonoise ratio (SNR) of 2.7 up to 27.9 (for flexible AMR sensors) and 6.2 up to 72.3 (for rigid GMR sensors), respectively. A 2D magnetometer mapping of the sample with a spatial scanning step of 10 × 50 μm2 (flexible AMR) and 16 × 100 μm2 (rigid GMR) was obtained. The results show that this type of sensor can be used for high-resolution and high-detail mapping of defects on the surface of planar and non-planar ferromagnetic samples since the scanning lift-off distance is equal to the substrate thickness of 20 μm for in-contact scanning. The SNR comparison between flexible and rigid sensors shows that the performance of the flexible AMR sensors employed is not very far behind the performance of the rigid GMR sensors used.
It is an essential requirement for all building products to ensure durability of their fire safety. Throughout the working life of products, intumescent coatings are aged by certain climatic factors. To predict a lifetime of several years, generally the behaviour of the intumescent coating is extrapolated based on accelerated artificial ageing. The established German and European procedures to assess the durability assume a working life of at least 10 years. For a longer period, additional evidence is required; yet the procedure and the specifications to justify this are not described. In addition to addressing this formal lack, from a scientific point of view it is necessary to investigate the degradation of intumescent coatings in detail and to propose a reliable test concept to assess durability for more than 10 years. This paper summarises the existing knowledge about the ageing of intumescent coatings. The results of various demanding weathering approaches are presented for two intumescent coatings tested in a joint research project. Moreover, formulations with a reduced amount of functionally relevant components were analysed to gain insight into the associated effects. Derived from these research results and knowledge, recommendations are proposed to assess the durability of intumescent coatings for more than 10 years based on a combination of verifications.
Quantum dots (QDs) are remarkable semiconductor nanoparticles, whose optical properties are strongly size-dependent. Therefore, the real-time monitoring of crystal growth pathway during synthesis gives an excellent opportunity to a smart design of the QDs luminescence. In this work, we present a new approach for monitoring the formation of QDs in aqueous solution up to 90 °C, through in situ luminescence analysis, using CdTe as a model system. This technique allows a detailed examination of the evolution of their light emission. In contrast to in situ absorbance analysis, the in situ luminescence measurements in reflection geometry are particularly advantageous once they are not hindered by the concentration increase of the colloidal suspension. The synthesized particles were additionally characterized using X-ray diffraction analysis, transition electron microscopy, UV-Vis absorption and infrared spectroscopy. The infrared spectra showed that 3-mercaptopropionic acid (MPA)-based thiols are covalently bound on the surface of QDs and microscopy revealed the formation of CdS. Setting a total of 3 h of reaction time, for instance, the QDs synthesized at 70, 80 and 90 °C exhibit emission maxima centered at 550, 600 and 655 nm. The in situ monitoring approach opens doors for a more precise achievement of the desired emission wavelength of QDs.
The glass system (50NaPO3–20BaF2–10CaF2–20GdF3)-xTbCl3 with x = 0.3, 1, 3, 5, and 10 wt % was investigated. We successfully produced transparent glass ceramic (GC) scintillators with x = 1 through a melt-quenching process followed by thermal treatment. The luminescence and crystallization characteristics of these materials were thoroughly examined using various analytical methods. The nanocrystallization of Tb3+-doped Na5Gd9F32 within the doped fluoride-phosphate glasses resulted in enhanced photoluminescence (PL) and radioluminescence (RL) of the Tb3+ ions. The GC exhibited an internal PL quantum yield of 33 % and the integrated RL intensity across the UV-visible range was 36 % of that reported for the commercial BGO powder scintillator. This research showcases that Tb-doped fluoridephosphate GCs containing nanocrystalline Na5Gd9F32 have the potential to serve as efficient scintillators while having lower melting temperature compared to traditional silicate and germanate glasses.
Upconverting nanoparticles are essential in modern photonics due to their ability to convert infrared light to visible light. Despite their significance, they exhibit limited brightness, a key drawback that can be addressed by combining them with plasmonic nanoparticles. Plasmon-enhanced upconversion has been widely demonstrated in dry environments, where upconverting nanoparticles are immobilized, but constitutes a challenge in liquid media where Brownian motion competes against immobilization.
This study employs optical tweezers for the three-dimensional manipulation of an individual upconverting nanoparticle, enabling the exploration of plasmon-enhanced upconversion luminescence in water. Contrary to expectation, experiments reveal a long-range (micrometer scale) and moderate (20%) enhancement in upconversion luminescence due to the plasmonic resonances of gold nanostructures. Comparison between experiments and numerical simulations evidences the key role of Brownian motion. It is demonstrated how the three-dimensional Brownian fluctuations of the upconverting nanoparticle lead to an “average effect” that explains the magnitude and spatial extension of luminescence enhancement.
Silicon isotope fractionation during silicification is poorly understood and impedes our ability to decipher paleoenvironmental conditions from Si isotopes in ancient cherts. To investigate isotope fractionation during silica-for-carbonate replacement we analyzed the microscale Si and O isotope composition in different silica phases in a silicified zebra dolostone as well as their bulk δ18O and Δ’17O compositions. The subsequent replacement of carbonate layers is mimicked by decreasing δ18O and δ30Si. The textural relationship and magnitude of Si and O isotope fractionation is best explained by near-quantitative silica precipitation in an open system with finite Si. A Rayleigh model for silicification suggests positive Ɛ30/28Si during silicification, conforming with predictions for isotope distribution at chemical equilibrium from ab-initio models. Application of the modelled Ɛ30Si-T relationship yields silicification temperatures of approx. 50°C. To reconcile the δ18Ochert composition with these temperatures, the δ18O of the fluid must have been between -2.5 and -4 ‰, compositions for which the quartz phases fall close to the oxygen equilibrium fractionation line in three-isotope space. Diagenetic silica replacement appears to occur in O and Si isotopic equilibrium allowing reconstructions of temperatures of silicification from Si isotopes and derive the δ18O composition of the fluid – a highly desired value needed for accurate reconstructions of the temperature- and δ18O histories of the oceans.
Distributed fiber optic strain sensing for structural health monitoring of 70 MPa hydrogen vessels
(2024)
We report on the development and testing of 70 MPa hydrogen pressure vessels with integrated fiber optic sensing fibers for automotive use. The paper deals with the condition monitoring of such composite pressure vessels (CPVs) using the optical backscatter reflectometry (OBR) applied for a distributed fiber optic strain sensing along fully integrated polyimide-coated single-mode glass optical fiber (SM-GOF). The sensing fibers were embedded into the vessel structure by wrapping them over the polymer liner during the manufacturing process of the carbon fiber reinforced polymer (CFRP). Detecting local strain events by the integrated fiber optic sensors can be an opportunity for monitoring the material degradation of CPVs under static and cyclic loading.
We present a distributed polymer optical fiber sensor system for deformation monitoring of geotechnical infrastructure. The sensor system is based on the digital incoherent optical frequency domain reflectometry (I-OFDR) for the detection of local strain events along a perfluorinated polymer optical fiber (PF-POF) used as a sensing fiber. For the best possible load transfer, the PF-POFs were integrated onto geosynthetics which pose a sensor carrier for the sensing fiber. By using elastic PF-POF instead of a standard glass fiber as a sensing fiber the strain range of geosynthetics-integrated fiber optic sensors could be extended up to 10 % in accordance with the end-user requirements.
Hydrogen pressure vessels are among the most essential components for reliable hydrogen technology. Under current regulations, a mostly conservative strategy is employed, restricting the usage time of hydrogen pressure vessels without providing information on the real remaining lifetime. During the service life, pressure vessels are inspected periodically. However, no established method that can provide continuous monitoring or information on the remaining safe service life of the vessel. In this paper, we propose a sensor network for Structural Health Monitoring (SHM) of hydrogen pressure vessels where data from all sensors are collected and centrally evaluated. Specifically, we integrate three different SHM sensing technologies namely Guided Wave ultrasonics (GW), Acoustic Emission testing (AT), and distributed Fiber Optic Sensing (FOS). This integrated approach offers significantly more information and could therefore enable a transition from costly and time-consuming periodic inspections to more efficient and modern predictive maintenance strategies, including Artificial Intelligence (AI)-based evaluation. This does not only have a positive effect on the operational costs but enhances safety through early identification of critical conditions in the overall system in real-time. We demonstrate an experimental set-up of a lifetime test where a Type IV Composite Overwrapped Pressure Vessel (COPV) is investigated under cyclic loading instrumented with AT, FOS, and GW methods. We acquired data from the sensor network until the pressure vessel failed due to material degradation. The data collected using the three different SHM sensor technologies is planned to be evaluated individually, using data fusion, and AI. In the future, we aim to integrate the measurement setup into a hydrogen refueling station with the data stream implemented into a digital signal processing chain and a digital twin.
The transition toward a hydrogen-based economy requires a widespread transport and distribution network, and repurposed natural gas pipelines are a viable option. An assessment of the hydrogen-induced degradation of pipeline steels is needed to inject H2 gas into the existing infrastructure safely. The conservative and standardized method consists of in-situ tensile tests in an autoclave filled with high-pressure hydrogen gas. A proposed alternative method involves
using a hollow specimen as containment volume and applying the gas pressure in the inner cavity.
This technique has lower costs and shorter test preparation time but is not standardized yet. This study aims to evaluate and compare the tensile properties of API 5L X65 pipeline steel in two states: vintage and modern. The influence of the surface roughness is investigated through parallel tests with drilled and reamed specimens. Hydrogen tests are compared with reference tests in an inert environment. A significant hydrogen-induced decrease in tensile properties is observed, and no significant difference between vintage and modern X65 can be drawn. The reduction in tensile properties is more significant in specimens with higher inner surface roughness. The evaluation of surface conditions appears crucial when assessing the HE susceptibility of hydrogen transport and storage equipment.
Structural health monitoring of hydrogen pressure vessels using distributed fiber optic sensing
(2024)
We report on distributed fiber optic sensing-based monitoring of hydrogen composite overwrapped pressure vessels (COPV) to simultaneously increase the operational lifespan and mitigate maintenance costs. Our approach represents, to the best of our knowledge, the first application of distributed fiber optic sensing for COPV Type IV monitoring, where the sensing fibers are attached to the surface, rather than integrated into the composite material. Specifically, we attach an optical fiber of 50 m to the pressure vessel's surface, covering both the cylindrical and dome sections. We note that our fiber optic sensing technique relies on swept wavelength interferometry providing strain information along the entire length of the optical fiber with high spatial resolution even at the millimeter scale. When the vessel is pressurized, the sensing optical fiber shows a linear strain response to pressure at every position along the fiber. After thousands of load cycles, the vessel finally fails with the optical fiber detecting and precisely localizing the damage in the vessel’s blind dome area. Furthermore, we discuss the potential of state-of-the-art signal processing methods and machine learning for advancing predictive maintenance. This could reduce the number of regular inspections, mitigate premature maintenance costs, and simultaneously increase the vessel’s remaining safe service life. We believe that the structural health monitoring of hydrogen pressure vessels with fiber optic sensors can enhance trust in hydrogen technology contributing to the energy transition in the future.
Modern dry pressing of ceramic powders using spray‐dried granulates cannot avoid the occurrence of defects related to persisting inter‐ and intra‐granulate interstitial voids. These constitute the parent defect size population limiting the application of polycrystalline ceramics in high‐stress conditions. The mitigation of such defects could widen the range of application in technical and biomedical engineering, reduce the safety range for design, and extend the lifetime of components. Herein, the Weibull size‐effect on strength in size‐partitioned Yttria‐stabilized zirconias (YSZ) feedstocks is used to explore the viability of changing the density distribution of granulate sizes as an effective strategy to obtain a denser particle packing that could reduce the size distribution of strength‐limiting pressing defects. In a direct assessment of critical defect size using multiscale strength testing with a dataset of ≈1300 values, the success of such an approach in increasing the strength reliability for small volume components is demonstrated, along with its ultimate failure in altering the defect size distribution in sintered YSZ ceramics across several length scales. Finally, it is shown that granule morphology (spherical or dimpled) fails to affect the defect density and size distribution in YSZ ceramics.
Compared to mechanisms like solid solution strengthening, the stacking fault energy (SFE) should be considered as a further factor that influences the material properties. The effect of SFE of alloys or individual elements on strength and resistance can vary considerably. In the high-temperature regime above 700 ◦C, there are still significant gaps in the knowledge about the effect of the SFE on the mechanical properties of single-phase alloys. The effect of SFE on creep resistance of two face-entered cubic equiatomic medium and high entropy alloys, CrCoNi and CrMnFeCoNi, respectively, is evaluated to fill parts of these gaps. Using the Bridgman solidification process, the alloys were produced as single crystals and crept under vacuum at 700 ◦C up to 1100 ◦C. This work shows a significant impact of the lower SFE of CrCoNi on the creep behavior compared to the results of previous investigations of CrMnFeCoNi. The creep resistance of the former is higher over the complete temperature range. At very high temperatures, the strengthening effect of the stacking faults is significantly present. The formation of tetragonal stacking faults and extended dislocation nodes can be identified as the reason for this effect.
Additively manufactured components are characterized by heterogeneous mechanical properties due to variations of the microstructure, flaws and residual stresses resulting from the inhomogeneous fabrication process. The large number of influencing factors poses a further challenge in understanding the correlation between material properties, process parameters and component geometry. Therefore, the qualification of components based on witness specimens produced within the same job is questionable. This work aims to present a new strategy for the characterization of PBF-LB/M components based on representative specimens. The key assumption is the feasibility of a transfer of the thermal history from a component to a specimen. It is assumed that similar material properties are determined for components and specimens produced adopting a similar thermal history. After the definition of a region of interest in the component, a combination of thermal analyses by means of finite elements and in-situ experimental determination of the thermal history through infrared thermography is used to produce test coupons with a similar thermal history. The effectiveness of the procedure is demonstrated on a pressure vessel for applications in the chemical industry.
Quantitative microstructural analysis of XCT 3D images is key for quality assurance of materials and components. In this paper we implement a Graph Convolutional Neural Network (GCNN) architecture to segment a complex Al-Si Metal Matrix composite XCT volume (3D image). We train the model on a synthetic dataset and we assess its performance on both synthetic and experimental, manually-labeled, datasets. Our simple GCNN shows a comparable performance, measured via the Dice score, to more standard machine learning methods, but uses a greatly reduced number of parameters (less than 1/10 of parameters), features low training time, and needs little hardware resources. Our GCNN thus achieves a cost-effective reliable segmentation.
The biogenesis of iron–sulfur (Fe/S) proteins entails the synthesis and trafficking of Fe/S clusters, followed by their insertion into target apoproteins. In eukaryotes, the multiple steps of biogenesis are accomplished by complex protein machineries in both mitochondria and cytosol. The underlying biochemical pathways have been elucidated over the past decades, yet the mechanisms of cytosolic [2Fe-2S] protein assembly have remained ill-defined. Similarly, the precise site of glutathione (GSH) requirement in cytosolic and nuclear Fe/S protein biogenesis is unclear, as is the molecular role of the GSH-dependent cytosolic monothiol glutaredoxins (cGrxs). Here, we investigated these questions in human and yeast cells by various in vivo approaches. [2Fe-2S] cluster assembly of cytosolic target apoproteins required the mitochondrial ISC machinery, the mitochondrial transporter Atm1/ABCB7 and GSH, yet occurred independently of both the CIA system and cGrxs. This mechanism was strikingly different from the ISC-, Atm1/ABCB7-, GSH-, and CIA-dependent assembly of cytosolic–nuclear [4Fe-4S] proteins. One notable exception to this cytosolic [2Fe-2S] protein maturation pathway defined here was yeast Apd1 which used the CIA system via binding to the CIA targeting complex through its C-terminal tryptophan. cGrxs, although attributed as [2Fe-2S] cluster chaperones or trafficking proteins, were not essential in vivo for delivering [2Fe-2S] clusters to either CIA components or target apoproteins. Finally, the most critical GSH requirement was assigned to Atm1-dependent export, i.e. a step before GSH-dependent cGrxs function. Our findings extend the general model of eukaryotic Fe/S protein biogenesis by adding the molecular requirements for cytosolic [2Fe-2S] protein maturation.
The presence of endocrine-disrupting compounds (EDCs) in water poses a significant threat to human and animal health, as recognized by regulatory agencies throughout the world. The Yeast Estrogen Screen (YES) assay is an excellent method to evaluate the presence of these compounds in water due to its simplicity and capacity to assess the bioaccessible forms/fractions of these compounds. In the presence of a compound with estrogenic activity, Saccharomyces cerevisiae cells, containing a lacZ reporter gene encoding the enzyme β-galactosidase, are induced, the enzyme is synthesised, and released to the extracellular medium. In this work, a YES-based approach encompassing the use of a lacZ reporter gene modified strain of S. cerevisiae, microcarriers as solid support, and a fluorescent substrate, fluorescein di-β-D-galactopyranoside, is proposed, allowing for the assessment of EDCs’ presence after only 2 h of incubation. The proposed method provided an EC50 of 0.17 ± 0.03 nM and an LLOQ of 0.03 nM, expressed as 17β-estradiol. The assessment of different EDCs provided EC50 values between 0.16 and 1.2 × 103 nM. After application to wastewaters, similar results were obtained for EDCs screening, much faster, compared to the conventional 45 h spectrophotometric procedure using a commercial kit, showing potential for onsite high-throughput screening of environmental contamination.
Peptide pools consist of short amino acid sequences and have proven to be versatile tools in various research areas in immunology and clinical applications. They are commercially available in many different compositions and variants. However, unlike other reagents that consist of only one or a few compounds, peptide pools are highly complex products which makes their quality control a major challenge. Quantitative peptide analysis usually requires sophisticated methods, in most cases isotope-labeled standards and reference materials. Usually, this would be prohibitively laborious and expensive. Therefore, an approach is needed to provide a practical and feasible method for quality control of peptide pools. With insufficient quality control, the use of such products could lead to incorrect experimental results, worsening the well-known reproducibility crisis in the biomedical sciences. Here we propose the use of ultra-high performance liquid chromatography (UHPLC) with two detectors, a standard UV detector at 214 nm for quantitative analysis and a high-resolution mass spectrometer (HRMS) for identity confirmation. To be cost-efficient and fast, quantification and identification are performed in one chromatographic run. An optimized protocol is shown, and different peak integration methods are compared and discussed. This work was performed using a peptide pool known as CEF advanced, which consists of 32 peptides derived from cytomegalovirus (CMV), Epstein–Barr virus (EBV) and influenza virus, ranging from 8 to 12 amino acids in length.
The non-steroidal anti-inflammatory drug (NSAID) diclofenac (DCF) is an important environmental contaminant occurring in surface waters all over the world, because, after excretion, it is not adequately removed from wastewater in sewage treatment plants. To be able to monitor this pollutant, highly efficient analytical methods are needed, including immunoassays. In a medical research project, monoclonal antibodies against diclofenac and its metabolites had been produced. Based on this monoclonal anti-DCF antibody, a new indirect competitive enzyme-linked immunosorbent assay (ELISA) was developed and applied for environmental samples. The introduction of a spacer between diclofenac and the carrier protein in the coating conjugate led to higher sensitivity. With a test midpoint of 3 mg L−1 and a measurement range of 1–30 mg L−1, the system is not sensitive enough for direct analysis of surface water. However, this assay is quite robust against matrix influences and can be used for wastewater. Without adjustment of the calibration, organic solvents up to 5%, natural organic matter (NOM) up to 10 mg L−1, humic acids up to 2.5 mg L−1, and salt concentrations up to 6 g L−1 NaCl and 75 mg L−1 CaCl2 are tolerated. The antibody is also stable in a pH range from 3 to 12. Cross-reactivity (CR) of 1% or less was determined for the metabolites 40-hydroxydiclofenac (40-OH-DCF), 5-hydroxydiclofenac (5-OH-DCF), DCF lactam, and other NSAIDs. Relevant cross-reactivity occurred only with an amide derivative of DCF, 6-aminohexanoic acid (DCF-Ahx), aceclofenac (ACF) and DCF methyl ester (DCF-Me) with 150%, 61% and 44%, respectively. These substances, however, have not been found in samples. Only DCF-acyl glucuronide with a cross-reactivity of 57% is of some relevance. For the first time, photodegradation products were tested for cross-reactivity. With the ELISA based on this antibody, water samples were analysed. In sewage treatment plant effluents, concentrations in the range of 1.9–5.2 mg L−1 were determined directly, with recoveries compared to HPLC-MS/MS averaging 136%.
Concentrations in lakes ranged from 3 to 4.4 ng L−1 and were, after pre-concentration, determined with an average recovery of 100%
Machine learning-assisted equivalent circuit identification for dielectric spectroscopy of polymers
(2024)
Polymers have become indispensable across fields of application, and understanding their structure–property relationships and dynamic behaviour is essential for performance optimization. Polymer membranes, particularly ion exchange membranes, play a crucial role in renewable energy conversion technologies, fuel cells, solar energy conversion, and energy storage. In this context, broadband dielectric spectroscopy (BDS) offers a powerful, non-destructive approach to investigate the electrical response and relaxation dynamics of polymers. These properties are investigated by parametrizing the system’s impedance response in terms of a network of circuit elements, i.e. the electrical equivalent circuit (EEC), whose impedance resembles the one of the system under investigation. However, the determination of the EEC from BDS data is challenging due to system complexity, interdependencies of circuit elements, and researcher biases. In this work, we propose a novel approach that incorporates a convolutional neural network (CNN) model to predict the EEC topology. By reducing user bias and enhancing data analysis, this approach aims to make BDS accessible to both experienced users and those with limited expertise. We show that the combination of machine learning and BDS provides valuable insights into the dynamic behaviour of polymer membranes, thus facilitating the design and characterization of tailored polymers for various applications. We also show that our model outperforms state-of-the-art machine learning methods with a top-5 accuracy of around 80% for predicting the circuit topology and a parameter fitting error as low as 0.05%.
Barriers to transitioning to a circular bio-based economy: Findings from an industrial perspective
(2024)
The transition from a linear fossil-based to a circular bio-based economy represents an opportunity and a suitable pathway for achieving several sustainable development goals. However, the transition is a complex process since it requires transformative policies, purposeful innovation, access to finance, risk-taking capacity as well as new and sustainable business models and markets. Accordingly, the first step in this transition process is the identification of barriers that are hampering the transition to a sustainable circular bio-based economy. With this motivation in mind, this study reviews grey literature to identify barriers focusing on four critical sectors facing major challenges within the current linear economy and requiring a sustainable transition most urgently: construction, chemicals, plastics, and textile sectors. Employing an adapted STEEP methodology (Social, Technological, Economical, Environmental, Political), a total of 193 different barriers have been identified and clustered under six categories: cultural, technical, economic, environmental, governance, and structural. Regardless of the sector, cultural and structural barriers are identified as the most prominent; the lack of incentives for consumer behaviour change and lack of stakeholder collaboration were the most cited barriers among the literature records. From a value chain perspective, most of the barriers are related to the material processing and product manufacturing stage. Finally, potential solutions, extracted from the grey literature, are proposed to fill the gaps and overcome the identified barriers. Many of the identified barriers are common across the four investigated sectors, indicating the solutions or measures can be applicable in a wider perspective to promote the transition in the right direction.
Various software products for the simulation of industrial X-ray radiography have been developed in recent years (e.g., aRTist 2, CIVA CT, Scorpius XLab, SimCT, Wilcore) and their application potential has been shown in numerous works. However, full systematic approaches to characterise a specific CT system for these simulation software products to obtain a truthful digital twin are still missing. In this contribution, we want to present two approaches to obtain realistic grey values in X-ray projections in aRTist 2 simulations based on measured projections. In aRTist 2, the displayed grey value of a pixel is based on the energy density incident on that pixel.
The energy density is calculated based on the X-ray tube spectrum, the attenuation between source and detector as well as an energy-dependent sensitivity curve of the detector. The first approach presented in this contribution uses the sensitivity curve as a free modelling parameter. We measured the signal response at different thicknesses of Al EN-AW6082 at different tube voltages (i.e., different tube spectra). We then regarded the grey values displayed by these projections as a data regression respectively an optimisation problem and obtained the sensitivity curve that is best able to reproduce the measured behaviour in aRTist 2. The resulting sensitivity curve does not necessarily hold physical meaning but is able to simulate the real system behaviour in the simulation software.
The second approach presented in this contribution is to estimate the sensitivity curve based on assumptions about the characteristics of the scintillation detector (e.g., scintillator material, scintillator thickness and signal processing characteristics). For this approach, a linear response function (linear relationship between the deposited energy per pixel and the resulting grey value) is assumed. If the detector characteristics, which affect the simulated deposited energy, are properly modelled, the slope and offset of the response function to match the measured grey values should be the same for different tube spectra. As the offset is constant and given by the grey values measured at no incident radiation, the slope is the remaining parameter to evaluate the success of the detector modelling. We therefore adapted the detector characteristics by changing the detector setup until the slope was nearly the same for all measured tube spectra. We are aware that the resulting parameters of the scintillator material and thickness might not be the real ones, but with those modelling parameters we are able to simulate realistic grey values in aRTist 2. Both of those approaches could potentially be a step forward to a full systematic approach for a digital twin of a real CT system in aRTist 2.
Recent publications indicate that the order of electrochemical anodization (before or after the laser processing step) plays an important role for the response of bone-forming osteoblasts—an effect that can be utilized for improving permanent dental or removable bone implants. For exploring these different surface functionalities, multimethod morphological, structural, and chemical characterizations are performed in combination with electrochemical pre- and postanodization for two different characteristic microspikes covered by nanometric laser-induced periodic surface structures on Ti–6Al–4V upon irradiation with near-infrared ps-laser pulses (1030 nm wavelength, ≈1 ps pulse duration, 67 and 80 kHz pulse repetition frequency) at two distinct sets of laser fluence and beam scanning parameters. This work involves morphological and topographical investigations by scanning electron microscopy and white light interference microscopy, structural material examinations via X-ray diffraction, and micro-Raman spectroscopy, as well as near-surface chemical analyses by X-ray photoelectron spectroscopy and hard X-ray photoelectron spectroscopy. The results allow to qualify the mean laser ablation depth, assess the spike geometry and surface roughness parameters, and provide new detailed insights into the near-surface oxidation that may affect the different cell growth behavior for pre- or postanodized medical implants.
Sacrifice Few to Save Many: Fire Protective Interlayers in Carbon- Fiber-Reinforced Laminates
(2024)
The fire protection of carbon-fiber-reinforced polymer (CFRP) laminates often relies on flame-retardant coatings, but in some applications, their efficacy may diminish upon direct fire exposure due to rapid pyrolysis. This study introduces an innovative approach by integrating protective interlayers within the laminate structure to enhance the fire resistance. Various materials, including ceramic composite WHIPOX, titanium foil, poly(etherimide) (PEI) foil, basalt fibers, rubber mat, and hemp fibers, were selected as protective interlayers. These interlayers were strategically placed within the laminate layout to form a sacrificial barrier, safeguarding the integrity of the composite. Bench-scale fire resistance tests were conducted, where fire (180 kW/m2) was applied directly to the one side of the specimen by a burner while a compressive load was applied at the same time. Results indicate significant prolongation of time to failure for CFRP laminates with protective interlayers, which is up to 10 times longer. This innovative approach represents a potential advance in fire protection strategies for CFRP laminates, offering improved resilience against fire-induced structural failure.
A systematic series of industrial-relevant polystyrene-based anion exchange resins that are functionalized with hydro- or fluorocarbon chains are compared regarding their adsorption behavior toward perfluorocarboxylic acids (PFCA) in respect to their charge, chain length, and type of chain. The results clearly show the dominance of electrostatic interactions in the adsorption process as uncharged adsorber materials showed no adsorption at all. In contrast, the charged adsorber materials showed in general a PFCA removal of 80% to 30% over the experiment depending on effluent fraction.
Unexpectedly, for perfluorobutanoic acid (PFBA) the highest removal rate is found with consistently >90%. Despite observing significant benefits in the adsorption of PFCA for fluoroalkylated adsorbers in comparison to their non-fluorinated counterparts, this effect of fluoroalkylation is comparatively small and can not be clearly attributed to fluorophilic interactions between the fluoroalkyl chains. These findings help clarifying that the introduction of fluorocarbon moieties in adsorber materials is not necessary in order to remove fluorocarbon molecules from the environment.
Relation of craze to crack length during slow crack growth phenomena in high‐density polyethylene
(2024)
The craze‐crack mechanism occurring in high‐density polyethylene (HDPE) causing slow crack growth and environmental stress cracking is investigated in detail with respect to the relation of crack length and the related craze zone. This is essential for the understanding of the resulting features of the formed fracture surface and their interpretation in the context of the transition from crack propagation to ductile shear deformation. It turns out that an already formed craze zone does not inevitably result in formation of a propagating crack, but could also undergo ductile failure. For the examination, the full notch creep test (FNCT) was employed with a subsequent advanced fracture surface analysis that was performed using various imaging techniques: light microscopy, laser scanning microscopy, scanning electron microscopy, and X‐ray micro computed tomography scan. FNCT specimens were progressively damaged for increasing durations under standard test conditions applying Arkopal, the standard surfactant solution, and biodiesel as test media were used to analyze the stepwise growth of cracks and crazes. From considerations based on well‐established fracture mechanics approaches, a theoretical correlation between the length of the actual crack and the length of the preceding craze zone was established that could be evidenced and affirmed by FNCT fracture surface analysis. Moreover, the yield strength of a HDPE material exposed to a certain medium as detected by a classic tensile test was found to be the crucial value of true stress to induce the transition from crack propagation due to the craze‐crack mechanism to shear deformation during FNCT measurements.
Highlights
- Progress of crack formation in high‐density polyethylene is analyzed by different imaging techniques
- Determined growth rates depend on distinction between craze zone and crack
- The ratio of the present crack to the anteceding craze zone is validated theoretically
- The transition from crack propagation to ductile shear deformation is identified
- An already formed craze zone may still fail by ductile mechanisms
Changes in Black Truffle (Tuber melanosporum) Aroma during Storage under Different Conditions
(2024)
The enticing aroma of truffles is a key factor for their culinary value. Although all truffle species tend to be pricy, the most intensely aromatic species are the most sought after. Research into the aroma of truffles encompasses various disciplines including chemistry, biology, and sensory science. This study focusses on the chemical composition of the aroma of black truffles (Tuber melanosporum) and the changes occurring under different storage conditions. For this, truffle samples were stored under different treatments, at different temperatures, and measured over a total storage time of 12 days. Measurements of the truffle aroma profiles were taken with SPME/GC–MS at regular intervals. To handle the ample data collected, a systematic approach utilizing multivariate data analysis techniques was taken. This approach led to a vast amount of data which we made publicly available for future exploration. Results reveal the complexity of aroma changes, with 695 compounds identified, highlighting the need for a comprehensive understanding. Principal component analyses offer initial insights into truffle composition, while individual compounds may serve as markers for age (formic acid, 1-methylpropyl ester), freshness (2-Methyl-1-propanal; 1-(methylthio)-propane), freezing (tetrahydrofuran), salt treatment (1-chloropentane), or heat exposure (4-hydroxy-3-methyl-2-butanone). This research suggests that heat treatment or salt contact significantly affects truffle aroma, while freezing and cutting have less pronounced effects in comparison. The enrichment of compounds showing significant changes during storage was investigated with a metabolomic pathway analysis. The involvement of some of the enriched compounds on the pyruvate/glycolysis and sulfur pathways was shown.
The present work addresses powder bed binder jetting additive manufacturing by selective magnesium phosphate cement activation. Despite the potential of this technology to aid the digitalization of the construction industry, the effect of processing parameters on the mechanical performance of printed materials has not yet been studied to generate a guideline for the further development of the technology. Statistical methodologies were used to screen the effect of four printing process parameters (printing speed, layer thickness, raster angle, and build direction on flexural and compressive strength). As the exploited technology works with constant fluid pressure, the physical interpretation of the effect of each factor can be considered taking into account the interactions between the binder materials in the powder bed. Analysis of variance (ANOVA) indicated that printing speed and layer thickness significantly affect mechanical performances. Furthermore, the layout of samples for the printing process is preferable to be parallel the printhead movement. An anisotropic behavior was observed, and the samples subjected to compressive forces parallel to the layer plane possessed lower strength values. This effect can be interpreted as a result of a weak area of low density in between layers, leading to a pronounced delamination under compression. Even though the strength of the printed material is not suitable for a structural concrete, it can be marginally improved by design of experiment and optimized for non-structural applications, such as for porous artificial stone. Design of experiment coupled with ANOVA methods can be used in the future to support the development of novel material mixtures, thus expanding the fields of application of this novel additive manufacturing technology.
A widespread recovery of waste heat requires a cost‐effective production of thermoelectric generators. Thermoelectric oxides are predestined for use at high temperatures. For manufacturing reasons, a multilayer generator design will be easily scalable and cost‐effective. To evaluate the potential of ceramic multilayer technology for that purpose, a multilayer of the promising thermoelectric oxides calcium cobaltite (Ca3Co4O9), calcium manganate (CMO, CaMnO3), and glass–ceramic insulation layers is fabricated. Cracks and reaction layers at the interfaces are observed in the microstructure. The compositions of these reaction layers are identified by energy‐dispersive X‐ray spectroscopy and X‐ray diffraction. Mechanical and thermal properties of all layers are compiled from literature or determined by purposeful sample preparation and testing. Based on this data set, the internal stresses in the multilayer after co‐firing are calculated numerically. It is shown that tensile stresses in the range of 50 MPa occur in the CMO layers. The reaction layers have only a minor influence on the level of these residual stresses. Herein, it is proven that the material system is basically suitable for multilayer generator production, but that the co‐firing process and the layer structure must be adapted to improve densification and reduce the tensile stresses in the CMO.
Confocal micro-X-ray fluorescence (micro-XRF) spectroscopy facilitates three-dimensional (3D) elemental imaging of heterogeneous samples in the micrometer range. Laboratory setups using X-ray tube excitation render the method accessible for diverse research fields but interpretation of results and quantification remain challenging. The attenuation of X-rays in composites depends on the photon energy as well as on the composition and density of the material. For confocal micro-XRF, attenuation severely impacts elemental distribution information, as the signal from deeper layers is distorted by superficial layers. Absorption correction and quantification of fluorescence measurements in heterogeneous composite samples have so far not been reported. Here, an absorption correction approach for confocal micro-XRF combining density information from microcomputed tomography (micro-CT) data with laboratory X-ray absorption spectroscopy (XAS) and synchrotron transmission measurements is presented. The energy dependency of the probing volume is considered during the correction. The methodology is demonstrated on a model composite sample consisting of a bovine tooth with a clinically used restoration material.