Filtern
Erscheinungsjahr
- 2023 (510) (entfernen)
Dokumenttyp
- Zeitschriftenartikel (510) (entfernen)
Sprache
- Englisch (472)
- Deutsch (32)
- Mehrsprachig (4)
- Französisch (1)
- Russisch (1)
Schlagworte
- Additive manufacturing (17)
- SAXS (11)
- Microstructure (9)
- Corrosion (8)
- Fluorescence (8)
- X-ray scattering (8)
- Concrete (7)
- LIBS (7)
- Laser beam welding (7)
- MOUSE (7)
Organisationseinheit der BAM
- 6 Materialchemie (118)
- 8 Zerstörungsfreie Prüfung (93)
- 1 Analytische Chemie; Referenzmaterialien (86)
- 7 Bauwerkssicherheit (75)
- 5 Werkstofftechnik (62)
- 9 Komponentensicherheit (55)
- 6.3 Strukturanalytik (46)
- 4 Material und Umwelt (40)
- 8.5 Röntgenbildgebung (33)
- 5.1 Mikrostruktur Design und Degradation (24)
Paper des Monats
- ja (50)
Per- and polyfluoroalkyl substances (PFAS) are widely used for durable water-repellent finishing of different fabrics and textiles like outdoor clothing, carpets, medical textiles and more. Existing PFAS extraction techniques followed by target analysis are often insufficient in detecting widely used side-chain fluorinated polymers (SFPs) that are barely or non-extractable. SFPs are typically copolymers consisting of a non-fluorinated backbone with perfluoroalkyl side-chains to obtain desired properties. We compared the accessible analytical information and performance of complementary techniques based on oxidation (dTOP assay, PhotoTOP), hydrolysis (THP assay), standard extraction, extractable organic fluorine (EOF), and total fluorine (TF) with five functional textiles and characterized 7 further textiles only by PhotoTOP oxidation. The results show that when applied directly to textile samples, oxidation by dTOP and PhotoTOP and also hydrolysis by the THP are able to capture large fractions of the TF in form of perfluoroalkyl side-chains present in the textiles while methods relying on extracts (EOF, target and non-target analysis) were much lower (e.g., factor ~25-50 lower). The conversion of large fractions of the measured TF into PFCAs or FTOHs from fluorinated side chains is in contrast to previous studies. Concentrations ranged from <LOQ to over ~1000 mg F/kg after oxidation/hydrolysis and <LOQ to over 2000 mg F/kg for TF, while EOF and target PFAS in extracts were detected at much lower concentrations (up to ~ 60 mg F/kg) (amount of fluorine in the order: extraction << EOF << oxidation/hydrolysis ≤ TF). Perfluoroalkyl carboxylic acids (PFCAs) and fluorotelomer alcohols (FTOHs) from THP and PhotoTOP both represented the chain-length distribution in the textiles showing that long-chain SFPs are still used in current textiles. Further advantages and disadvantages of the applied methods are discussed.
Large temperature gradients inherent to additive manufacturing (AM) processes induce large residual stress (RS) in the final part. Because RS can influence the tribological properties, this study focuses on the relationship between wear sliding properties and RS in IN718 coatings. Such coatings were deposited with a Laser metal deposition (LMD) machine using two different scanning strategies.
The wear resistance and RS state were investigated after surface milling. RS were measured before and after wear tests on a reciprocating sliding test apparatus.
Two different X-ray diffraction techniques were employed to measure the surface and subsurface state RS: Laboratory Energy Dispersive X-ray Diffraction (LEDXD) and Synchrotron X-ray Energy Dispersive Diffraction (SXEDD). Due to the milling process, the coatings show similar depth distributions of RS from 22 to 92 μm depth, but exhibit different magnitudes depending on the scanning strategy used. Reciprocating sliding wear tests induced high compressive residual stresses that erased the initial RS state, and a similar wear behavior was observed in the two samples. These samples possess similar texture and grain morphology. This demonstrates that the influence of RS on wear resistance is a second-order effect. Nevertheless, it was observed that RS can still impact the wear performance at the early testing stages of the repaired parts.
The microstructure of an apatite-wollastonite (code name AP40) glass-ceramic is analyzed in this study by combining 2D microscopy, phase analysis, X-ray absorption and synchrotron X-ray refraction computed tomography (XCT and SXRCT, respectively). It is shown that this combination provides a useful toolbox to characterize the global microstructure in a wide scale range, from sub-micrometer to millimeter. The material displays a complex microstructure comprising a glassy matrix with embedded fluorapatite and wollastonite small crystals. In this matrix, large (up to 200 μm) spike-shaped structures are distributed. Such microstructural features are oriented around a central sphere, thereby forming a structure resembling a sea urchin. A unique feature of SXRCT, in contrast to XCT, is that internal interfaces are visualized; this allows one to show the 3D distribution of these urchins with exceptionally good contrast. Furthermore, it is revealed that the spike-shaped structures are not single crystals, but rather composed of sub-micrometric crystals, which are identified as fluorapatite and diopside phases by SEM-EDX analysis.
EURAMET.QM-K3.2019 was a repeat of the key comparison EURAMET.QM-K3 on the composition of automotive exhaust gases. New in EURAMET.QM-K3.2019 was the addition of the amount fraction oxygen to the programme. The key comparison reference values were obtained independently, using static gravimetry and appropriate corrections from purity analysis and are linked to those of CCQM-K3.2019. The key comparison results show equivalence between the measurement standards maintained by the participating national metrology institutes. The demonstrated equivalence can be used to underpin services related to automotive exhaust gases as well as generically through the flexible scheme ("track A").
Aero-engine turbine disks are safety-relevant components which are operated under high thermal and mechanical stress conditions. The actual part qualification and certification procedures make use of spin-tests conducted on production-similar disks. While these tests provide, on the one hand, a reliable definition of the critical conditions for real components, on the other hand they represent a relevant cost item for engine manufacturers. The aim of this work is to present two alternative burst speed assessment methods under development based on the Failure Assessment Diagram (FAD) and a global stability criterion, respectively. In the scope of the fracture mechanics assessment, the failure modes hoop-burst and rim-peeling are investigated with semicircular surface cracks modelled at the critical regions on the turbine disk. The comparison of the predicted critical rotational speed shows good agreement between the assessment methods.
An in-depth understanding of the degradation mechanisms is a prerequisite for developing the nextgeneration all solid-state lithium metal battery (ASSLMB) technology. Herein, synchrotron X-ray computed tomography (SXCT) together with other probing tools and simulation method were employed to rediscover the decaying mechanisms of LiNi0.8Co0.1Mn0.1O2 (NCM)|Li6PS5Cl (LPSCl)|Li ASSLMB. It reveals that the detachment and isolation of NCM particles cause the current focusing on the remaining active regions of cathode. The extent of Li stripping and the likelihood of Li+ plating into LPSCl facing the active NCM particles becomes higher. Besides, the homogeneity of Li stripping/plating is improved by homogenizing the electrochemical reactions at the cathode side by LiZr2(PO4)3 (LZP) coating. These results suggest a codependent failure mechanism between cathode and anode that is mediated by uneven Li ion flux. This work contributes to establish a holistic understanding of the degradation mechanisms in ASSLMBs and opens new opportunities for their further optimization and evelopment.
Friction stir welding (FSW) has the capacity to join the Al/Ti dissimilar structures with superior mechanical properties. The microstructures and mechanical characteristics of Al/Ti dissimilar FSW joints are determined by the heat and mass transfer during the welding process. However, a quantitative study of the Al/Ti dissimilar FSW process is lacking. Therefore, using the computational fluid dynamics (CFD) and volume of fluid (VOF) approach, a multi-phase model was constructed for quantitatively analyzing the heat and mass transfer behaviour in dissimilar FSW of TC4 titanium alloy and AA2024-T4 aluminium alloy. The mixed material was treated as a functionally graded material (FGM) to compute the thermophysical characteristics at the weld nugget zone (WNZ). Due to the vast disparity in the thermophysical characteristics of aluminum and titanium alloy, the temperature field in Al/Ti dissimilar FSW was severely asymmetric. The temperature of titanium alloy on the advancing side (AS) was higher than that of aluminium alloy on the retreating side (RS) at the same distance from the tool centre line near the tool shoulder, but it was lower than that of aluminium alloy on the RS without the influence of the shoulder. Due to the high flow stress of titanium alloy, plastic material flow mostly occurred on the RS of aluminium alloy in the Al/Ti dissimilar FSW, with its percentage exceeding 80%. This model was validated by experiment results.
Effect of Polycarboxylate Superplasticizer in Ordinary Portland Cement and Sulfate Resistant Cement
(2023)
Polycarboxylate superplasticizers (PCE) are the most widely used admixtures in today’s cementitious construction materials. The molecular structure has a decisive influence on the effectiveness of PCE, which also can be tailored to serve in a different cementitious system.
The current study investigates the influence of the backbone charge density of PCE on the rheology, hydration kinetics, and adsorption behavior of ordinary Portland cement (OPC) and sulfate-resistant cement (SRC). The results indicate that regardless of the PCE type, OPC requires a higher amount of PCE to be adsorbed to induce changing of rheological parameters and hydration kinetics. Regardless of the cement type, the PCE with a higher charge density exhibits higher adsorption behavior, corresponding to lower viscosity measurement.
Compared to OPC, SRC is more sensitive to the introduction of both PCEs and has a lower saturation dosage, indicating that SRC generally provides better workability properties regardless of the PCE.
An observation of the fracture process in front of the crack tip inside a dentin sample by means of ex-situ X-ray computed tomography after uniaxial compression at different deformation values was carried out in this work. This ex-situ approach allowed the microstructure and fracturing process of human dentin to be observed during loading. No cracks are observed up to the middle part of the irreversible deformation in the samples at least visible at 0.4μm resolution. First cracks appeared before the mechanical stress reached the compression strength. The growth of the cracks is realized by connecting the main cracks with satellite cracks that lie ahead of the main crack tip and parallel its trajectory. When under the stress load the deformation in the sample exceeds the deformation at the compression strength of dentin, an appearance of micro-cracks in front of the main cracks is observed. The micro-cracks are inclined (~60°) to the trajectory of the main cracks. The further growth of the main cracks is not realized due to the junction with the micro-cracks; we assume that the micro-cracks dissipate the energy of the main crack and suppressed its growth. These micro-cracks serve as additional stress accommodations, therefore the samples do not break apart after the compression test, as it is usually observed under bending and tension tests.
Understanding the mechanical behavior of silicon nanowires is essential for the implementation of advanced nanoscale devices. Although bending tests are predominantly used for this purpose, their findings should be properly interpreted through modeling. Various modeling approaches tend to ignore parts of the effective parameter set involved in the rather complex bending response. This oversimplification is the main reason behind the spread of the modulus of elasticity and strength data in the literature. Addressing this challenge, a surface-based nanomechanical model is introduced in this study. The proposed model considers two important factors that have so far remained neglected despite their significance: (i) intrinsic stresses composed of the initial residual stress and surface-induced residual stress and (ii) anisotropic implementation of surface stress and elasticity. The modeling study is consolidated with molecular dynamics-based study of the native oxide surface through reactive force fields and a series of nanoscale characterization work through in situ threepoint bending test and Raman spectroscopy. The treatment of the test data through a series of models with increasing complexity demonstrates a spread of 85 GPa for the modulus of elasticity and points to the origins of ambiguity regarding silicon nanowire properties, which are some of the most commonly employed nanoscale building blocks. A similar conclusion is reached for strength with variations of up to 3 GPa estimated by the aforementioned nanomechanical models. Precise consideration of the nanowire surface state is thus critical to comprehending the mechanical behavior of silicon nanowires accurately. Overall, this study highlights the need for a multiscale theoretical framework to fully understand the size-dependent mechanical behavior of silicon nanowires, with fortifying effects on the design and reliability assessment of future nanoelectromechanical systems.
Recovery is an important measure for seal applications representing to which extent the elastomer regains its initial shape after deformation and release of an applied force. Compression set (CS) indicates the degree of recovery. Ethylene propylene diene rubber (EPDM) was aged at 75 ◦C, 100 ◦C, 125 ◦C and 150 ◦C for different ageing times up to five years and compression set measurements were performed at different times after disassembly and after additional tempering. Short- and long-term recovery up to one year after release for samples aged at 125 ◦C and 150 ◦C was also studied. To assess the curvature in the Arrhenius diagram that may occur due to non-sufficiently aged specimens, a degradation-rate based model was fitted to the CS data after tempering. For each ageing temperature, two decay fit functions were proposed, each with an activation energy and a corresponding degradative process. The influence of ageing on the leak-tightness after fast small partial release is investigated and estimated through the analysis of the shift factors from time temperature superposition (TTS) of CS measurements at different times after disassembly. Shift factors of CS measurement after 1 s and after additional tempering are in good agreement.
In this work, we employed glow discharge optical emission spectrometry (GD-OES) depth profiling as a fast and semi-quantitative method to investigate the aluminum (Al) current collector degradation in commercial lithium cobalt oxide (LCO) pouch cells with no Al2O3 pretreatment. After battery aging, a heterogeneous deposit was found on the surface of the cathode. Gray hotspot areas within an extensive pale white region were formed. Consistent with energy dispersive X-ray (EDX) analysis of micro-cross sections milled via targeted focused ion beam (FIB), an Al-containing layer of approximately 3 µm can be observed using GD-OES. We attribute one main cause of this layer is the degradation of the Al current collector. The nonuniform growth of this layer was investigated by performing GD-OES depth profiling at different in-plane positions. We found that the gray area has a higher mass concentration of Al, probably in metallic form, whereas the white area was probably covered more homogeneously with Al2O3, resulting from the inhomogeneous distribution of the pitting positions on the current collector. Compared to FIB-EDX, GD-OES enables a faster and more convenient depth profile analysis, which allows the more productive characterization of lithium-ion batteries (LIBs), and consequently benefits the development of preferable battery materials.
The digitalization of quality control processes and the underlying data infrastructures for safety relevant components, such as hydrogen pressure vessels, plays a significant role in the transition towards Industry 4.0. In the current safety regulations for hydrogen pressure vessels, there is no established concept for structural health monitoring. The development of a reliable structural health monitoring methodology for monitoring the structural integrity of pressure vessels enables a fast-forward transition from personnel- and costintensive recurring inspections, a.k.a. periodic maintenance, to predictive maintenance. In the work presented; we investigated the application of ultrasonic guided wave propagation to monitor and assess the condition of Type IV composite overwrapped pressure vessel (COPV). A sensor network of fifteen piezo-electric wafers is placed on the carbon fibre reinforced composite cylinder. Five different artificial damage configurations are created by gluing two different weight blocks on three different locations. The database containing measured guided wave data sets is enriched by two different boundary conditions. We utilized an open-source software, openBIS labnotebook, to store and analyse experimental datasets. The guided wave ultrasonic signals were investigated and analysed by using commonly used ultrasonic features (e.g., amplitude, frequency, time of flight) as well as non-traditional time-series features (kurtosis, skewness, variance). The features were used to calculate damage index and the detection performance for the results has been evaluated. The results suggest that both traditional and non-traditional features assume significant importance in artificial damage detection. The future works will additionally involve the impacts of operational conditions, such as periodic pressure variations temperature loadings as well as material degradations.
Li dendrites penetration through solid electrolytes (SEs) challenges the development of solid-state Li batteries (SSLBs). To date, significant efforts are devoted to understand the mechanistic dynamics of Li dendrites nucleation, growth, and propagation in SEs, and various strategies that aim to alleviate and even inhibit Li dendrite formation have been proposed. Nevertheless, most of these conventional strategies require either additional material processing steps or new materials/layers that eventually increase battery cost and complexity. In contrast, using external fields, such as mechanical force, temperature physical field, electric field, pulse current, and even magnetic field to regulate Li dendrites penetration through SEs, seems to be one of the most cost-effective strategies. This review focuses on the current research progress of utilizing external physical fields in regulating Li dendrites growth in SSLBs. For this purpose, the mechanical properties of Li and SEs, as well as the experimental results that visually track Li penetration dynamics, are reviewed. Finally, the review ends with remaining open questions in future studies of Li dendrites growth and penetration in SEs. It is hoped this review can shed some light on understanding the complex Li dendrite issues in SSLBs and potentially guide their rational design for further development.
Accurate and precise isotope ratio measurements of heavy elements are playing an increasinglyimportant role in modern analytical sciences and have numerous applications. Today, isotope ratio measurements are typically performed with two principal techniques: thermal ionization mass spectrometry (TIMS) and multiple collector-inductively coupled plasma mass spectrometry (MC-ICP-MS). To obtain accurate results by mass spectrometry, isotopic certified reference materials (iCRMs) are needed for mass bias correction and for the validation of the method used for analysis.Thus, it is of paramount importance to achieve measurement comparability of all data reported, and to assess measurement capability of each CRM producer/National Metrology Institute (NMI). Therefore, the international comparison (CCQM-P213) was performed to assess the analytical capabilities of NMIs for the accurate determination of copper isotope ratio delta values in high purity materials. The study was proposed by the coordinating laboratories, National Research Council Canada (NRC), National Institute of Standards and Technology (NIST), Bundesanstalt für Materialforschung und -prüfung (BAM) and Physikalisch-Technische Bundesanstalt (PTB), as an activity of the Isotope Ratio Working Group (IRWG) of the Consultative Committee for Amount of Substance - Metrology in Chemistry and Biology (CCQM). Participants included six NMIs and one designated institute (DI) from the six countries. Although no measurement method was prescribed by the coordinating laboratories, MC-ICP-MS with either standard-sample bracketing (SSB) or combined SSB with internal normalization (C-SSBIN) models for mass bias correction were recommended. Results obtained from the six NMIs and one DI were in good agreement.
Liquid metal embrittlement (LME) cracking is a phenomenon observed during resistance spot welding (RSW) of zinccoated advanced highstrength steels (AHSS) in automotive manufacturing. In this study, severe cracks are observed at the edge of the sheet under reduced flange widths. These cracks, traversing the AHSS sheet, culminate at the edge with a width of approximately 1.2 mm.
Through combined numerical and experimental investigations, and material testing, these cracks are identified and validated as a new type of LME crack. The mechanism behind this crack formation is attributed to unique geometric conditions that, when compared to center welding, amplify radial material flow by ninefold to 0.87 mm. The resultant tangential tensile stresses approximate 760 MPa, which exceed the yield strength of the examined advanced highstrength steel (AHSS) under heightened temperature conditions, and when combined with liquid zinc, promote the formation of this new type of LME crack.
The effect of the oscillating metal vapor plume on the keyhole and molten pool behavior during the laser beam welding of AlMg3 aluminum alloys is investigated by experimental and numerical methods. The real-time height of the metal vapor plume is measured by high-speed camera observation. The obtained experimental results are used to evaluate the additional heating source and laser beam attenuation caused by the scattering and absorption based on the Beer–Lambert theory. Furthermore, the dynamic behavior of the metal vapor plume is incorporated into a 3D transient heat transfer and fluid flow model, coupled with the ray tracing method, for the laser beam welding of the AlMg3 alloy. It is found that additional heating resulting from the scattered and absorbed laser beam energy by the metal vapor plume significantly expands the shape of the molten pool on the top region. Moreover, the oscillating metal vapor plume caused the fluctuation of the high-temperature region in the molten pool. The probability of keyhole collapse at the bottom increases 17% due to the oscillating laser power induced by the laser beam attenuation. The internal interplay between the metal vapor plume, molten pool shape, and keyhole collapse is obtained. The developed model has been validated by experiments, which shows a good agreement.
Through experimental observation and auxiliary numerical simulation, this investigation studies the different types of grain refinement of 5754 aluminum alloy laser beam welding by applying a transverse oscillating magnetic field. Scanning electron microscope results have proved that the application of a magnetic field can reduce the average crystal branch width and increase its number. The interaction between the induced eddy current generated by the Seebeck effect and the applied external magnetic field produces a Lorentz force, which is important for the increase in the number of crystal branches. Based on the theory of dendrite fragmentation and the magnetic field-induced branches increment, the grain size reduction caused by the magnetic field is studied. Furthermore, the effects of the magnetic field are analyzed by combining a phase field method model and simulations of nucleation and grain growth. The grain distribution and average grain
size after welding verify the reliability of the model. In addition, the introduction of a magnetic field can increase the number of periodic three-dimensional solidification patterns. In the intersection of two periods of solidification patterns, the metal can be re-melted and then re-solidified, which prevents the grains, that have been solidified and formed previously, from further growth and generates some small cellular grains in the new fusion line. The magnetic field increases the building frequency of these solidification structures and thus promotes this kind of grain refinement.
Uncertainty quantification of multimodal surface wave inversion using artificial neural networks
(2023)
An inversion of surface waves dispersion curves is a non-unique and ill-conditioned problem. The inversion result has a probabilistic nature, which becomes apparent when simultaneously restoring the shear wave (S-wave) velocity and layer thickness. Therefore, the problem of uncertainty quantification is relevant. Existing methods through deterministic or global optimization approaches of uncertainty quantification via posterior probability density (PPD) of the model parameters are not computationally efficient since they demand multiple solutions of the inverse problem. We present an alternative method based on a multi-layer fully connected artificial neural network (ANN). We improve the current uni-modal approach, which is known from publications, to multi-modal inversion. The learned ANN maps the phase velocity dispersion curves to values of the S-wave velocity and layers thickness. To estimate the uncertainties, we adapt the Monte-Carlo simulation strategy and project onto the resulting velocity model both frequency-dependent data noise and inverse operator errors, which are evaluated by the prediction of the training data set. The proposed combination of surface waves data processing methods, configured with each other, provides a novel surface waves multi-modal dispersion data inversion and uncertainty quantification approach. We first test our approach on synthetic experiments for various velocity models: a positive velocity gradient, a low-velocity layer and a high-velocity layer. This is done considering uni-modal inversion at first and then compared to the multi-modal inversion. Afterwards, we apply our approach to field data and compare resulting models with the body S-wave processing by the generalized reciprocal method (GRM). The experiments show high-potential results using ANN yields the possibility to accurately estimate PPD of restored model parameters without a significant computational effort. The PPD-based comparison demonstrates advantages of a multi-modal inversion over uni-modal inversion. The trained ANN provides reasonable model parameters predictions and related uncertainties in real-time.
Comparing the performance of molecular and nanoscale luminophores and luminescent microand nanoparticles and estimating achievable signal amplitudes and limits of detection requires a standardizable intensity scale. This initiated the development of the relative MESF (number of molecules of equivalent soluble fluorochromes) and ERF (equivalent reference fluorophores) scales for flow cytometry and fluorescence microscopy. Both intensity scales rely on fluorescence intensity values assigned to fluorescent calibration beads by an intensity comparison to spectrally closely matching fluorophore solutions of known concentration using a spectrofluorometer. Alternatively, the luminophore or bead brightness (B) can be determined that equals the product of the absorption cross section (σa) at the excitation wavelength (σa(λex)) and the photoluminescence quantum yield (Φpl).
Thereby, an absolute scale based on fundamental and measurable spectroscopic properties can be realized which is independent of particle size, material, and luminophore staining or labeling density and considers the sensitivity of the optical properties of luminophores to their environment. Aiming for establishing such a brightness scale for light-scattering dispersions of luminescent particles with sizes exceeding a few ten nanometers, we demonstrate how the brightness of quasi-monodisperse 25 nm, 100 nm, and 1 μm sized polystyrene particles (PSP), loaded with two different dyes in varying concentrations, can be obtained with a single custom-designed integrating sphere setup that enables the absolute determination of Φpl and transmittance and diffuse reflectance measurements. The resulting Φpl, σa(λex), imaginary parts of the refractive index, and calculated B values of these samples are given in dependence of the number of incorporated dye molecule per particle. Finally, a unitless luminescence efficiency (LE) is defined allowing for the direct comparison of luminescence efficiencies of particles with different sizes.
A facile yet robust synthesis is reported herein to simultaneously incorporate atomically dispersed Co-Nₓ sites with graphitic layer-protected Co₉S₈ nanoparticles (denoted as Co SACs+Co₉S₈) as an efficient electrocatalyst for oxygen reduction in acidic solution. The Co SACs+Co₉S₈ catalyst shows low H₂O₂ selectivity (∼5 %) with high half-wave potential (E1/2) of ∼0.78 V(RHE) in 0.5 M H₂SO₄. The atomic sites of the catalyst were quantified by a nitrite stripping method and the corresponding site density of the catalyst is calculated to be 3.2×10¹⁸ sites g⁻¹. Besides, we also found the presence of a reasonable amount of Co₉S₈ nanoparticles is beneficial for the oxygen electrocatalysis. Finally, the catalyst was assembled into a membrane electrode assembly (MEA) for evaluating its performance under more practical conditions in proton exchange membrane fuel cell (PEMFC) system.
The hybrid mixture of combustible dusts and flammable gases/vapours widely exist in various industries, including mining, petrochemical, metallurgical, textile and pharmaceutical. It may pose a higher explosion risk than gas/vapor or dust/mist explosions since the hybrid explosions can still be initiated even though both the gas and the dust concentration are lower than their lower explosion limit (LEL) values. Understanding the explosion threat of hybrid mixtures not only contributes to the inherent safety and sustainability of industrial process design, but promotes the efficiency of loss prevention and mitigation. To date, however, there is no test standard with reliable explosion criteria available to determine the safety parameters of all types of hybrid mixture explosions, nor the flame propagation and quenching mechanism or theoretical explanation behind these parameters. This review presents a state-of-the-art overview of the comprehensive understanding of hybrid mixture explosions mainly in an experimental study level; thereby, the main limitations and challenges to be faced are explored. The discussed main contents include the experimental measurement for the safety parameters of hybrid mixtures (i.e., explosion sensitivity and severity parameters) via typical test apparatuses, explosion regime and criterion of hybrid mixtures, the detailed flame propagation/quenching characteristics behind the explosion severities/sensitivities of hybrid mixtures. This work aims to summarize the essential basics of experimental studies, and to provide the perspectives based on the current research gaps to understand the explosion hazards of hybrid mixtures in-depth.
Bulk metallic glasses (BMG) are amorphous metal alloys known for their unique physical and mechanical properties. In the present study, the formation of femtosecond (fs) laser-induced periodic surface structures (LIPSS) on the Zr-based BMGs Zr46Cu46Al8, Zr61Cu25Al12Ti2, Zr52.5Cu17.9Al10Ni14.6Ti5 (Vit105) and Zr57Cu15.4Al10Ni12.6Nb5 (Vit106) was investigated as a function of their different chemical composition. For this purpose, LIPSS were generated on the sample surfaces in an air environment by fs-laser irradiation (λ = 1025 nm, τ = 300 fs, frep = 100 kHz). The surface topography was characterized by scanning electron microscopy and atomic force microscopy. Moreover, the impact of LIPSS formation on the structure and chemical surface composition was analyzed before and after fs-laser irradiation by X-ray diffraction and X-ray photoelectron spectroscopy as well as by transmission electron microscopy in combination with energy dispersive X-ray spectroscopy. Despite the different chemical composition of the investigated BMGs, the fs-laser irradiation resulted in almost similar properties of the generated LIPSS patterns. In the case of Zr61Cu25Al12Ti2, Vit105 and Vit106, the surface analysis revealed the preservation of the amorphous state of the materials during fs-laser irradiation. The study demonstrated the presence of a native oxide layer on all pristine BMGs. In addition, fs-laser irradiation results in the formation of laser-induced oxide layers of larger thickness consisting of an amorphous ZrAlCu-oxide. The precise laser-structuring of BMG surfaces on the nanoscale provides a versatile alternative to thermoplastic forming of BMG surfaces and is of particular interest for the engineering of functional material surfaces.
Wear behavior of innovative niobium carbide cutting tools in ultrasonic-assisted finishing milling
(2023)
The resources of niobium exceed the ones of tungsten by an order of magnitude. With 92%, Brazil is today the main global producer of niobium. Hence, niobium carbides (NbC) are a sustainable and economic alternative to conventionally used cutting materials, especially tungsten carbides (WC). Moreover, NbC can be used in Ni alloy matrix and thus offer significant advantages by substituting WC in Co matrix as cutting materials in terms of health risks and raw material price and supply risk. Based on recent studies which found an increased performance of NbC compared to WC cutting tools in machining higher strength steels, the composition NbC12Ni4Mo4VC was chosen for finish machining of a high-strength steel S960QL in this study. The experiments were carried out on an ultrasonic-assisted 5-axis milling machine using NbC tools specially made to benchmark them with commercially available coated WC cutting inserts. In addition, the influence of a coating system for the NbC inserts is tested and evaluated for its performance in the cutting process. Tool wear and cutting force analyses are implied to identify optimal parameter combinations as well as tool properties for the novel NbC tool. Together with the oscillation of ultrasonic-assisted milling, the loads on the component surface and the tool can be reduced and the wear behavior of the novel NbC tool can be refined. These milling tests are accompanied by standardized wear tests, i.e., pin-on-disc, between the aforementioned material combinations, and the results are correlated with each other. Finally, the behavior when using hard-to-cut materials such as Ni alloys, or innovative materials such as iron aluminide is also being tested, as these are constantly in the focus of machining optimization. With this strategy, comprehensive knowledge is achievable for future efficient application of NbC for milling tools, which have already been researched for decades using WC.
We investigated the performance of nitrogen microwave inductively coupled atmospheric-pressure plasma mass spectrometry (MICAP-MS) under matrix effects and its applicability to trace element analysis in steels. Influences of different gas flows and ion optics on the matrix tolerance are studied, indicating that nebulizer gas flow has the most significant impact. Optimization of ion optics improves matrix tolerance for light elements due to the reduction of the inelastic collisional scattering effect. With optimized operating conditions, MICAP-MS achieves an internal standard intensity recovery of over 90% at an Fe concentration of 500 mg L−1. Even at an Fe concentration of 1 g L−1, the recovery remains above 80%. Three certified reference materials – non-alloy, low-alloy and high-alloy steel – were analyzed using MICAP-MS. The determined mass concentrations of the trace and minor components show metrological compatibility to the reference values. No significant differences are observed between the results obtained with aqueous and matrix-matched calibration, demonstrating the strong matrix tolerance of MICAP-MS, and its promising applicability to steel analysis.
Bei einem Schulexperiment mit Brennspiritus kam es zu einer „Verpuffung“ und durch den entstandenen „Feuerball“ fing die Kleidung von zwei Schülern und des Lehrers Feuer. Der Aufsatz arbeitet das Strafbefehlsverfahren auf, diskutiert Verantwortlichkeit, Pflichtverletzung und Verschulden des Lehrers und geht auf die im Strafbefehlsverfahren nicht in Bezug genommenen konkreten Regelungen der DGUV zu Unterricht an Schulen mit gefährlichen Stoffen ein.
Technische Regeln im Arbeitsschutz – wie TRBS für die Betriebssicherheitsverordnung und TRGS für die Gefahrstoffverordnung – sind nicht zwingendes Recht, sondern konkretisierende Empfehlungen mit Vermutungswirkung. In Gerichtsurteilen werden sie eher selten herangezogen. Wie diese – und Branchenregelungen von Verbänden – von der Rechtsprechung diskutiert werden, zeigt ein Urteil des Verwaltungsgerichts Münster.
Die Begriffe gefährlicher Stoff und Gefahrstoff werden häufig nicht unterschieden – in vielen Fällen resultieren aber durch den Kontext auch keine Missverständnisse. Tatsächlich bestehen aber Unterschiede – sowohl inhaltlich als auch bezüglich des Rechtsbereichs, der jeweils für sie gilt.
Stoffe sind gefährlich, wenn sie den Kriterien der CLP-Verordnung für physikalische Gefahren, Gesundheitsgefahren oder Umweltgefahren entsprechen. Sie werden dann im Sinne der CLP-Verordnung entsprechend eingestuft und es ergeben sich Pflichten bezüglich des Inverkehrbringens innerhalb der EU.
Gefahrstoffe sind in der Gefahrstoffverordnung definiert. Sie beinhalten die gefährlichen Stoffe und weitere nicht notwendigerweise als gefährlich eingestufte Stoffe. Das Ziel ist vor allem der Schutz von Beschäftigten bei Tätigkeiten mit Gefahrstoffen – es handelt sich also um eine Arbeitsschutzvorschrift.
Dieser Aufsatz stellt gefährliche Stoffe in ihrem Kontext vor, gibt einen Überblick über die Prinzipien und Rechtsfolgen sowie Hinweise auf weiterführende Informationen und stellt ihnen die Gefahrstoffe gegenüber.
AbstractMicroplastics (MP) can be detected in all environmental systems. Marine and terrestrial aquatic systems, especially the transported suspended solids, have often been the focus of scientific investigations in the past. Sediments of aquatic river systems, on the other hand, were often ignored due to the time‐consuming sample preparation and analysis procedures. Spectroscopic measurement methods counting particle numbers are hardly suitable as detection methods, because there are plenty of natural particles next to a small number of MP particles. Integral methods, such as thermoanalytical methods are determining the particle mass independently of the inorganic components.In this study, a workflow for sample preparation via density separation and subsequent analysis by thermal extraction desorption‐gas chromatography/mass spectrometry is presented, which leads to representative and homogeneous samples and allows fast and robust MP mass content measurements suitable for routine analysis. Polymers were identified and quantified in all samples. Polyethylene and styrene‐butadiene rubber are the dominant polymers, besides polypropylene and polystyrene. Overall, total polymer masses between 1.18 and 337.0 µg/g could be determined. Highest MP concentrations in riverbed sediment are found in sites characterized by low flow velocities in harbors and reservoirs, while MP concentrations in sandy/gravelly bed sediments with higher flow velocities are small.
Inputs of plastic impurities into the environment via the application of fertilizers are regulated in Germany and the EU by means of ordinances. Robust and fast analytical methods are the basis of legal regulations. Currently, only macro- and large microplastic contents (>1 mm) are measured. Microplastics (1–1,000 µm), are not yet monitored. Thermal analytical methods are suitable for this purpose, which can determine the mass content and can also be operated fully automatically in routine mode. Thermal extraction desorption-gas chromatography/mass spectrometry (TED-GC/MS) allows the identification of polymers and the determination of mass contents in solid samples from natural environments. In accordance with the German or European Commission (EC) Fertiliser Ordinance, composting plants should be monitored for microplastic particles with this method in the future. In this context a compost plant was sampled. At the end of the rotting process, the compost was sieved and separated in a coarse (>1 mm) and a fine fraction (<1 mm). The fine fraction was processed using density separation comparing NaCl and NaI as possible salt alternative and screened for microplastic masses by TED-GC/MS with additional validation and quality assurance experiments. With TED-GC/MS total microplastics mass contents of 1.1–3.0 μg/mg in finished compost could be detected with polyethylene mainly. What differs much to the total mass of plastics in the coarse fraction with up to 60 μg/mg, which were visually searched, identified via ATR-FTIR and gravimetrically weighted.
Reclaimed asphalt pavements (RAP) with increased contents of polycyclic aromatic hydrocarbons (PAH) are restricted for reuse due to their harmful effects on humans and the environment. This work investigated whether Fourier transform infrared (FTIR) spectroscopy is suitable for a fast and simple identification and quantification of PAH in binders recovered from reclaimed asphalts. For this, the binders from 34 RAP samples were recovered using a rapid procedure developed at the Universität Kassel and were examined with infrared spectroscopy. The obtained spectra were pre-processed (Standard Normal Variate transformation, 1st derivative) and evaluated using a combination of factor analysis and linear discriminant analysis. The results showed that various PAH groups with differently pronounced aromatic structures are present in the binders.
However, with FTIR spectroscopy combined with the multivariate methods, a statistical model was developed allowing for the differentiation between the PAH groups and also for the distinction between PAH contents below or above the threshold of 25 mg/kg valid in Germany.
Die Fourier-Transformations-Infrarot-Spektroskopie (FTIR-Spektroskopie) stellt eine innovative und wirkungsvolle Methode zur Charakterisierung von Bitumen und bitumenhaltigen Bindemitteln dar. So erlaubt die FTIRCharakterisierung nicht nur eine Bewertung des Alterungsfortschritts eines Bindemittels, sondern zudem auch die Identifizierung von im Bitumen enthaltenen Additiven und Schadstoffen wie z. B. polyzyklischen aromatischen Kohlenwasserstoffen (PAK), die Ableitung verschiedener physikalischer und chemischer Kennwerte sowie weiterhin eine Klassifizierung von Bindemitteln nach verschiedenen übergeordneten Eigenschaften wie der Raffinerie, dem Alterungszustand und auch der Alterungsempfindlichkeit.
In this work, a methodology based on Fourier transform infrared (FTIR)spectroscopy and multivariate evaluation is presented to estimate the aging sensitivity of bitumen based on the unaged samples and thus without the need for time- and material-consuming aging simulations. For this purpose, factor analysis and linear discriminant analysis are used to develop a statistical model based on the FTIR spectra of unaged bitumen samples, which can be used fast and simple in everyday laboratory work and allows to assign the bitumen to a low, moderate, or strong aging sensitivity. The evaluation of the aging sensitivity is based on the complex shear modulus|G* | and the phase angle δ from the measurement with a dynamic shear rheometer(DSR), whose aging-related changes were captured as the slope in the Black diagram. A relevant influence on the classification concerning the aging sensitivity has the oxygen-containing compounds(sulfoxide, hydroxyl and partly carbonyl compounds), whereby lower contents and thus less preaged bitumen tend to have a stronger aging sensitivity. However, in addition to the oxygen-containing compounds, the structure of the aliphatic and aromatic compounds and, in particular, the interaction of the different structures are decisive for the aging sensitivity
Alcohol-initiated ROPs of L-Lactide were performed at 140 ◦C in bulk with variation of the initiator/catalyst ratio and time. Lower ratios favor the formation of cycles which upon annealing display a change of the MALDI mass peak distribution towards a new maximum with a “saw-tooth pattern” of the mass peaks representing the cycles.
Such a pattern was not observed for the mass peak of the linear chains. The coexistence of these patterns indicate that linear and cyclic poly (L-lactide)s (PLA) crystallize in separate crystals, and that the crystallites of the cycles are made up by extended rings. High Tm and ΔHm values confirm that these extended-ring crystallites represent a thermodynamically optimized form of PLA. Experiments with preformed cyclic and linear PLAs support this interpretation.
Conceptually, high-precision manufacturing is a sequence of production and measurement steps, where both kinds of steps require to use non-deterministic models to represent production and measurement tolerances. This paper demonstrates how to effectively represent these manufacturing processes as Partially Observable Markov Decision Processes (POMDP) and derive an offline strategy with state-of-the-art Monte Carlo Tree Search (MCTS) approaches. In doing so, we face two challenges: a continuous observation space and explainability requirements from the side of the process engineers. As a result, we find that a tradeoff between the quantitative performance of the solution and its explainability is required. In a nutshell, the paper elucidates the entire process of explainable production planning: We design and validate a white-box simulation from expert knowledge, examine state-of-the-art POMDP solvers, and discuss our results from both the perspective of machine learning research and as an illustration for high-precision manufacturing practitioners.
Material extrusion of thermoplastic polymers enables the realization of complex specific designs with high performance composites. The present study aims at evaluating the mechanical properties of carbon fiberreinforced semi-crystalline thermoplastic polymer polyether ether ketone (CFR-PEEK) manufactured by material extrusion and correlating them with results obtained by micro-CT. Samples in the shape of small bars were provided by Kumovis (Munich, Germany). The determination of surface roughness and density was followed by three-point bending tests. To reveal the pore distribution as well as the fusion quality of CFR PEEK when applied with external forces, micro-CT scans were performed with an X-ray microscope before and after the mechanical test to localize the sites where the fracture is generated. The density of CFR-PEEK bars indicated that they had superior mechanical properties compared with our previous study on unfilled 3D printed PEEK (bending modulus: (5.4 ± 0.5) GPa vs. (1.05 ± 0.05) GPa to (1.48 ± 0.10) GPa; bending strength: (167 ± 11) MPa vs. (51 ± 15) to (193 ± 7) MPa). Micro-CT analyses revealed the local 3D-distribution of voids. Voids of 30 μm diameter are nearly spherical and make up the main part of the total porosity. The larger the voids, the more they deviate from a spherical shape. Significant lack-of-fusion voids are located between the deposited filaments. By growing and merging, they act as seeds for the forming fracture line in the region of the flexural specimens where the maximum local tensile stresses occurred under bending load. Our work provides a detailed analysis of printed PEEK with fiber additive and relates this with mechanical properties.
The effect of spin fluctuations on the α(bcc)-γ(fcc)-δ(bcc) structural phase transitions in iron is investigated with a tight-binding (TB) model. The orthogonal d-valent TB model is combined with thermodynamic integration, spin-space averaging, and Hamiltonian Monte Carlo to compute the temperature-dependent free-energy difference between bcc and fcc iron. We demonstrate that the TB model captures experimentally observed phonon spectra of bcc iron at elevated temperatures. Our calculations show that spin fluctuations are crucial for both the α−γ and γ−δ phase transitions but they enter through different mechanisms. Spin fluctuations impact the α−γ phase transition mainly via the magnetic/electronic free-energy difference between bcc and fcc iron. The γ−δ phase transition, in contrast, is influenced by spin fluctuations only indirectly via the spin-lattice coupling. Combining the two mechanisms, we obtain both the α−γ and γ−δ phase transitions with our TB model. The calculated transition temperatures are in very good agreement with experimental values.
Along with the desire for developing novel multi-principal element alloys, also known as high-entropy alloys, the concern about their safe application is also increasingly growing. This relates to the alloys’ phase stability, in particular, the control required over unexpected phase decompositions resulting from solute segregation at grain boundaries. Yet, the mechanisms of co-segregation and grain boundary phase decomposition in multi-component alloys are rather challenging to explore. In fact, quantitative investigation of grain boundary behaviors is mostly conducted for binary and a few ternary alloys. In this work, we apply the recently introduced CALPHAD-integrated density-based formalism [RSC Advances 10 (2020) 26728-26741] for considering co-segregation phenomena in alloys with an arbitrary number of components —the term ‘co-segregation’ here refers to co-evolution and any mutual interplay among the solute atoms during their interaction with a grain boundary. Quaternary Fe-Co-Mn-Cr alloy system is studied. We present two major advances beyond previous results: First, a co-segregation-induced multi-component grain boundary spinodal decomposition is quantitatively simulated for the first time. We found that in addition to its low cohesive energy and asymmetrical mixing enthalpy due to magnetic ordering, Mn plays a leading role in triggering interfacial phase decomposition by having a relatively large, concentration-dependent atomic mobility. Second, as an alternative to grain boundary phase diagrams proposed for binary and ternary alloys, we introduce the concept of co-segregation maps for grain boundary segregation screening and design in multi-component alloys. Applying the co-segregation maps, the nonlinear Mn and Cr co-segregation are discussed. Depicted on the alloying composition and phase space, the co-segregation maps enable the required insights to guide a safer, more controlled design of high-entropy alloys.
Photodynamic therapy (PDT) used for treating cancer relies on the generation of highly reactive oxygen species, for example, singlet oxygen 1O2, by light-induced excitation of a photosensitizer (PS) in the presence of molecular oxygen, inducing DNA damage in close proximity of the PS. Although many precious metal complexes have been explored as PS for PDT and received clinical approval, only recently, the potential of photoactive complexes of nonnoble metals as PS has been discovered. Using the DNA origami technology that can absolutely quantify DNA strand break cross sections, we assessed the potential of the luminescent transition metal complex [Cr(ddpd)2]3+ (ddpd=N,N’-dimethyl-N,N’-dipyridine-2-ylpyridine-2,6-diamine) to damage DNA in an air-saturated aqueous environment upon UV/Vis illumination. The quantum yield for strand breakage, that is, the ratio of DNA strand breaks to the number of absorbed photons, was determined to 1–4%, indicating efficient transformation of photons into DNA strand breaks by [Cr(ddpd)2]3+.
Wire arc additive manufacturing (WAAM) enables the efficient production of weight-optimized modern engineering structures. Further increases in efficiency can be achieved by using high-strength structural steels. Commercial welding consumables for WAAM are already available on the market. Lack of knowledge and guidelines regarding welding residual stress and component safety during production and operation leads to severely limited use for industry applications. The sensitive microstructure of high-strength steels carries a high risk of cold cracking; therefore, residual stresses play a crucial role. For this reason, the influences of the material, the WAAM process, and the design on the formation of residual stresses and the risk of cold cracking are being investigated. The material used has a yield strength of over 800 MPa. This strength is adjusted via solid solution strengthening and a martensitic phase transformation. The volume expansion associated with martensite formation has a significant influence on the residual stresses. The focus of the present investigation is on the additive welding parameters and component design on their influence on hardness and residual stresses, which are analyzed by means of X-ray diffraction (XRD). Reference specimens (hollow cuboids) are welded fully automated with a systematic variation of heat control and design. Welding parameters and AM geometry are correlated with the resulting microstructure, hardness, and residual stress state. Increased heat input leads to lower tensile residual stresses which causes unfavorable microstructure and mechanical properties. The component design affects heat dissipation conditions and the intensity of restraint during welding and has a significant influence on the residual stress.
Evaluation of Charpy-V transition curve fitting based on distribution-free statistical assessment
(2023)
A non-parametric, distribution-free, statistical assessment of 5 large Charpy transition curve data sets is used for the optimum fitting equations for smaller data sets. The assessment makes use of a combination of rank probability and binomial probability analysis of the data. The original non-parametric assessment method is improved by combining upper and lower bound binomial estimates, thus removing a bias that exists in the original method. The non-parametric assessment is not suitable as a standard method because it requires too many data points to give a reliable result. It is, however, ideal as a research tool to examine transition curve shape and scatter. Based on the assessment several recommendations for transition curve fitting can be made.
The increasing amount and complexity of clinical data require an appropriate way of storing and analyzing those data. Traditional approaches use a tabular structure (relational databases) for storing data and thereby complicate storing and retrieving interlinked data from the clinical domain. Graph databases provide a great solution for this by storing data in a graph as nodes (vertices) that are connected by edges (links). The underlying graph structure can be used for the subsequent data analysis (graph learning). Graph learning consists of two parts: graph representation learning and graph analytics. Graph representation learning aims to reduce high-dimensional input graphs to low-dimensional representations. Then, graph analytics uses the obtained representations for analytical tasks like visualization, classification, link prediction and clustering which can be used to solve domain-specific problems. In this survey, we review current state-of-the-art graph database management systems, graph learning algorithms and a variety of graph applications in the clinical domain. Furthermore, we provide a comprehensive use case for a clearer understanding of complex graph learning algorithms.
Immobilized metal affinity chromatography (IMAC) is a widely used technique for purifying polyhistidine-tagged recombinant proteins. However, it often has practical limitations that require complex optimizations and additional steps for purification. In this study, we introduce functionalized corundum particles as a novel, efficient, and economical method for purifying recombinant proteins in a column-free format. The corundum surface is modified with amino silane APTES, followed by EDTA dianhydride, and then loaded with nickel ions. We used the Kaiser test to monitor the modification process and ICP-MS to quantify the metal-binding capacity. To evaluate the system, we used His-tagged protein A/G (PAG) mixed with bovine serum albumin (BSA). The corundum particles exhibited a binding capacity of approximately 3 mg of protein per gram of corundum or 2.4 mg per 1 mL of corundum suspension. We also examined cytoplasm obtained from different E. coli strains as an example of a complex matrix. Varying the imidazole concentration in the loading and washing buffers showed that higher concentrations during loading improved purity. Even with sample volumes as large as one liter, we successfully isolated recombinant proteins down to a concentration of 1 µg/mL. We found higher purity levels with corundum when comparing the corundum material to standard Ni–NTA agarose beads. We successfully purified His6-MBP-mSA2, a fusion protein comprising monomeric streptavidin and maltose-binding protein, from E. coli cytoplasm, demonstrating the method's applicability. We also purified SARS-CoV-2-S-RBD-His8 expressed in human Expi293F cells, confirming its suitability for mammalian cell culture supernatants. The material cost of the nickel-loaded corundum material (without regeneration) is estimated to be less than 30 cents per gram of functionalized support or 10 cents per milligram of isolated protein. Another advantage of this system is the exceptional physical and chemical stability of corundum particles. Overall, we have demonstrated that this novel material offers an efficient, robust, and cost-effective purification platform for His-tagged proteins, even in challenging, complex matrices and large sample volumes with low product concentrations. This method has potential applications in both small laboratories and large-scale industrial settings.
Concrete structures experience severe damage during service, for example due to pitting corrosion of rebars caused by the ingress of chlorine (Cl) into the porous concrete structure. The ingress can be monitored using laser-induced breakdown spectroscopy (LIBS), a recently introduced civil engineering technique used to detect Cl in concrete structures in addition to conventional wet chemistry methods. The key advantages of LIBS are high spatial resolution, which is important when analyzing heterogeneous concrete samples, as well as the almost complete absence of sample preparation. To assess LIBS as a reliable analytical method, its accuracy and robustness must be carefully tested. This paper presents the results of an interlaboratory comparison on the analysis of Cl in cement paste samples conducted by 12 laboratories in 10 countries. Two sets of samples were prepared with Cl content ranging from 0.06 to 1.95 wt% in the training set and 0.23–1.51 wt% in the test set, with additional variations in the type of cement and Cl source (salt type). The overall result shows that LIBS is suitable for the quantification of the studied samples: the average relative error was generally below 15%. The results demonstrate the true status quo of the LIBS method for this type of analysis, given that the laboratories were not instructed on how to perform the analysis or how to process the data.
The Boltzmann plot method is widely used to determine the temperature of laser induced plasma. It involves the use of individual lines that are not easy to find in complex spectra and/or in the spectral range available. If the number of such lines is not enough to build a reliable Boltzmann plot, overlapping lines are often used, which are separated by software. However, line separation is a rather imprecise procedure, which, in addition, requires significant computational costs. This study proposes an extension of the Boltzmann plot method that allows a specific group of unresolved lines to be included in a Boltzmann plot without the need to separate them. This group of lines are multiplets, lines of the same element with similar upper and lower transition states. The multiplet lines along with the individual lines are included in the algorithm, which also includes a correction for self-absorption and is used to determine the plasma temperature. The algorithm is tested on synthetic spectra which are consistent with the model of a homogeneous isothermal plasma in local thermodynamic equilibrium and is shown to be superior to the standard Boltzmann plot method both in more accurate determination of the plasma temperature and in a significant reduction in the computational time. The advantages and disadvantages of the method are discussed in the context of its applications in laser induced breakdown spectroscopy.
The electron density and temperature of a laser-induced plasma can be determined from the width and intensity of the spectral lines, provided that the corresponding optical transitions are optically thin. However, the lines in laser induced plasma are often self-absorbed. One of the methods of correction of this effect is based on the use of the Planck function and an iterative numerical calculation of the plasma temperature. In this study, the method is further explored and its inherent errors and limitations are evaluated. For this, synthetic spectra are used that fully correspond to the assumed conditions of a homogeneous isothermal plasma at local thermodynamic equilibrium. Based on the error analysis, the advantages and disadvantages of the method are discussed in comparison with other methods of self-absorption correction.
In recent decades, the number of components in concrete has grown, particularly in formulations aimed at reducing carbon footprints. Innovations include diverse binders, supplementary cementitious materials, activators, concrete admixtures, and recycled aggregates. These developments target not only the enhancement of material properties but also the mitigation of the ecological and economic impacts of concrete — the most extensively used material by humankind. However, these advancements also introduce a greater variability in the composition of raw materials. The material’s behavior is significantly influenced by its nanoscale properties, which can pose challenges in accurate characterization. Consequently, there’s an increasing need for experimental tuning of formulations. This is accompanied by a more inconsistent composition of raw materials, which makes an experimental tuning of formulations more and more necessary. However, the increased complexity in composition presents a challenge in finding the ideal formulation through trial and error. Inverse design (ID) techniques offer a solution to this challenge by allowing for a comprehensive search of the entire design space to create new and improved concrete formulations. In this publication, we introduce the concept of ID and demonstrate how our open-source app “SLAMD” provides all necessary steps of the workflow to adapt it in the laboratory, lowering the application barriers. The intelligent screening process, guided by a predictive model, leads to a more efficient and effective data-driven material design process resulting in reduced carbon footprint and improved material quality while considering socio-economic factors in the materials design.
This paper presents a novel approach for developing sustainable building materials through Sequential Learning. Data sets with a total of 1367 formulations of different types of alkali-activated building materials, including fly ash and blast furnace slag-based concrete and their respective compressive strength and CO2-footprint, were compiled from the literature to develop and evaluate this approach. Utilizing this data, a comprehensive computational study was undertaken to evaluate the efficacy of the proposed material design methodologies, simulating laboratory conditions reflective of real-world scenarios. The results indicate a significant reduction in development time and lower research costs enabled through predictions with machine learning. This work challenges common practices in data-driven materials development for building materials. Our results show, training data required for data-driven design may be much less than commonly suggested. Further, it is more important to establish a practical design framework than to choose more accurate models. This approach can be immediately implemented into practical applications and can be translated into significant advances in sustainable building materials development.
Lithium-ion batteries are a key technology to achieve the goals of limiting climate change due to the important role as traction technology for Electric Vehicles and in stationary energy storage systems. Over(dis) charge, mechanical damage due to accidents or thermal abuse such as fires can initiate an accelerated self-heating process of the batteries, called thermal runaway. A thermal runaway can propagate from cell to cell within a larger assembly of cells such as modules or battery packs and can cause rapid heat and toxic gas emissions. The resulting battery fire can spread to adjacent facilities, e.g. other cars in underground car parks or to a whole building in case of a large stationary energy storage.
For proof of fire protection requirements or to design suitable fire protection systems, Computational Fluid Dynamic (CFD) simulations are getting more and more important. The aim of CFD fire simulations is to predict the global hazards of a fire to its surroundings, that is mainly characterized by the release of heat and smoke and its spread in the fire environment. There are many numerical investigations of lithium-ion batteries in the literature. One class of models is used to simulate the charge and discharge process of lithium-ion batteries and to predict the temperature or voltage evolution inside the battery. On the other hand, there are models describing batteries under abuse conditions to predict the consequences of a thermal runaway event to the local environment, like the temperatures inside a battery or at the battery surface. Henriksen et al. use a generic battery gas mixture to simulate an explosion of vented gases from a Lithium Iron Phosphate battery and compare experimental results for the explosion pressure and the position of the flame front to the outcomes of a simulation with Xifoam. Larsson et al. used a combination of CFD simulations with FDS and thermal model with COMSOL to predict the temperature development of neighboring cells in a thermal runaway propagation. Truchot et al. use a design Heat Release Rate (HRR) curve for a battery based on experimental measurements to build up an overall HRR curve for a truck loaded with 100 lithium-ion batteries. This summed up HRR and corresponding smoke production curve is then used as an input for a simulation of a truck fire in a tunnel with Fire Dynamics Simulator (FDS). The pre-definition of the HRR curve is a frequently used method in fire engineering. It has the disadvantage, that the heat release cannot be influenced by physical processes, such as changed ventilation conditions or extinguishing measures. In this paper, a model is presented that determines the release of heat and gases based on the thermal runaway mechanisms of the battery, which can be used in CFD fire simulations with focus on prediction of fire hazards to nearby environment.
Optimizing the properties of next-generation high-temperature and corrosion-resistant alloys is rooted in balancing structure-property relationships and phase chemistry. Here, we implement a complementary approach based on transmission electron microscopy (TEM) and atom probe tomography (APT) to ascertain aspects of hierarchical phase separation behavior, by understanding the microstructural evolution and the three-dimensional (3D) nanochemistry of a single crystal Fe79.5Si15.5V5.0 (at%) alloy. A maze-like hierarchical microstructure forms, in which a complex network of metastable disordered α plates (A2 phase) emerges within ordered α1 precipitates (D03 phase). The supersaturation in α1 (D03) precipitates with Fe and V drives the formation of α (A2) plates. The morphology of α (A2) plates is discussed concerning crystal structure, lattice misfit, and elastic strain. Phase compositions and a ternary phase diagram aid the thermodynamic assessment of the hierarchical phase separation mechanism via the Gibbs energy of mixing. A perspective on the stabilization of hierarchical microstructures beyond Fe79.5Si15.5V5.0 is elaborated by comparing hierarchical alloys. We find that the ratio of elastic anisotropy (Zener ratio) serves as a predictor of the hierarchical particles’ morphology. We suggest that the strengthening effect of hierarchical microstructures can be harnessed by improving the temporal and thermal stability of hierarchical particles. This can be achieved through phase-targeted alloying aiming at the hierarchical particles phase by considering the constituents partitioning behavior. Beyond Fe79.5Si15.5V5.0, our results demonstrate a potential pathway for improving the properties of high-temperature structural materials.
Solid wastewater-based fertilizers were screened for per- and polyfluoroalkyl substances (PFAS) by the extractable organic fluorine (EOF) sum parameter method. The EOF values for ten sewage sludges from Germany and Switzerland range from 154 to 7209 mg kg−1. For thermal treated sewage sludge and struvite the EOF were lower with values up to 121 mg kg−1. Moreover, the application of PFAS targeted
and suspect screening analysis of selected sewage sludge samples showed that only a small part of the EOF sum parameter values can be explained by the usually screened legacy PFAS. The hitherto unknown part of EOF sum parameter contains also fluorinated pesticides, pharmaceutical and aromatic compounds. Because these partly fluorinated compounds can degrade to (ultra-)short PFAS in wastewater treatment plants they should be considered as significant sources of organic fluorine in the environment. The combined results of sum parameter analysis and suspect screening reveal the need to update current regulations, such as the German fertilizer ordinance, to focus not solely on a few selected PFAS such as perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) but
consider an additional sum parameter approach as a more holistic alternative. Moreover, diffusion gradient in thin-films (DGT) passive samplers were utilized as an alternative simplified extraction method for PFAS in solid wastewater-based fertilizers and subsequently quantified via combustion ion chromatography. However, the DGT method was less sensitive and only comparable to the EOF values
of the fertilizers in samples with >150 mg kg−1, because of different diffusion properties for various PFAS, but also kinetic exchange limitations.
Physical adsorption at cryogenic temperature (cryoadsorption) is a reversible mechanism that can reduce the pressure of conventional compressed gas storage systems. Metal–organic framework (MOF) materials are remarkable candidates due to the combination of high specific surface area and density which, in some cases, provide a high volumetric storage capacity. However, such extensive use of MOFs for this application requires the selection of affordable structures, easy to produce and made from feasible metallic and organic components. Herein, we introduce a MOF database detailing the crystallographic and porous properties of 3600 existing MOFs made from industrially relevant metals and their organic composition. The comparison of the available minimum costs of linkers allowed the creation of a database to select affordable structures with high potential for volumetric hydrogen storage by cryoadsorption, considering their composition based on individual or mixed building blocks. A user interface, available online, facilitates the selection of MOFs based on the properties or names of structures and linkers.
Episodic failures of ice-dammed lakes have produced some of the largest floods in history, with disastrous consequences for communities in high mountains. Yet, estimating changes in the activity of ice-dam failures through time remains controversial because of inconsistent regional flood databases. Here, by collating 1,569 ice-dam failures in six major mountain regions, we systematically assess trends in peak discharge, volume, annual timing and source elevation between 1900 and 2021. We show that extreme peak flows and volumes (10 per cent highest) have declined by about an order of magnitude over this period in five of the six regions, whereas median flood discharges have fallen less or have remained unchanged.
Ice-dam floods worldwide today originate at higher elevations and happen about six weeks earlier in the year than in 1900. Individual ice-dammed lakes with repeated outbursts show similar negative trends in magnitude and earlier occurrence, although with only moderate correlation to glacier thinning8. We anticipate that ice dams will continue to fail in the near future, even as glaciers thin and recede. Yet widespread deglaciation, projected for nearly all regions by the end of the twenty-first century9, may bring most outburst activity to a halt.
A new simplified and effective method has been formalised to estimate the Constant Amplitude Fatigue Limit (CAFL) of stress-relieved steel welded joints subjected to uniaxial push–pull loading and failing from the weld toe. Starting from the sharp V-notch assumption of the NSIF approach and the cyclic R-curve of the material in the heat affected zone, the proposed method identifies the CAFL as threshold level of the local stress field at the V-notched weld toe in the uncracked configuration. Such threshold stress field assures the crack arrest at the V-notched weld toe, according to the cyclic R-curve analysis. The method has been validated against experimental results and proved effective for a straightforward assessment of the CAFL of welded joints, as the stable crack propagation analysis of classical fracture mechanics approaches can be avoided.
The combination of acoustically levitated droplets, mid-IR laser evaporation, and subsequent post-ionization by secondary electrospray ionization was applied for monitoring the enzymatic digestion of various proteins. Acoustically levitated droplets are an ideal, wall-free model reactor, readily allowing compartmentalized microfluidic trypsin digestions. Time-resolved interrogation of the droplets yielded real-time information on the progress of the reaction and thus provided insights into reaction kinetics. After 30 min of digestion in the acoustic levitator, the obtained protein sequence coverages were identical to the reference overnight digestions. Importantly, our results clearly demonstrate that the applied experimental setup can be used for the real-time investigation of chemical reactions. Furthermore, the described methodology only uses a fraction of the typically applied amounts of solvent, analyte, and trypsin. Thus, the results exemplify the use of acoustic levitation as a green analytical chemistry alternative to the currently used batch reactions.
Agar gel pads have been used for electrochemical measurements for some time. For zinc in particular, a standard method for measuring the stability of the corrosion product layer is being established. The main interpretation factor is the corrosion product layer resistance RL, as it is easy to determine and interpret. A high corrosion product layer resistance indicates a high level of protection. However, it is not yet known how low the corrosion product layer resistance is for freshly produced zinc samples. As zinc is highly active, it reacts immediately with the environment to form a corrosion product layer, which affects the corrosion product layer resistance. The addition of zinc acetate to the agar gel pads prevents the formation of a surface layer and destroys existing ones.
This makes it possible to measure an almost corrosion product-free zinc surface. This is important in defining the range of corrosion product layer resistance for a protective surface.
Pseudomonas aeruginosa is an opportunistic pathogen of considerable medical importance, owing to its pronounced antibiotic tolerance and association with cystic fibrosis and other life-threatening diseases. The aim of this study was to highlight the genes responsible for P. aeruginosa biofilm tolerance to antibiotics and thereby identify potential new targets for the development of drugs against biofilm-related infections. By developing a novel screening approach and utilizing a public P. aeruginosa transposon insertion library, several biofilm-relevant genes were identified. The Pf phage gene (PA0720) and flagellin gene (fliC) conferred biofilm-specific tolerance to gentamicin. Compared with the reference biofilms, the biofilms formed by PA0720 and fliC mutants were completely eliminated with a 4-fold-lower gentamicin concentration. Furthermore, the mreC, pprB, coxC, and PA3785 genes were demonstrated to play major roles in enhancing biofilm tolerance to gentamicin. The analysis of biofilm-relevant genes performed in this study provides important novel insights into the understanding of P. aeruginosa antibiotic tolerance, which will facilitate the detection of antibiotic resistance and the development of antibiofilm strategies against P. aeruginosa.
The application and benefits of Semantic Web Technologies (SWT) for managing, sharing, and (re-)using of research data are demonstrated in implementations in the field of Materials Science and Engineering (MSE). However, a compilation and classification are needed to fully recognize the scattered published works with its unique added values. Here, the primary use of SWT at the interface with MSE is identified using specifically created categories. This overview highlights promising opportunities for the application of SWT to MSE, such as enhancing the quality of experimental processes, enriching data with contextual information in knowledge graphs, or using ontologies to perform specific queries on semantically structured data. While interdisciplinary work between the two fields is still in its early stages, a great need is identified to facilitate access for nonexperts and develop and provide user-friendly tools and workflows. The full potential of SWT can best be achieved in the long term by the broad acceptance and active participation of the MSE community. In perspective, these technological solutions will advance the field of MSE by making data FAIR. Data-driven approaches will benefit from these data structures and their connections to catalyze knowledge generation in MSE.
FAIR (findable, accessible, interoperable and reusable) data usage is one of the main principals that many of the research and funding organizations include in their strategic plans, which means that following the main principals of FAIR data is required in many research projects. The definition of data being FAIR is very general. When implementing that for a specific application or project or even setting a standardized procedure within a working group, a company or a research community, many challenges arise. In this contribution, an overview about our experience with different methods and tools is outlined.
We begin with a motivation on potential use cases for the application of FAIR data with increasing complexity starting from a reproducible research paper over collaborative projects with multiple participants such as Round-Robin tests up to data-based models within standardization codes, applications in machine learning or parameter estimation of physics-based simulation models.
In a second part, different options for structuring the data (including metadata schema) are discussed. The first one is the openBIS system, which is an open-source lab notebook and PostgreSQL based data management system. A second option is a semantic representation using RDF based on ontologies for the domain of interest.
In a third section, requirements for workflow tools to automate data processing are discussed and their integration into reproducible data analysis is presented with an outlook on required information to be stored as metadata in the database.
Finally, the presented procedures are exemplarily demonstrated for the calibration of a temperature dependent constitutive model for additively manufactured mortar. A metadata schema for a rheological measurement setup is derived and implemented in an openBIS database. After a short review of a potential numerical model predicting the structural build-up behavior, the automatic workflow to use the stored data for model parameter estimation is demonstrated.
The damage mechanisms of metallic components produced by process laser powder bed fusion differ significantly from those typically observed in conventionally manufactured variants of the same alloy. This is due to the unique microstructures of additively manufactured materials. Herein, the focus is on the study of the evolution of creep damage in stainless steel 316L specimens produced by laser powder bed fusion. X-ray computed tomography is used to unravel the influence of the process-specific microstructure from the influence of the initial void distribution on creep damage mechanisms. The void distribution of two specimens tested at 600 °C and 650 °C is analyzed before a creep test, after an interruption, and after fracture. The results indicate that the formation of damage is not connected to the initial void distribution. Instead, damage accumulation at grain boundaries resulting from intergranular cracking is observed.
Polyamide 4.6 (PA46) is a high-heat-resistant polymer, but it has no dripping resistance under fire. Three commercial grades of PA46 are investigated under UL 94 vertical fire test conditions. Their performances are discussed based on the materials’ structural, thermal, and rheological properties. PA46 presents flaming drops, whereas dripping is prevented in the flame-retarded PA46.
Friction-modified PA46 has increased flaming dripping. Temperature profiles of the specimens under fire and the temperature of the drops are measured by thermocouples. A UL 94 vertical test configuration consisting of two flame applications is designed to assess the quantitative dripping behavior of the set of materials by the particle finite element method (PFEM). Polymer properties (activation energy and Arrhenius coefficient of decomposition, char yield, density, effective heat of combustion, heat of decomposition, specific heat capacity, and thermal conductivity) in addition to rheological responses in high temperatures are estimated and measured as input parameters for the simulations. The dripping behavior obtained by simulated materials corresponds with the experimental results in terms of time and drop size. A consistent picture of the interplay of the different phenomena controlling dripping under fire appears to deliver a better understanding of the role of different materials’ properties
For a comprehensive safety assessment of stationary lithium-ion-battery applications, it is necessary to better understand the consequences of thermal runaway (TR). In this study, experimental tests comprising twelve TR experiments including four single-cell tests, two cell stack tests and six second-life module tests (2.65 kW h and 6.85 kW h) with an NMC-cathode under similar initial conditions were conducted. The temperature (direct at cells/modules and in near field), mass loss, cell/module voltage, and qualitative vent gas composition (Fourier transform infrared (FTIR) and diode laser spectroscopy (DLS) for HF) were measured. The results of the tests showed that the battery TR is accompanied by severe and in some cases violent chemical reactions. In most cases, TR was not accompanied by pregassing of the modules. Jet flames up to a length of 5 m and fragment throwing to distances to more than 30 m were detected. The TR of the tested modules was accompanied by significant mass loss of up to 82%. The maximum HF concentration measured was 76 ppm, whereby the measured HF concentrations in the module tests were not necessarily higher than that in the cell stack tests.
Subsequently, an explosion of the released vent gas occurred in one of the tests, resulting in the intensification of the negative consequences. According to the evaluation of the gas measurements with regard to toxicity base on the “Acute Exposure Guideline Levels” (AEGL), there is some concern with regards to CO, which may be equally as important to consider as the release of HF.
The cowpea chlorotic mottle virus (CCMV) is a plant virus explored as a nanotechnological platform. The robust self-assembly mechanism of its capsid protein allows for drug encapsulation and targeted delivery. Additionally, the capsid nanoparticle can be used as a programmable platform to display different molecular moieties. In view of future applications, efficient production and purification of plant viruses are key steps. In established protocols, the need for ultracentrifugation is a significant limitation due to cost, difficult scalability, and safety issues. In addition, the purity of the final virus isolate often remains unclear. Here, an advanced protocol for the purification of the CCMV from infected plant tissue was developed, focusing on efficiency, economy, and final purity. The protocol involves precipitation with PEG 8000, followed by affinity extraction using a novel peptide aptamer. The efficiency of the protocol was validated using size exclusion chromatography, MALDI-TOF mass spectrometry, reversed-phase HPLC, and sandwich immunoassay. Furthermore, it was demonstrated that the final eluate of the affinity column is of exceptional purity (98.4%) determined by HPLC and detection at 220 nm. The scale-up of our proposed method seems to be straightforward, which opens the way to the large-scale production of such nanomaterials. This highly improved protocol may facilitate the use and implementation of plant viruses as nanotechnological platforms for in vitro and in vivo applications.
It is shown that preconditioning of experimental X‐ray computed tomography (XCT) data is critical to achieve high‐precision segmentation scores. The challenging experimental XCT datasets and deep convolutional neural networks (DCNNs) are used that are trained with low‐resemblance synthetic XCT data. The material used is a 6‐phase Al–Si metal matrix composite‐reinforced with ceramic fibers and particles. To achieve generalization, in our past studies, specific data augmentation techniques were proposed for the synthetic XCT training data. In addition, two toolsets are devised: (1) special 3D DCNN architecture (3D Triple_UNet), slicing the experimental XCT data from multiple views (MultiView Forwarding), the i.S.Sy.Da.T.A. iterative segmentation algorithm, and (2) nonlocal means (NLM) conditioning (filtering) for the experimental XCT data. This results in good segmentation Dice scores across all phases compared to more standard approaches (i.e., standard UNet architecture, single view slicing, standard single training, and NLM conditioning). Herein, the NLM filter is replaced with the deep conditioning framework BAM SynthCOND introduced in a previous publication, which can be trained with synthetic XCT data. This leads to a significant segmentation precision increase for all phases. The proposed methods are potentially applicable to other materials and imaging techniques.
The greatest challenge when using deep convolutional neural networks (DCNNs) for automatic segmentation of microstructural X-ray computed tomography (XCT) data is the acquisition of sufficient and relevant data to train the working network. Traditionally, these have been attained by manually annotating a few slices for 2D DCNNs. However, complex multiphase microstructures would presumably be better segmented with 3D networks. However, manual segmentation labeling for 3D problems is prohibitive. In this work, we introduce a method for generating synthetic XCT data for a challenging six-phase Al–Si alloy composite reinforced with ceramic fibers and particles. Moreover, we propose certain data augmentations (brightness, contrast, noise, and blur), a special in-house designed deep convolutional neural network (Triple UNet), and a multi-view forwarding strategy to promote generalized learning from synthetic data and therefore achieve successful segmentations. We obtain an overall Dice score of 0.77. Lastly, we prove the detrimental effects of artifacts in the XCT data on achieving accurate segmentations when synthetic data are employed for training the DCNNs. The methods presented in this work are applicable to other materials and imaging techniques as well. Successful segmentation coupled with neural networks trained with synthetic data will accelerate scientific output.
We propose a novel iterative segmentation algorithm (i.S.Sy.Da.T.A: Iterative Segmentation Synthetic Data Training Algorithm) employing Deep Convolutional Neural Networks and synthetic training data for X-ray tomographic reconstructions of complex microstructures. In our method, we reinforce the synthetic training data with experimental XCT datasets that were automatically segmented in the previous iteration. This strategy produces better segmentations in successive iterations. We test our algorithm with experimental XCT re constructions of a 6-phase Al-Si Matrix Composite reinforced with ceramic fibers and particles. We perform the analysis in 3D with a special network architecture that demonstrates good generalization with synthetic training data. We show that our iterative algorithm returns better segmentations compared to the standard single training approach. More specifically, phases possessing similar attenuation coefficients can be better segmented: for Al2O3 fibers, SiC particles, and Intermetallics, we see an increase of the Dice score with respect to the classic approach: from 0.49 to 0.54, from 0.66 to 0.72, and from 0.55 to 0.66 respectively. Furthermore, the overall Dice score increases from 0.77 to 0.79. The methods presented in this work are also applicable to other materials and imaging techniques.
Regardless of the experimental care practiced in acquiring X-ray computed tomography (XCT) data, artifacts might still exist, such as noise and blur. This is typical for fast XCT data acquisitions (e.g., in-situ investigations), or low-dose XCT. Such artifacts can complicate subsequent analysis of the data. Digital filters can moderately cure extensive artifacts. The selection of filter type, intensity, and order of application is not always straight forward. To tackle these problems, a complete sequential multilevel, multi-scale framework: BAM SynthCOND, employing newly designed deep convolutional neural networks (DCNNs), was formulated. Although data conditioning with neural networks is not uncommon, the main complication is that completely artifact-free XCT data for training do not exist. Thus, training data were acquired from an in-house developed library (BAM SynthMAT) capable of generating synthetic XCT material microstructures. Some novel DCNN architectures were introduced (2D/3D ACEnet_Denoise, 2D/3D ACEnet_Deblur) along with the concept of Assertive Contrast Enhancement (ACE) training, which boosts the performance of neural networks trained with continuous loss functions. The proposed methodology accomplished very good generalization from low resemblance synthetic training data. Indeed, denoising, sharpening (deblurring), and even ring artifact removal performance were achieved on experimental post-CT scans of challenging multiphase Al-Si Metal Matrix Composite (MMC) microstructures. The conditioning efficiencies were: 92% for combined denoising/sharpening, 99% for standalone denoising, and 95% for standalone sharpening. The results proved to be independent of the artifact intensity. We believe that the novel concepts and methodology developed in this work can be directly applied on the CT projections prior to reconstruction, or easily be extended to other imaging techniques such as: Microscopy, Neutron Tomography, Ultrasonics, etc.
This data article introduces a dataset comprising 1630 alkali-activated concrete (AAC) mixes, compiled from 106 literature sources. The dataset underwent extensive curation to address feature redundancy, transcription errors, and duplicate data, yielding refined data ready for further data-driven science in the field of AAC, where this effort constitutes a novelty. The carbon footprint associated with each material used in the AAC mixes, as well as the corresponding CO2 footprint of every mix, were approximated using two published articles. Serving as a foundation for future expansions and rigorous data applications, this dataset enables the characterization of AAC properties through machine learning algorithms or as a benchmark for performance comparison among different formulations. In summary, the dataset provides a resource for researchers focusing on AAC and related materials and offers insights into the environmental benefits of substituting traditional Portland concrete with AAC.
Using digital twins for decision making is a very promising concept which combines simulation models with corresponding experimental sensor data in order to support maintenance decisions or to investigate the reliability. The quality of the prognosis strongly depends on both the data quality and the quality of the digital twin. The latter comprises both the modeling assumptions as well as the correct parameters of these models. This article discusses the challenges when applying this concept to realmeasurement data for a demonstrator bridge in the lab, including the data management, the iterative development of the simulation model as well as the identification/updating procedure using Bayesian inference with a potentially large number of parameters. The investigated scenarios include both the iterative identification of the structural model parameters as well as scenarios related to a damage identification. In addition, the article aims at providing all models and data in a reproducibleway such that other researcher can use this setup to validate their methodologies.
The development of hydrogen technologies entails high safety requirements in distribution and dispensing infrastructure. Therefore, it is necessary to pursue research on material compatibility in hydrogen, especially for critical parts with tribological issues.
The focus of this study is to evaluate the influence of hydrogen on a wider range of commercially available polymer materials. Thereby, the friction and wear behavior of different grades of TPE, POM, PA66, PA12, PPA, PEEK, PPS, PTFE, PAI, PI and PBI were investigated against a rotating steel disk (AISI 304). Filled and unfilled polymers from different suppliers were evaluated at room temperature in air, vacuum and hydrogen gas (H2) as well as in liquid hydrogen at - 253°C (LH2).
The sliding behavior of the polymer materials is discussed by means of surface analyses, whereby special attention is paid to the formation of a transfer film.
According to the results at ambient temperature, the effect of hydrogen environment on the tribological behavior of neat polymers may be related to lack of moisture, but also to saturated hydrocarbons in gaseous hydrogen. In liquid hydrogen, the best tribological performances were achieved with neat PA polymers as well as PPS and PI composites.
The X-ray intensities of the K-, L- and M-lines of copper, zirconium and tungsten have been measured with an energy-dispersive X-ray spectrometer of known efficiency as function of photon energy. X-ray production efficiencies were determined from the measured intensities for Kα- and L-series of Cu and Zr and for the L- and M-series of W. These data were compared to calculated X-ray production efficiencies based on the widely used matrix correction models of Pouchou and Pichoir (XPP) and Bastin (PROZA96).
Our results indicate that a replacement of the stopping power in the PROZA96 algorithm by expressions of Joy and Jablonski has only a minor influence on the calculated X-ray production efficiencies. In contrast, the modifications of the ionization cross-section show a stronger effect. We replaced the ionization cross-sections for K lines of the PROZA96 algorithm with different models.
The results for L- and M-Lines are different. For the L-lines of Cu the original XPP and PROZA96 models show the best agreement while using the Bote cross-sections result in an overestimation. For the Zr-L and W-L1, -L2, -L3 X-ray production efficiencies, the Bote cross-sections lead to a significant improvement compared to all other models. The original XPP model represents the best agreement for the M5 efficiencies but underestimates the M4 efficiencies.
There is no superior model or modification because the parameter sets in the models need to be aligned to each other. However, using the ionization cross-sections of Bote, which are based on quantum mechanical calculations, show promising results in many cases.
Elemental composition and thickness determination of thin films by electron probe microanalysis
(2023)
Electron probe microanalysis (EPMA) applies to solid samples of homogenous (bulk) chemical composition and can usually not be applied to structures which are inhomogeneous in the micrometer range such as thin film systems down to a few nm. However, in combination with the established thin film software Stratagem, the thickness as well as the elemental composition of thin films on a substrate can be determined. This has been recently successfully demonstrated for Fe-Ni on Si and Si-Ge on Al2O3 thin film systems. For both systems five samples of different elemental composition and a reference were produced and characterised by inductively coupled plasma mass spectrometry (ICP-MS), Rutherford backscattering (RBS), and transmission electron microscopy (TEM) as reference values. Last year, a new and open-source thin film evaluation programme called BadgerFilm has been released. It can also be used to determine thin film composition and thickness from intensity ratios of the unknown sample and standards (k-ratios). In this contribution, we reevaluated the data acquired for the Fe-Ni and Si-Ge systems using the BadgerFilm software package and compared the obtained elemental compositions and thickness values with the results of the Stratagem software and the reference methods. The conclusion is that the BadgerFilm software shows good agreement with the elemental composition and thickness calculated by Stratagem (mostly <2% for both composition and thickness) and with the reference values for two representative thin film systems (<1%–2% for composition and <10%–20% for thickness).
Tailoring negative pressure by crystal defects: Microcrack induced hydride formation in Al alloys
(2023)
Climate change motivates the search for non-carbon-emitting energy generation and storage solutions. Metal hydrides show promising characteristics for this purpose. They can be further stabilized by tailoring the negative pressure of microstructural and structural defects. Using systematic ab initio and atomistic simulations, we demonstrate that an enhancement in the formation of hydrides at the negatively pressurized tip region of the microcrack is feasible by increasing the mechanical tensile load on the specimen. The theoretical predictions have been used to reassess and interpret atom probe tomography experiments for a high-strength 7XXX-aluminium alloy that show a substantial enhancement of hydrogen concentration at structural defects near a stress-corrosion crack tip. These results contain important implications for enhancing the capability of metals as H-storage materials.
Quantitative 1H Nuclear Magnetic Resonance (qNMR) of Aromatic Amino Acids for Protein Quantification
(2023)
Hydrolysis of protein samples into amino acids facilitates the use of NMR spectroscopy for protein and peptide quantification. Different conditions have been tested for quantifying aromatic amino acids and proteins. The pH-dependent signal shifts in the aromatic region of amino acid samples were examined. A pH of 12 was found to minimize signal overlap of the four aromatic amino acids. Several aromatic compounds, such as terephthalic acid, sulfoisophthalic acid, and benzene tricarboxylic acid, were applied as internal standards. The quantification of amino acids from an amino acid standard was performed. Using the first two suggested internal standards, recovery was ~97% for histidine, phenylalanine, and tyrosine at a concentration of approximately 1 mM in solution. Acidic hydrolysis of a certified reference material (CRM) of bovine serum albumin (BSA) and subsequent quantification of Phe and Tyr yielded recoveries of 98% ± 2% and 88% ± 4%, respectively, at a protein concentration of 16 g/L or 250 µM.
AbstractThis work addresses the critical need for multifunctional materials and substrate‐independent high‐precision surface modification techniques that are essential for advancing microdevices and sensing elements. To overcome existing limitations, the versatility of mussel‐inspired materials (MIMs) is combined with state‐of‐the‐art multiphoton direct laser writing (DLW) microfabrication. In this way, 2D and 3D MIM microstructures of complex designs are demonstrated with sub‐micron to micron resolution and extensive post‐functionalization capabilities. This study includes polydopamine (PDA), mussel‐inspired linear, and dendritic polyglycerols (MI‐lPG and MI‐dPG), allowing their direct microstructure on the substrate of choice with the option to tailor the patterned topography and morphology in a controllable manner. The functionality potential of MIMs is demonstrated by successfully immobilizing and detecting single‐stranded DNA on MIM micropattern and nanoarray surfaces. In addition, easy modification of MIM microstructure with silver nanoparticles without the need of any reducing agent is shown. The methodology developed here enables the integration of MIMs in advanced applications where precise surface functionalization is essential.
Cardiac troponin I (cTnI) is a crucial biomarker for diagnosing cardiac vascular diseases, including acute myocardial infarction (AMI). This study presents a proof-of-concept chemiluminescence-based immunosensor for rapid and accurate measurement of cTnI, with the potential for online monitoring. The immunosensor incorporates a flow cell design and a sensitive complementary metal-oxide-semiconductor (CMOS) camera for optical readout. A microfluidic setup was established to enable selective and quasi-online determination of cTnI within ten minutes. The sensor was tested with recombinant cTnI in phosphate buffer, demonstrating measurements in the concentration range of 2–25 µg/L, with a limit of detection (LoD) of 0.6 µg/L (23 pmol/L) achieved using the optimized system. The immunosensor exhibited high selectivity, as no cross-reactivity was observed with other recombinant proteins such as cTnT and cTnC at a concentration of 16 µg/L. Measurements with diluted blood plasma and serum yielded an LoD of 60 µg/L (2.4 nmol/L) and 70 µg/L (2.9 nmol/L), respectively. This biosensor offers a promising approach for the rapid and sensitive detection of cTnI, contributing to the diagnosis and management of acute myocardial infarction and other cardiac vascular diseases.
Fused filament fabrication (FFF) is a material extrusion-based technique often used in desktop 3D printers. Polymeric filaments are melted and are extruded through a heated nozzle to form a 3D object in layers. The extruder temperature is therefore a key parameter for a successful print job but also one of the main emission driving factors as harmful pollutants (e.g., ultrafine particles) are formed by thermal polymer degradation. The awareness of potential health risks has increased the number of emission studies in the past years. However, studies usually refer their calculated emission data to the printer set extruder temperature for comparison purposes. In this study, we used a thermocouple and an infrared camera to measure the actual extruder temperature and found significant temperature deviations to the displayed set temperature among printer models. Our result shows that printing the same filament feedstocks with three different printer models and with identical printer set temperature resulted in a variation in particle emission of around two orders of magnitude. A temperature adjustment has reduced the variation to approx. one order of magnitude. Thus, it is necessary to refer the measured emission data to the actual extruder temperature as it poses a more accurate comparison parameter for evaluation of the indoor air quality in user scenarios or for health risk assessments.
One of the main challenges for the synthesis and application of the promising hard-magnetic compound CeFe11Ti is the formation of Laves phases that are detrimental for their thermodynamic stability and magnetic properties. In this paper, we present an ab initio based approach to modify the stability of these phases in the Ce-Fe-Ti system by additions of 3d and 4d elements. We combine highly accurate free-energy calculations with an efficient screening technique to determine the critical annealing temperature for the formation of Ce(Fe,X)11Ti. The central findings are the dominant role of the formation enthalpy at T = 0 K on chemical trends and the major relevance of partial chemical decompositions. Based on these insights, promising transition metals to promote the stability of the hard-magnetic phase, such as Zn and Tc, were predicted. The comparison with suction casting and reactive crucible melting experiments for Ce-Fe-Ti-X (X = Cu, Ga, Co, and Cr) highlights the relevance of additional phases and quaternary elements.
Stereolithography processes such as lithography-based ceramic manufacturing (LCM) are technologies that can produce centimeter-sized structures in a reasonable time frame. However, for some parts specifications, they lack resolution. Two-photon-polymerization (2PP) ensures the highest geometric accuracy in additive manufacturing so far. Nevertheless, building up parts in sizes as large as a few millimeters or even centimeters is a time-consuming process, which makes the production of 2PP printed parts very costly. Regarding feedstock specification, the requirements for 2PP are different to those for LCM, and generally, feedstocks are designed to meet requirements for only one of these manufacturing technologies. In an attempt to fabricate highly precise ceramic components of a rather large size, it is necessary to develop a feedstock that suits both light-based technologies, taking advantage of LCM’s higher productivity and 2PP’s accuracy. Hybridization should bring the desired precision to the region of interest on reasonably large parts without escalating printing time and costs. In this study, specimens gained from a transparent feedstock with yttria stabilized zirconia (YSZ) particles of 5 nm at 70 wt% were presented. The resin was originally designed to suit 2PP, while being also printable with LCM. This work demonstrates how hybrid parts can be sintered into full YSZ ceramics.
Inelastic incoherent neutron time-of-flight scattering was employed to investigate the low-frequency vibrational density of states (VDOSs) for a series of glassy Janus-poly(tricyclononenes), which consist of a rigid main chain and flexible alkyl side chains. Here, the length of the flexible side chains was systematically varied from propyl to octyl. Such materials have potential applications as active separation layers in gas separation membranes as a green future technology, especially for the separation of higher hydrocarbons. From the morphological point of view, the Janus polynorbornenes undergo a nanophase separation into alkyl side chain-rich nanodomains surrounded by a rigid polynorbornene matrix. Here, the influence of the nanophase-separated structure on the low-frequency VDOS is investigated from a fundamental point of view. The low-frequency VDOSs of these Janus polynorbornene show excess contributions to the Debye type VDOS known as the Boson peak (BP) for all side chain lengths. Due to the high incoherent scattering cross-section of hydrogen, most of the scattering comes from the alkyl side chain-rich domains.
Compared to conventional glass-forming materials, in the considered Janus polynorbornenes, the BP has a much lower intensity and its frequency position is shifted to higher values. These experimental results are discussed in terms of the nanophase-separated structure where the alkyl chain-rich domains were constrained by the surrounding matrix dominated by the rigid backbone. With increasing alkyl chain length, the size of the alkyl chain-rich domains increases. The frequency position of the BP shifts linearly to lower frequencies with the size of these nanodomains estimated from X-ray measurements. The obtained results support the sound wave interpretation to the BP
Irradiation assisted stress corrosion cracking (IASCC) is known to be a combination of applied stress, and a corrosive environment in irradiated materials, but an appropriate understanding of how each of these components affects cracking is not yet clear. In this work, we isolate the role of grain boundary (GB) oxidation in IASCC. For this purpose, solution-annealed 304L stainless steel irradiated in reactor to 5.4 or 69 dpa was studied using a miniaturized four-point bend technique. Two modes of bend tests were conducted; straining in simulated pressurized water reactor primary water (PW) at 320 ◦C in an incremental manner, and pre-oxidation in PW at 320 ◦C without application of stress followed by dynamic straining in purified Ar at the same temperature until crack initiation. Exposure of the 5.4 dpa sample for 210 h in high temperature water initiated cracks in Ar at 60% of the yield stress (0.6YS), whereas the companion sample of the same dose exposed for 1010 h cracked in Ar at 0.5YS. The long-term exposure in water led to GB oxidation that ultimately lowered the crack initiation stress. Dynamic straining in water resulted in larger crack lengths and greater crack depths indicating stress accelerated oxidation and cracking. Dislocation pile-ups at dislocation channel-grain boundary sites provide an amplification of the applied stress to a level consistent with the fracture stress of the grain boundary oxide, providing an explanation for IASCC that occurs at applied stresses well below the irradiated yield stress of the alloy. There was no evidence of cracking upon straining of an unoxidized 69 dpa sample in Ar to well above yield, confirming that the irradiated state is not inherently susceptible to intergranular (IG) cracking and that oxidized GBs are responsible for initiation of IG cracking.
Refractory chemically complex alloys with bcc-based microstructures show great potential for high-temperature applications but most of them exhibit limited room-temperature ductility, which remains a challenge. One such example is the AlMo0.5NbTa0.5TiZr alloy, mainly consisting of a nano-scaled structure with an ordered B2 matrix and a high-volume fraction of aligned cuboidal and coherently embedded A2 precipitates. This work aims to investigate how the cooling rate after hot isostatic pressing of the AlMo0.5NbTa0.5TiZr alloy affects its microstructure and its resulting hardness and fracture toughness at room temperature. A slow cooling rate of 5 °C/min leads to a coarse microstructure consisting of aligned slabs (mean A2 precipitate ≈ 25 nm) with a nanohardness of about 8 GPa. In contrast, after the fastest cooling rate (30 °C/min), the A2 precipitates become more cubic with an edge length of ≈ 16 nm, resulting in an increase in nanohardness by 10 %. The fracture toughness is roughly independent of the cooling rate and its mean value (≈ 4.2 MPa∙m1/2) resembles that of some B2 intermetallics and other A2/B2 alloys. As the lattice misfit between the A2 and B2 phases is known to play a key role in microstructure formation and evolution, its temperature dependence between 20 and 900 °C was investigated. These findings offer insights into the evolution of the microstructure and room-temperature mechanical properties of the AlMo0.5NbTa0.5TiZr alloy, which could help the development of advanced chemically complex alloys.
This contribution contains the raw data used to compare experimental results with thermodynamic calculations using the CALPHAD method, which is related to the research article “The AlMo0.5NbTa0.5TiZr refractory high entropy superalloy: experimental findings and comparison with calculations using the CALPHAD method” [1] , and therefore this article can be used as a basis for interpreting the data contained therein. The AlMo0.5NbTa0.5TiZr refractory superalloy was characterized in the cast and annealed condition (1400 °C for 24 h) in order to measure grain size and to identify and measure the size and area fraction of the phases present. The raw data of this article include X-ray diffraction (XRD) measurements, microstructural characterization by scanning and transmission electron microscopy (SEM and TEM), and elemental analysis by energy dispersive X-ray spectroscopy (EDX). XRD includes the determination of phases and the lattice parameters (A2, B2, and hexagonal structure). Microstructural analysis by scanning and transmission electron microscopy includes (1) identification of composition, size, and volume fraction of the present phases and (2) determination of grain size. Based on these experimental data, it is possible to identify similarities and discrepancies with the data calculated using the CALPHAD method for the alloy under study in Ref. [1] , which provides the basis for better and more efficient development of reliable databases.
In the processing of nanocomposites, high shear stresses at elevated tempera-tures orient two-dimensional nanoparticles like graphene. This orientationleads to anisotropic mechanical, thermal or barrier properties of the nanocom-posite. This anisotropy is addressed in this study by comparing graphene (few-layer graphene, FLG) with a nanoscaled carbon black (nCB) at a filler contentof 3 phr, by varying the vulcanization, and by comparing different FLG con-tents. Transmission electron microscopy gives insight into the qualitative ori-entation in the nanocomposite with FLG or nCB. The storage moduli paralleland normal to the orientation reveal the direction dependency of reinforce-ment through dynamic mechanical analysis (DMA). Dimensional swellingmeasurements show a restriction of the expansion parallel to the FLG orienta-tion, and an increased expansion normal to the orientation. The vulcanizationsystem and crosslinking determine the respective level of property values, andhigher crosslinking densities increase the anisotropy in DMA resulting invalues of up to 2.9 for the quantified anisotropy factor. With increasing FLGcontent, the anisotropy increases. A comparison of the results reveals swellingmeasurements as the most suitable method for the determination of anisot-ropy. Compared to recent literature, the presented processing induces higheranisotropy, leading to higher reinforcing effects in the direction of orientation
The addition of nanoparticles as reinforcing fillers in elastomers yields nanocomposites with unique property profiles, which opens the door for various new application fields. Major factors influencing the performance of nanocomposites are studied by varying the type and shape of nanoparticles and their dispersion in the natural rubber matrix. The industrial applicability of these nanocomposites is put into focus using two types of graphene and a nanoscale carbon black, all commercially available, and scalable processing techniques in the form of a highly filled masterbatch production via latex premixing by simple stirring or ultrasonically assisted dispersing with surfactant followed by conventional two-roll milling and hot pressing. Different processing and measurement methods reveal the potential for possible improvements: rheology, curing behavior, static and dynamic mechanical properties, swelling, and fire behavior. The aspect ratio of the nanoparticles and their interaction with the surrounding matrix prove to be crucial for the development of superior nanocomposites. An enhanced dispersing method enables the utilization of the improvement potential at low filler loadings (3 parts per hundred of rubber [phr]) and yields multifunctional rubber nanocomposites: two-dimensional layered particles (graphene) result in anisotropic material behavior with strong reinforcement in the in-plane direction (157% increase in the Young's modulus). The peak heat release rate in the cone calorimeter is reduced by 55% by incorporating 3 phr of few-layer graphene via an optimized dispersing process.
AISI 2205 duplex stainless steel is used in a variety of industries, including the chemical and petrochemical industries. This is due to its high tensile strength combined with good ductility and corrosion resistance. However, in laser beam welding, these properties are negatively afected by the high cooling rates typical of the welding process. The resulting higher ferrrite content in the weld metal than in the base material leads to a reduction in the ductility and corrosion resistance of the welded joint. To overcome this problem, in this study, thick plates were coated by direct energy deposition (DED) prior to laser beam welding, whereas a duplex powder mixture containing a higher nickel concentration was used as a coating material. To improve the weld quality for the proposed two-step process, a method of additional material deposition instead of conventional tack weld was investigated. The resulting welded joints showed a well-balanced austenite to ferrite ratio and their properties and microstructure were verifed by metallographic analysis, electron backscatter difraction and Charpy impact testing. Using the standard ASTM G48 test method, it was found that the corrosion resistance of the welds was improved by a factor of four in average compared to the conventionally welded joints. The resulting properties, such as good ductility and corrosion resistance, of the welds with pre-coated edges showed good agreement with those of the base metal and confrmed the proposed two-step process as a promising alternative to the conventional approaches for welding thick duplex stainless steel plates.
In this study, five laboratories, namely, BRML (Romania), TUBITAK UME (Turkey), IMBIH (Bosnia and Herzegovina), BAM (Germany), and DTI (Denmark), developed and validated analytical procedures by ICP-MS, ICP-OES, MWP-AES, WD-XRF, and ID-MS for the determination of inorganic
impurities in solid and liquid biofuels, established the budget of uncertainties, and developed the method for determining the amount of ash in the measurement range 0–1.2% with absolute repeatability less than 0.1% and absolute reproducibility of 0.2% (according to EN ISO 18122). In order to create homogeneous certified reference materials, improved methodologies for the measurement and characterization of solid and liquid biofuels were developed. Thus, information regarding the precision, accuracy, and bias of the method, and identifying the factors that intervened in the measurement of uncertainty were experimentally determined, supplementing the information from the existing standards in the field.
Almost all building materials in civil engineering have an open porosity and interact with or are affected by the environmental conditions. Structures might suffer from effects such as moisture adsorption, carbonation, corrosion, penetration of salt ions and chemical substances, etc. In the hygroscopic range, these processes are mostly driven by diffusion. Due to the confinement of small pores (less than1 µm), the Knudsen effect reduces the molecular diffusion. This reduction can become more significant in case of temporal changing pore systems because of physisorption of water vapor, carbonation, or chemisorption.
In this study, unstabilised earth blocks and earth masonry are investigated. In a first step, the pore size distribution of the blocks is measured and sorption isotherms are recorded in experiments. Besides the ordinary physisorption, the involved clay minerals undergo swelling or shrinking due to chemisorption. The following two effects must be considered: first, the reduction of the available pore space by the adsorbed water layer. For this, the Hillerborg sorption theory is used, which is a combination of the well-known Brunauer-Emmett-Teller sorption theory and the Kelvin equation. This allows the computation of adsorbed water layers even in curved pore geometries. Second, the variation of the initial pore size distribution due to chemisorption needs to be modelled. Based on these two models, the effective diffusion coefficient can be predicted. For validation, arrays of relative humidity sensors were embedded into a free-standing earth masonry wall. This monitoring was carried out over more than a year to have a broad variety of environmental conditions and was located in Berlin, Germany.
The prediction of the effective diffusion coefficient can also be transferred to other processes and allows the investigation of materials having temporarily changing pore systems. Examples are the carbonation of cementitious materials, alkali silica reaction, calcium leaching of long-lasting structures, etc. These effects are prominent in the meso-pore range and might significantly alter the effective diffusion coefficient.
Materials that support natural biodiversity on their surfaces can compensate for human activities that have a negative impact on nature and thus contribute to a carbon-neutral and nature-positive world. Specifically designing bioreceptive materials which favor the growth of biofilms on their surface is an approach complementing conventional, macroscopic green façades. But what exactly characterizes a bioreceptive substrate and how do biofilm and substrate interact? How and why does a spontaneous colonization and the formation of biofilms take place? What are biofilms and how can they be established in a laboratory setting? How can this existing knowledge be transferred to the artificial stone concrete so that this material can be tuned to increase (or decrease) its bioreceptivity?
This review paper aims at summarizing the existing state of knowledge on bioreceptive concrete and pointing out inconsistencies and contradictions which can only be removed by more interdisciplinary research in the field.
Advanced experimental and numerical approaches are being developed to
capture the localization of plasticity at the nanometer scale as a function of the multiscale and heterogeneous microstructure present in metallic materials.
These innovative approaches promise new avenues to understand microstructural effects on mechanical properties, accelerate alloy design, and enable more accurate mechanical property prediction. This article provides an overview of emerging approaches with a focus on the localization of plasticity by crystallographic slip. New insights into the mechanisms and mechanics of strain localization are addressed. The consequences of the localization of plasticity by deformation slip for mechanical properties of metallic materials are also detailed.
Ratiometric green–red fluorescent nanosensors for fluorometrically monitoring pH in the acidic range were designed from 80 nm-sized polystyrene (PS) and silica (SiO2) nanoparticles (NPs), red emissive reference dyes, and a green emissive naphthalimide pH probe, analytically and spectroscopically characterized, and compared regarding their sensing performance in aqueous dispersion and in cellular uptake studies. Preparation of these optical probes, which are excitable by 405 nm laser or LED light sources, involved the encapsulation of the pH-inert red-fuorescent dye Nile Red (NR) in the core of self-made carboxylated PSNPs by a simple swelling procedure and the fabrication of rhodamine B (RhB)-stained SiO2-NPs from a silane derivative of pH-insensitive RhB. Subsequently, the custom-made naphthalimide pH probe, that utilizes a protonation-controlled photoinduced electron transfer process, was covalently attached to the carboxylic acid groups at the surface of both types of NPs. Fluorescence microscopy studies with the molecular and nanoscale optical probes and A549 lung cancer cells confirmed the cellular uptake of all probes and their penetration into acidic cell compartments, i.e., the lysosomes, indicated by the switching ON of the green naphthalimide fluorescence. This underlines their suitability for intracellular pH sensing, with the SiO2-based nanosensor revealing the best performance regarding uptake speed and stability.
Despite their inherent instability, 4n π systems have recently received significant attention due to their unique optical and electronic properties. In dibenzopentalene (DBP), benzanellation stabilizes the highly antiaromatic pentalene core, without compromising its amphoteric redox behavior or small HOMO−LUMO energy gap. However, incorporating such molecules in organic devices as discrete small molecules or amorphous polymers can limit the performance (e.g., due to solubility in the battery electrolyte solution or low internal surface area). Covalent organic frameworks (COFs), on the contrary, are highly ordered, porous, and crystalline materials that can provide a platform to align molecules with specific properties in a well-defined, ordered environment. We synthesized the first antiaromatic framework materials and obtained a series of three highly crystalline and porous COFs based on DBP. Potential applications of such antiaromatic bulk materials were explored: COF films show a conductivity of 4 × 10−8 S cm−1 upon doping and exhibit photoconductivity upon irradiation with visible light. Application as positive electrode materials in Li-organic batteries demonstrates a significant enhancement of performance when the antiaromaticity of the DBP unit in the COF is exploited in its redox activity with a discharge capacity of 26 mA h g−1 at a potential of 3.9 V vs. Li/Li+ . This work showcases antiaromaticity as a new design principle for functional framework materials.
Covalent organic frameworks (COFs) are a prominent class of organic materials constructed from versatile building blocks via reversible reactions. The quality of imine-linked COFs can be improved by using amine monomers protected with benzophenone forming benzophenone imines. Here, we present a study on substituted benzophenones in COF synthesis via formal transimination. 12 para-substituted N-aryl benzophenone imines, with a range of electron-rich to electron-poor substituents, were prepared and their hydrolysis kinetics were studied spectroscopically. All substituted benzophenone imines can be employed in COF synthesis and lead to COFs with high crystallinity and high porosity. The substituents act innocent to COF formation as the substituted benzophenones are cleaved off. Imines can be tailored to their synthetic demands and utilized in COF formation. This concept can make access to previously unattainable, synthetically complex COF monomers feasible.
Safety characteristics are used to keep processes, including flammable gases, vapors, and combustible dusts, safe. In the standards for the determination of safety characteristics of gases and vapors, the induction spark is commonly used. However, classic transformers are hard to obtain, and replacement with new electronic transformers is not explicitly allowed in the standards. This article presents the investigation of five gases that are normally used to calibrate devices for the determination of safety characteristics, the maximum experimental safe gap (MESG), with an electronic transformer, and the values are compared to the ones that are obtained with the standard transformer. Additionally, calorimetric measurements on the net energy of both ignition sources were performed as well as open-circuit voltage measurements. It is concluded that the classic type of transformer can be replaced by the new type obtaining the same results for the MESG and introducing the same amount of energy into the system.
Safety characteristics are widely used in industrial processes to avoid explosive atmospheres (primary explosionprotection) or to mitigate the consequences of an explosion (constructive explosion protection). Several laboratory parameters influence the determined values when performing the test series such as the beginning pressure and the pre-ignition pressure rise, the ignition source, the ignition energy, the burning duration and volume or the concentration of the combustible substance.
In the different standards for the determination of safety characteristics of dusts there is no statement about the scattering or the deviation when parameters are chosen or occur on the borders of their allowed range. Thus, two laboratories might determine values that are hardly comparable for the same given substance.
This article summarizes some of the influential factors that cause a deviation and shows the inherent scattering of dust tests when all other parameters are kept constant. It also provides some advice how to minimize the deviation and the scattering with little effort.
Several standardized ignition sources are used to determine the safety characteristics of gases, vapours and dusts. Standards indicate the source of ignition but vary in specifying other features such as the burning duration, energy or the volume in which the energy is released. Since heat is not visible under normal conditions, a schlieren technique was used to visualize the entire igniting volume and not just the flames. This article focuses on the igniting volume, compares it among the four standardized ignition sources and displays its relationship to the size of the test vessel. Differences in the ignition behaviour of the ignition sources might lead to the determination of erroneous safety characteristics and with that to the unsafe operation of processes.