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Paper des Monats
- ja (72)
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Impact of organic phosphates on the structure and composition of short-range ordered iron nanophases
(2024)
Organic phosphates (OP) are important nutrient components for living cells in natural environments, where they readily interact with ubiquitous iron phases such as hydrous ferric oxide, ferrihydrite (FHY). FHY partakes in many key bio(geo)chemical reactions including iron-mediated carbon storage in soils, or iron-storage in living organisms. However, it is still unknown how OP affects the formation, structure and properties of FHY. Here, we document how β-glycerophosphate (GP), a model OP ligand, affects the structure and properties of GP–FHY nanoparticles synthesized by coprecipitation at variable nominal molar P/Fe ratios (0.01 to 0.5). All GP–FHY precipitates were characterized by a maximum solid P/Fe ratio of 0.22, irrespective of the nominal P/Fe ratio. With increasing nominal P/Fe ratio, the specific surface area of the GP–FHY precipitates decreased sharply from 290 to 3 m2 g−1, accompanied by the collapse of their pore structure. The Fe–P local bonding environment gradually transitioned from a bidentate binuclear geometry at low P/Fe ratios to monodentate mononuclear geometry at high P/Fe ratios. This transition was accompanied by a decrease in coordination number of edge-sharing Fe polyhedra, and the loss of the corner-sharing Fe polyhedra. We show that Fe(III) polymerization is impeded by GP, and that the GP–FHY structure is highly dependent on the P/Fe ratio. We discuss the role that natural OP-bearing Fe(III) nanophases have in biogeochemical reactions between Fe–P and C species in aquatic systems.
The processes of hydrogen reduction of silicon and germanium chlorides under the conditions of high-frequency (40.68 MHz) counteracted arc discharge stabilized between two rod electrodes are investigated. The main gas-phase and solid products of plasma-chemical transformations are determined. Thermodynamic analysis of SiCl4 + H2 and GeCl4 + H2 systems for optimal process parameters was carried out. Using the example of hydrogen reduction of SiCl4 by the method of numerical modeling, gas-dynamic and thermal processes for this type of discharge are investigated. The impurity composition of gas-phase and solid reaction products is investigated. The possibility of single-stage production of high-purity Si and Ge mainly in the form of compact ingots, as well as high-purity chlorosilanes and trichlorogermane, is shown.
In situ chemical analysis of duplex stainless steel weld by laser induced breakdown spectroscopy
(2024)
The high corrosion resistance and good mechanical properties of duplex stainless steel (DSS) are due to its special chemical composition, which is a balanced phase ratio of ferrite (α) and austenite (γ). Many industrial applications require the integration of DSS components. For this, Gas tungsten arc welding (GTAW) is an excellent choice, as it allows an automated operation with high reproducibility. However, when the weld pool solidifies, critical ratios of α- and γ- phases can occur, which lead to solidification cracking, increased susceptibility to corrosion, and a decrease in ductility and critical strength. Previous studies have shown that these defects can be caused by the accumulation of manganese and chromium in the heat affected zone (HAZ), requiring ongoing monitoring of this accumulation. A suitable method for such monitoring is laser-induced breakdown spectroscopy (LIBS), which can be used in two operating modes: calibration using standard reference samples and calibration-free. Unlike conventional quantitative LIBS measurements, which require reference samples to generate a calibration curve, calibration-free LIBS (CF-LIBS) allows chemical compositions to be determined solely from the emission spectrum of the plasma. Numerous publications show that CF-LIBS is a fast and efficient analytical method for the quantitative analysis of metal samples. In this work, CF-LIBS is applied to spectra obtained during GTAW DSS welding and the result is compared with those obtained by PLS analysis. A good correlation was found between both types of analysis, demonstrating the suitability of the CF-LIBS method for this application. The CF-LIBS method has a significant advantage over conventional LIBS due to the rapid in situ measurement of concentrations of major alloying elements without calibration procedure. This, combined with fast feedback and appropriate adjustment of welding parameters, helps prevent welding defects.
Acceleration sensors are vital for assessing engineering structures by measuring properties like natural frequencies. In practice, engineering structures often have low natural frequencies and face harsh environmental conditions. Understanding sensor behavior on such structures is crucial for reliable masurements. The research focus is on understanding the behavior of acceleration sensors in harsh environmental conditions within the low-frequency acceleration range. The main question is how to distinguish sensor behavior from structural influences to minimize errors in assessing engineering structure conditions. To investigate this, the sensors are tested using a long-stroke calibration unit under varying temperature and humidity conditions. Additionally, a mini-monitoring system configured with four IEPE sensors is applied to a small-scale support structure within a climate chamber. For the evaluation, a signal-energy approach is employed to distinguish sensor behavior from structural behavior. The findings show that IEPE sensors display temperature-dependent nonlinear transmission behavior within the low-frequency acceleration range, with humidity having negligible impact. To ensure accurate engineering structure assessment, it is crucial to separate sensor behavior from structural influences using signal energy in the time domain. This study underscores the need to compensate for systematic effects, preventing the underestimation of vibration energy at low temperatures and overestimation at higher temperatures when using IEPE sensors for engineering structure monitoring.
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.
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.
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.
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.
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.
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.
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.
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.
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%.
This technical note highlights the fact that CF-LIBS algorithms work in mole fractions, while results of spectrochemical analysis are usually reported in mass fractions or mass percent. Ignoring this difference and not converting mole fractions to mass fractions can lead to errors in reported concentrations determined by the CF-LIBS method and inadequate comparison of these concentrations with certified concentrations. Here, the key points of the CF-LIBS algorithm are reproduced and the formulae for converting a mole fraction to a mass fraction and vice versa are given. Several numerical examples are also given, which show that the greater the difference between the molar mass of an individual element in a sample and the average molar mass, the greater the discrepancy between the mole and mass fractions.
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.
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.
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.
The emission of ultrafine particles from small desktop Fused Filament Fabrication (FFF) 3D printers has been frequently investigated in the past years. However, the vast majority of FFF emission and exposure studies have not considered the possible occurrence of particles below the typical detection limit of Condensation Particle Counters and could have systematically underestimated the total particle emission as well as the related exposure risks. Therefore, we comparatively measured particle number concentrations and size distributions of sub-4 nm particles with two commercially available diethylene glycol-based instruments – the TSI 3757 Nano Enhancer and the Airmodus A10 Particle Size Magnifier. Both instruments were evaluated for their suitability of measuring FFF-3D printing emissions in the sub-4 nm size range while operated as a particle counter or as a particle size spectrometer. For particle counting, both instruments match best when the Airmodus system was adjusted to a cut-off of 1.5 nm. For size spectroscopy, both instruments show limitations due to either the fast dynamics or rather low levels of particle emissions from FFF-3D printing in this range. The effects are discussed in detail in this article. The findings could be used to implement sub-4 nm particle measurement in future emission or exposure studies, but also for the development of standard test protocols for FFF-3D printing emissions.
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%
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.
The number of vehicles using or transporting cryogenic fuels such as Liquefied Hydrogen (LH2) or Liquefied Natural Gas (LNG) increases fast in the land transportation sector. Does this also entail new risks? The storage of cryogenic fuels requires tanks with Thermal Super Insulations (TSI) to keep the fluid cold and limit the formation of boil-off gas. TSI has proven itself in some applications since the middle of the 20th century, but in the land transport sector they are still quite new, where accidents involving fires, collisions, and their combination are to be expected. This work focuses on investigating the behavior of different types of TSI while exposed to a heat source representing a fire. To this aim, a High-Temperature Thermal Vacuum Chamber (HTTVC) was applied, which allows the thermal loading of a thermal insulation material in a vacuum and measuring the heat flow transported through the TSI in parallel. In this study, the results of 6 samples are presented regarding 3 types of MLI, rock wool, perlites, and microspheres. The thermal exposure caused different effects on the samples. In practice, this can be connected to the rapid release of flammable gases as well as to a Boiling Liquid Expanding Vapour Explosion (BLEVE). These results are relevant for reducing the risks to people and infrastructures in the progressive establishment of tanks for cryogenic fluids in our industry and society. The data presented in the study can be used to improve the design of tanks and TSIs, the assessment of accident scenarios, and the development of measures for first responders.
Discotic ionic liquid crystals (DILCs) consist of self-assembled superdiscs of cations and anions that spontaneously stack in linear columns with high one-dimensional ionic and electronic charge mobility, making them prominent model systems for functional soft matter. Compared to classical nonionic discotic liquid crystals, many liquid crystalline structures with a combination of electronic and ionic conductivity have been reported, which are of interest for separation membranes, artificial ion/proton conducting membranes, and optoelectronics. Unfortunately, a homogeneous alignment of the DILCs on the macroscale is often not achievable, which significantly limits the applicability of DILCs. Infiltration into nanoporous solid scaffolds can, in principle, overcome this drawback. However, due to the experimental challenges to scrutinize liquid crystalline order in extreme spatial confinement, little is known about the structures of DILCs in nanopores. Here, we present temperaturedependent high-resolution optical birefringence measurement and 3D reciprocal space mapping based on synchrotron X-ray scattering to investigate the thermotropic phase behavior of dopamine-based ionic liquid crystals confined in cylindrical channels of 180 nm diameter in macroscopic anodic aluminum oxide membranes. As a function of the membranes’ hydrophilicity and thus the molecular anchoring to the pore walls (edge-on or face-on) and the variation of the hydrophilic−hydrophobic balance between the aromatic cores and the alkyl side chain motifs of the superdiscs by tailored chemical synthesis, we find a particularly rich phase behavior, which is not present in the bulk state. It is governed by a complex interplay of liquid crystalline elastic energies (bending and splay deformations), polar interactions, and pure geometric confinement and includes textural transitions between radial and axial alignment of the columns with respect to the long nanochannel axis. Furthermore, confinement-induced continuous order formation is observed in contrast to discontinuous first-order phase transitions, which can be quantitatively described by Landau-de Gennes free energy models for liquid crystalline order transitions in confinement. Our observations suggest that the infiltration of DILCs into nanoporous solids allows tailoring their nanoscale texture and ion channel formation and thus their electrical and optical functionalities over an even wider range than in the bulk state in a homogeneous manner on the centimeter scale as controlled by the monolithic nanoporous scaffolds.
Concretes produced from salt aggregate and hybrid alkaline cements, an alkali-activated slag/fly ash blend, or a Portland cement were exposed to a magnesium chloride-rich saline solution ([Mg2+] = 3.6 m, [Cl−] = 8.3 m), representing a solution formed after contact of surface water with evaporite rock (rock salt) in a nuclear waste repository. The hydration and deterioration of the concretes were studied with X-ray diffraction, thermogravimetric analysis, pH mapping and permeability measurements. The results show that calcium silicate hydrate (C-S-H) or sodium-substituted calcium aluminium silicate hydrate (C-N-A-S-H) and Friedel's salt were the major reaction products in the concretes prior to exposure to the saline solution. During exposure to the saline solution, increasing amounts of C-S-H/C-N-A-S-H dissolved, and gypsum and a secondary AFm phase formed. The durability of the concretes improved with increasing amounts of Portland clinker in the cements, due to the associated differences in permeability and chemical resistance. Nevertheless, a massive increase of permeability occurred for all concretes, likely caused by crack formation due to the formation of gypsum from anhydrite in the salt aggregate. Thus, the behavior of the concretes differed from, and was more complex than, the behavior of plain cement pastes.
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.
Exploring the electrochemical and physical stability of lithium-ion cells exposed to liquid nitrogen
(2024)
The transport and storage of lithium-ion (Li-ion) batteries — damaged or in an undefined state — is a major safety concern for regulatory institutions, transportation companies, and manufacturers. Since (electro)chemical reactivity is exponentially temperature-dependent, cooling such batteries is an obvious measure for increasing their safety.
The present study explores the effect of cryogenic freezing on the electrochemical and physical stability of Li-ion cells. For this purpose, three different types of cells were repeatedly exposed to liquid nitrogen (LN2).
Before and after each cooling cycle, electrical and electrochemical measurements were conducted to assess the impact of the individual freezing steps. While the electrochemical behavior of the cells did not change significantly upon exposure to LN2 , it became apparent that a non-negligible number of cells suffered from physical changes (swelling) and functional failures. The latter defect was found to be caused by the current interrupt device of the cylindrical cells. This safety mechanism is triggered by the overpressure of expanding nitrogen which enters the cells at cryogenic temperatures.
This study underlines that the widely accepted reversibility of LN2 -cooling on a material scale does not allow for a direct extrapolation toward the physical integrity of full cells. Since nitrogen enters the cell at cryogenic temperatures and expands upon rethermalization, it can cause an internal overpressure. This can, in turn, lead to mechanical damage to the cell. Consequently, a more appropriate temperature condition — less extreme than direct LN2 exposure — needs to be found
Although the use of noble metal catalysts can increase the efficiency of hydrogen evolution reaction, the process is still limited by the characteristics of the metal-hydrogen (M−H) bond, which can be too strong or too weak, depending on the metal employed. Studies revealed that the hydrogen affinity for the metal surface (i.e. H absorption/desorption) is regulated also by the potential at the metal nanoparticles. Through controlled periodic illumination (CPI) of a series of metal/TiO2 suspensions, here we demonstrated that an increase of the HER efficiency is possible for those photodeposited metals which have a Tafel slope below 125 mV. Two possible explanations are here reported, in both of them the M−H interaction and the metal covering level play a prominent role, which also depend on the prevailing HER mechanism (Volmer-Heyrovsky or Volmer-Tafel).
A giant Zn segregation transition is revealed using CALPHAD-integrated density-based modeling of segregation into Fe grain boundaries (GBs). The results show that above a threshold of only a few atomic percent Zn in the alloy, a substantial amount of up to 60 at.% Zn can segregate to the GB. We found that the amount of segregation abruptly increases with decreasing temperature, while the Zn content in the alloy required for triggering the segregation transition decreases. Direct evidence of the Zn segregation transition is obtained using high-resolution scanning transmission electron microscopy. Base on the model, we trace the origin of the segregation transition back to the low cohesive energy of Zn and a miscibility gap in Fe-Zn GB, arising from the magnetic ordering effect, which is confirmed by ab-initio calculations. We also show that the massive Zn segregation resulting from the segregation transition greatly assists with liquid wetting and reduces the work of separation along the GB. The current predictions suggest that control over Zn segregation, by both alloy design and optimizing the galvanization and welding processes, may offer preventive strategies against liquid metal embrittlement.
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.
The effect of resting time on the rheological properties of cement suspensions is generally explained by early formed structure and overconsumption of polycarboxylate superplasticizers (PCEs). In this paper, we propose that the influence of resting time on the rheological properties is closely related to size variation of non-absorbed PCE. To identify this, glass bead suspensions were prepared with various amounts of PCE and ionic solution, and their rheological properties were evaluated at various times. We found that the yield stress increases with time at higher PCE concentrations and higher ionic strength solutions. Adsorbed PCE during resting tends to bridge the particles rather than disperse them. In addition, it was found that hydrodynamic radius of PCE increased with resting time, and depletion forces resulting from non-absorbed PCE size changes correlate well with the increased yield stress.
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
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.
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.
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.
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.
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.
Die Integration von Automation und Robotik in die Prüfprozesse ermöglicht die
Untersuchung komplexer Bauteile. Diese Studie präsentiert die robotergestützte
Laserthermografie, um Risse in solchen Bauteilen zu identifizieren und analysieren. Diese Technik ermöglicht die automatisierte Rissprüfung welche im Vergleich zur Farbeindringprüfung auf viele, meist manuelle, Arbeitsschritte sowie die notwendigen Chemikalien verzichtet.
Zusätzlich wird ein automatisiertes Einscannen der Bauteile mithilfe eines
Linienscanners vorgestellt. Dieser Schritt ermöglicht eine detaillierte 3D-Rekonstruktion der Bauteilgeometrie und ermöglicht eine einfache Korrektur von Abweichungen in der Bauteilaufnahme und eröffnet Möglichkeiten zur adaptiven Bahnplanung bei Bauteilverformungen.
Die Rückprojektion der gefundenen Risse auf die Oberfläche des Bauteils kann
automatisiert erfolgen. Dieser Schritt erlaubt nicht nur die Identifikation der Risse, sondern auch eine genauere Analyse ihrer Geometrie und Lage am Bauteil.
Die Kombination von robotergestützter Laserthermografie, automatisiertem 3DScanning und Rückprojektion der Risse auf die Bauteiloberfläche eröffnet neue
Möglichkeiten in der zerstörungsfreien Prüfung von komplexen Bauteilen und erweitert damit mögliche Anwendungsfelder.
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).
Despite the advances in hardware and software techniques, standard numerical methods fail in providing real-time simulations, especially for complex processes such as additive manufacturing applications. A real-time simulation enables process control through the combination of process monitoring and automated feedback, which increases the flexibility and quality of a process. Typically, before producing a whole additive manufacturing structure, a simplified experiment in the form of a beadon-plate experiment is performed to get a first insight into the process and to set parameters suitably. In this work, a reduced order model for the transient thermal problem of the bead-on-plate weld simulation is developed, allowing an efficient model calibration and control of the process. The proposed approach applies the proper generalized decomposition (PGD) method, a popular model order reduction technique, to decrease the computational effort of each model evaluation required multiple times in parameter estimation, control, and optimization. The welding torch is modeled by a moving heat source, which leads to difficulties separating space and time, a key ingredient in PGD simulations. A novel approach for separating space and time is applied and extended to 3D problems allowing the derivation of an efficient separated representation of the temperature.
The results are verified against a standard finite element model showing excellent agreement. The reduced order model is also leveraged in a Bayesian model parameter estimation setup, speeding up calibrations and ultimately leading to an optimized real-time simulation approach for welding experiment using synthetic as well as real measurement data.
Thermal transient problems, essential for modeling applications like welding and additive metal manufacturing, are characterized by a dynamic evolution of temperature. Accurately simulating these phenomena is often computationally expensive, thus limiting their applications, for example for model parameter estimation or online process control. Model order reduction, a solution to preserve the accuracy while reducing the computation time, is explored. This article addresses challenges in developing reduced order models using the proper generalized decomposition (PGD) for transient thermal problems with a specific treatment of the moving heat source within the reduced model. Factors affecting accuracy, convergence, and computational cost, such as discretization methods (finite element and finite difference), a dimensionless formulation, the size of the heat source, and the inclusion of material parameters as additional PGD variables are examined across progressively complex examples. The results demonstrate the influence of these factors on the PGD model’s performance and emphasize the importance of their consideration when implementing such models. For thermal example, it is demonstrated that a PGD model with a finite difference discretization in time, a dimensionless representation, a mapping for a moving heat source, and a spatial domain non-separation yields the best approximation to the full order model.