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Paper des Monats
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Microalloying elements such as Nb and Ti are essential to increase the strength of quenched and tempered high-strength low alloy (HSLA) structural steels with nominal yield strength ≥ 690 MPa and their welded joints. Standards such as EN 10025–6 only specify limits or ranges for chemical composition, which leads to variations in specific compositions between steel manufacturers. These standards do not address the mechanical properties of the material, and even small variations in alloy content can significantly affect these properties. This makes it difficult to predict the weldability and integrity of welded joints, with potential problems such as softening or excessive hardening of the heat-affected zone (HAZ). To understand these metallurgical effects, previous studies have investigated different microalloying routes with varying Ti and Nb contents using test alloys. The high-strength quenched and tempered fine-grained structural steel S690QL is the basic grade regarding chemical composition and heat treatment. To evaluate weldability, three-layer welds were made using high-performance MAG welding. HAZ formation was investigated, and critical microstructural areas were identified, focusing on phase transformations during cooling and metallurgical precipitation behavior. Isothermal thermodynamic calculations for different precipitations were also carried out. Mechanical properties, especially Charpy notch impact toughness, were evaluated to understand the influence of different microalloys on the microstructure of the HAZ and mechanical properties.
This work provides an investigation of the influence of low temperature heat treatments on the fatigue behavior of a PBF-LB AlSi10Mg alloy. Fatigue specimens are produced in form of round bars on a build platform preheated at 200 ◦C. The specimens have been tested in three different conditions: as-built, and after heat treatments at 265 ◦C for 1 h and 300 ◦C for 2 h. Prior to the fatigue testing, the defect distribution is analyzed by means of micro computed tomography. Subsequently, the peak over threshold method is successfully applied to provide a prediction of the size of killer defect. The defect population was of gas porosity type. No clear improvement of the fatigue performance is observed after the heat treatments. The fatigue strength predicted using fracture mechanics-based approaches is in good agreement with the experimental data. Among the studied approaches, short crack models provided the most conservative predictions.
Ni-Cu alloys are promising for application at temperatures between 400–900 °C and reducing atmospheres with high C-contents. Typically, under such conditions, metallic materials in contact with the C-rich atmosphere are degraded by a mechanism called metal dusting (MD). Ni-Cu-alloys do not form protective oxide scales, but their resistance is attributed to Cu, which catalytically inhibits the C-deposition on the surface. Adding other alloying elements, such as Mn or Fe, was found to enhance the MD attack of Ni-Cu alloys again. In this study, the effect of the Mn and Fe is divided into two affected areas: the surface and the bulk. The MD attack on binary Ni-Cu alloys, model alloys with Fe and Mn additions, and commercial Monel Alloy 400 is experimentally demonstrated. The surface electronic structure causing the adsorption and dissociation of C-containing molecules is investigated for model alloys. Analytical methods such as scanning electron microscopy combined with energy-dispersive X-ray spectroscopy, electron probe microanalysis combined with wavelength-dispersive X-ray spectroscopy, X-ray diffraction analysis, and near-edge X-ray absorption fine structure measurements were used. The results are correlated to CALPHAD calculations and atomistic simulations combining density functional theory calculations and machine learning. It is found that the Cu content plays a significant role in the surface reaction. The effect of Mn and Fe is mainly attributed to oxide formation. A mechanism explaining the enhanced attack by adding both Fe and Mn is proposed.
Iodine is an essential trace element in the human diet because it is involved in the synthesis of thyroid hormones. Iodine deficiency affects over 2.2 billion people worldwide, making it a significant challenge to find plant-based sources of iodine that meet the recommended daily intake of this trace element. In this study, cabbage plants were cultivated in a hydroponic system containing iodine at concentrations ranging from 0.01 to 1.0 mg/L in the form of potassium iodide or potassium iodate. During the experiments, plant physiological parameters, biomass production, and concentration changes of iodine and selected microelements in different plant parts were investigated. In addition, the oxidation state of the accumulated iodine in root samples was determined. Results showed that iodine addition had no effect on photosynthetic efficiency and chlorophyll content. Iodide treatment did not considerably stimulate biomass production but iodate treatment increased it at concentrations less than 0.5 mg/L. Increasing iodine concentrations in the nutrient solutions increased iodine content in all plant parts; however, the iodide treatment was 2–7 times more efficient than the iodate treatment. It was concluded, that iodide addition was more favourable on the target element accumulation, however, it should be highlighted that application of this chemical form in nutrient solution decreased the concetrations of selected micoelement concentration comparing with the control plants. It was established that iodate was reduced to iodide during its uptake in cabbage roots, which means that independently from the oxidation number of iodine (+ 5, − 1) applied in the nutrient solutions, the reduced form of target element was transported to the aerial and edible tissues.
The nature of the support can fundamentally affect the function of a heterogeneous catalyst. For the novel type of isolated metal atom catalysts, sometimes referred to as single‐atom catalysts, systematic correlations are still rare. Here, we report a general finding that Pd on nitride supports (non‐metal and metal nitride) features a higher oxidation state compared to that on oxide supports (non‐metal and metal oxide). Through thorough oxidation state investigations by X‐ray absorption spectroscopy (XAS), X‐ray photoelectron spectroscopy (XPS), CO‐DRIFTS, and density functional theory (DFT) coupled with Bader charge analysis, it is found that Pd atoms prefer to interact with surface hydroxyl group to form a Pd(OH)x species on oxide supports, while on nitride supports, Pd atoms incorporate into the surface structure in the form of Pd−N bonds. Moreover, a correlation was built between the formal oxidation state and computational Bader charge, based on the periodic trend in electronegativity.
Safety and reliability are the major challenges to face for the development and acceptance of hydrogen technology. It is therefore crucial to deeply study material compatibility, in particular for tribological components that are directly in contact with hydrogen. Some of the most critical parts are sealing materials that need increased safety requirements. In this study, the fretting behavior of several elastomer materials were evaluated against 316L stainless steel in an air and hydrogen environment up to 10 MPa. Several grades of cross-linked hydrogenated acrylonitrile butadiene (HNBR), acrylonitrile butadiene (NBR) and ethylene propylene diene monomer rubbers (EPDM) were investigated. Furthermore, aging experiments were conducted for 7 days under static contions in 100 MPa of hydrogen followed by rapid gas decompression. Fretting tests revealed that the wear of these compounds is significantly affected by the hydrogen environment compared to air, especially with NBR grades. After the aging experiment, the friction response of the HBNR grades is characterized by increased adhesion due to elastic deformation, leading to partial slip.
Viscous crack healing in soda–lime–magnesium–silicate–ZrO<sub>2</sub> glass matrix composites
(2024)
AbstractThe present study investigates the influence of the crystal volume content on viscous crack healing in glass ceramic glass sealants. To ensure constant microstructure during healing, soda–lime–magnesium silicate glass matrix composites with varied volume fractions of ZrO2 filler particles were used. Crack healing was studied on radial cracks induced by Vickers indentation, which were stepwise annealed to monitor the healing progress by confocal laser scanning microscopy. Confirming previous studies, healing of radial cracks in pure glass was found delayed by global flow phenomena like crack widening and crack edge and tip rounding to minimize the sample surface. With increasing ZrO2 filler content, these global flow phenomena were progressively inhibited whereas local flow phenomena like sharp crack tip healing could still occur. As a result, crack healing was even accelerated by filler particles up to a maximum filler content of 17 vol% whereas crack healing was fully suppressed only at 33 vol% filler content.
Glassy solids evolve towards lower-energy structural states by physical aging. This can be characterized by structural relaxation times, the assessment of which is essential for understanding the glass’ time-dependent property changes. Conducted over short times, a continuous increase of relaxation times with time is seen, suggesting a time-dependent dissipative transport mechanism. By focusing on micro-structural rearrangements at the atomic-scale, we demonstrate the emergence of sub-diffusive anomalous transport and therefore temporal fractional diffusion in a metallic glass, which we track via coherent x-ray scattering conducted over more than 300,000 s. At the longest probed decorrelation times, a transition from classical stretched exponential to a power-law behavior occurs, which in concert with atomistic simulations reveals collective and intermittent atomic motion. Our observations give a physical basis for classical stretched exponential relaxation behavior, uncover a new power-law governed collective transport regime for metallic glasses at long and practically relevant time-scales, and demonstrate a rich and highly non-monotonous aging response in a glassy solid, thereby challenging the common framework of homogeneous aging and atomic scale diffusion.
The development of multi‐principal‐element alloys (MPEAs) with unique characteristics such as high work hardening capacity similar to well‐known alloy systems like Hadfield steel X120Mn12 (ASTM A128) is a promising approach. Hence, by exploiting the core effects of MPEAs, the application range of conventional alloy systems can be extended. In the present study, work‐hardening MPEAs based on the equimolar composition CoFeNi are developed. Mn and C are alloyed in the same ratio as for X120Mn12. The production route consists of cast manufacturing by an electric arc furnace and surface functionalization via mechanical finishing using ultrasonic‐assisted milling (USAM) to initiate work hardening. The microstructure evolution, the hardness as well as the resulting oscillating wear resistance are detected. A pronounced lattice strain and grain refinement due to the plastic deformation during the USAM is recorded for the MPEA CoFeNi‐Mn12C1.2. Consequently, hardness increases by ≈380 HV0.025 in combination with a higher oscillating wear resistance compared to the X120Mn12. This shows the promising approach for developing work‐hardening alloys based on novel alloy concepts such as MPEAs.
Machine learning in non-destructive testing (NDT) offers significant potential for efficient daily data analysis and uncovering previously unknown relationships in persistent problems. However, its successful application heavily depends on the availability of a diverse and well-labeled training dataset, which is often lacking, raising questions about the transferability of trained algorithms to new datasets. To examine this issue closely, the authors applied classifiers trained with laboratory Ground Penetrating Radar (GPR) data to categorize on-site moisture damage in layered building floors. The investigations were conducted at five different locations in Germany. For reference, cores were taken at each measurement point and labeled as (i) dry, (ii) with insulation damage, or (iii) with screed damage. Compared to the accuracies of 84 % to 90 % within the laboratory training data (504 B-Scans), the classifiers achieved a lower overall accuracy of 53 % for on-site data (72 B-Scans). This discrepancy is mainly attributable to a significantly higher dynamic of all signal features extracted from on-site measurements compared to laboratory training data. Nevertheless, this study highlights the promising sensitivity of GPR for identifying individual damage cases. In particular the results showing insulation damage, which cannot be detected by any other non-destructive method, revealed characteristic patterns. The accurate interpretation of such results still depends on trained personnel, whereby fully automated approaches would require a larger and diverse on-site data set. Until then, the findings of this work contribute to a more reliable analysis of moisture damage in building floors using GPR and offer practical insights into applying machine learning to non-destructive testing for civil engineering (NDT-CE).
This article presents a method to use the dispersive behavior of ultrasonic guided waves and neural networks to determine the isotropic elastic constants of plate-like structures through dispersion images. Therefore, two different architectures are compared: one using convolutions and transfer learning based on the EfficientNetB7 and a Vision Transformer-like approach. To accomplish this, simulated and measured dispersion images are generated, where the first is applied to design, train, and validate and the second to test the neural networks. During the training of the neural networks, distinct data augmentation layers are employed to introduce artifacts appearing in measurement data into the simulated data. The neural networks can extrapolate from simulated to measured data using these layers. The trained neural networks are assessed using dispersion images from seven known material samples. Multiple variations of the measured dispersion images are tested to guarantee the prediction stability. The study demonstrates that neural networks can learn to predict the isotropic elastic constants from measured dispersion images using only simulated dispersion images for training and validation without needing an initial guess or manual feature extraction, independent of the measurement setup. Furthermore, the suitability of the different architectures for generating information from dispersion images in general is discussed.
This work studies the influence of the adsorbed layer on the glass transition of thin films of polysulfone. Therefore, the growth kinetics of the irreversibly adsorbed layer of polysulfone on silicon substrates was first investigated using the solvent leaching approach, and the thickness of the remaining layer was measured with atomic force microscopy. Annealing conditions before leaching were varied in temperature and time (0–336 h). The growth kinetics showed three distinct regions: a pre-growth step where it was assumed that phenyl rings align parallel to the substrate at the shortest annealing times, a linear growth region, and a crossover from linear to logarithmic growth observed at higher temperatures for the longest annealing times. No signs of desorption were observed, pointing to the formation of a strongly adsorbed layer.
Second, the glass transition of thin polysulfone films was studied in dependence on the film thickness using spectroscopic ellipsometry. Three annealing conditions were compared: two with only a tightly bound layer formed in the linear growth regime and one with both tightly bound and loosely adsorbed layers formed in the logarithmic growth regime. The onset thickness and increase in the glass transition temperature increases with annealing time and temperature. These differences were attributed to the distinct conformations of the formed adsorbed layers.
Pressure-sensitive adhesive tapes are used in a variety of applications such as construction, aircrafts, railway vehicles, and ships, where flame retardancy is essential. Especially in these applications, phosphorus-based flame retardants are often chosen over halogenated ones due to their advantages in terms of toxicity. Although there are pressure-sensitive adhesives with phosphorus flame retardants available on the market, their flame-retardant modes of action and mechanisms are not entirely understood. This research article provides fundamental pyrolysis research of three phosphorus-based flame retardants that exhibit different mechanisms in a pressuresensitive adhesive matrix. The flame-retardants modes of action and mechanisms of a 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) derivate, an aryl phosphate, and a self-synthesized, covalently bonded DOPO derivate (copolymerized) are investigated. The blended DOPO derivate is volatilized at rather low temperatures while the covalently bonded DOPO derivate decomposes together with the polymer matrix at the same temperature. Both DOPO derivates release PO radicals which are known for their flame inhibition. The aryl phosphate decomposes at higher temperatures, releases small amounts of aryl phosphates into the gas phase, and acts predominantly the condensed phase. The aryl phosphate acts as precursor for phosphoric acid and improves the charring of the pressure sensitive adhesive matrix. All flame retardants enhance the flammability of the adhesives depending on their individual mode of action while the covalently bonded flame retardant additionally improves the mechanical properties at elevated temperatures making it a promising future technology for pressure-sensitive adhesives.
Alcohol-initiated polymerizations of glycolide (GL) catalyzed by tin(II) 2-ethylhexanoate (SnOct2) were carried out in bulk with variation of GA/In ratio, temperature and time. Due to a rather strong competition of cyclization polyglycolide (PGA) free of cycles were never obtained. When the cyclic catalysts 2,2-dibutal-2-stanna − 1,3-dithiolane (DSTL) or 2-stanna 1,3-dioxo-4,5,6,7 bibenzepane (SnBiph) were used in combination with 1,4-butanediol the influence of cyclization was even stronger. Furthermore, the degrees of polymerization were higher than the GA/alcohol ratio due to rapid polycondensation in the solid state. At 160 °C or below, the matrixassisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectra indicated separate crystallization of low molar mass cyclic and linear PGAs from the same reaction mixture (also observed for poly(L-lactide)s).
In this study, we demonstrate the applicability of nitrogen microwave inductively coupled atmospheric pressure mass spectrometry (MICAP-MS) for Ca, Fe, and Se quantification in human serum using isotope dilution (ID) analysis. The matrix tolerance of MICAP-MS in Na matrix was investigated, uncovering that high Na levels can suppress the signal intensity. This suppression is likely due to the plasma loading and the space charge effect. Moreover, 40Ca and 44Ca isotopic fractionation was noted at elevated Na concentration. Nine certified serum samples were analyzed using both external calibration and ID analysis. Overestimation of Cr, Zn, As, and Se was found in the results of external calibration, which might be resulted from C-induced polyatomic interference and signal enhancement, respectively. Further investigations performed with methanol showed a similar enhancement effect for Zn, As, and Se, potentially supporting this assumption. The mass concentrations determined with ID analysis show metrological compatibility with the reference values, indicating that MICAP-MS combined with ID analysis can be a promising method for precise Ca, Fe, and Se determination. Moreover, this combination reduces the influences of matrix effects, broadening the applicability of MICAP-MS for samples with complex matrix.
A long-term study was conducted on double-lap spruce wood-concrete joints to investigate their shear strength and stiffness over a 12-month period. These joints were manufactured using both wet and dry processes, each incorporating two adhesive types for bonding the wood to the concrete: a brittle epoxy and a ductile polyurethane (PUR). The experimental design exposed the joints to three specific long-term environments: (1) outdoor exposure, (2) indoor conditions with applied load, and (3) outdoor conditions with applied load. The wood concrete joints exposed to outdoor conditions were subjected to destructive shear testing at intervals of 0 (serving as the reference sample), 2, 4, 6, and 12 months, respectively. For joints subjected to both indoor and outdoor conditions with shear loading, the shear deformation of joints was monitored continuously over the 12 months before performing the destructive tests. A gradual reduction in the shear stiffness and strength of dry joints (produced using the dry bond method) exposed to outdoor conditions was observed over a 12-month period, primarily due to bond failure at the concrete-adhesive interface. The wet joints exhibited no degradation in shear stiffness and strength across long-term conditions over the same period. The bond failure observed in dry joints was predominantly associated with stresses arising from dimensional changes in the wood. No degradation was found in the cross-linking density of the adhesive or in the concrete’s compressive stiffness and strength.
Introduction
Glacier ice algae, mainly Ancylonema alaskanum and Ancylonema nordenskiöldi, bloom on Greenland Ice Sheet bare ice surfaces. They significantly decrease surface albedo due to their purple-brown pigmentation, thus increasing melt. Little is known about their metabolic adaptation and factors controlling algal growth dynamics and pigment formation. A challenge in obtaining such data is the necessity of melting samples, which delays preservation and introduces bias to metabolomic analysis. There is a need to evaluate the physiological response of algae to melting and establish consistent sample processing strategies for metabolomics of ice microbial communities.
Objectives
To address the impact of sample melting procedure on metabolic characterization and establish a processing and analytical workflow for endometabolic profiling of glacier ice algae.
Methods
We employed untargeted, high-resolution mass spectrometry and tested the effect of sample melt temperature (10, 15, 20 °C) and processing delay (up to 49 h) on the metabolome and lipidome, and complemented this approach with cell counts (FlowCam), photophysiological analysis (PAM) and diversity characterization.
Results and Conclusion
We putatively identified 804 metabolites, with glycerolipids, glycerophospholipids and fatty acyls being the most prominent superclasses ( 50% of identified metabolites). Among the polar metabolome, carbohydrates and amino acid-derivatives were the most abundant. We show that 8% of the metabolome is affected by melt duration, with a pronounced decrease in betaine membrane lipids and pigment precursors, and an increase in phospholipids. Controlled fast melting at 10 °C resulted in the highest consistency, and is our recommendation for future supraglacial metabolomics studies.
Advanced ceramics printed with photon-based additive manufacturing deals with anisotropic mechanical properties from the layer-by-layer manufacturing. Motivated by the success in using highly filled transparent slurries containing nanoparticles for powder-based two-photon-polymerization (2PP) for advanced ceramic printing, this works approach is the transfer to Xolography, a volumetric additive manufacturing technology based on linear two-photon excitation and without recoating steps. This paper reports the results of a preliminary investigation optimizing the photocurable slurry to the requirements of Xolography in terms of transparency, over a significantly larger mean free path, compared to 2PP. A feedstock filled with 70 % weight fraction of ceramic particles (∼30 vol%) exhibiting an exceptionally high degree of transparency in the relevant wavelength range of 400–800 nm was prepared from 5 nm zirconia nanoparticles. The high transparency of the photocurable slurry is attributed to the near-monomodal particle size distribution of the zirconia nanoparticles used.
AbstractUnderstanding the origin of low thermal conductivities in ionic conductors is essential for improving their thermoelectric efficiency, although accompanying high ionic conduction may present challenges for maintaining thermoelectric device integrity. This study investigates the thermal and ionic transport in Cu7PSe6, aiming to elucidate their fundamental origins and correlation with the structural and dynamic properties. Through a comprehensive approach including various characterization techniques and computational analyses, it is demonstrated that the low thermal conductivity in Cu7PSe6 arises from structural complexity, variations in bond strengths, and high lattice anharmonicity, leading to pronounced diffuson transport of heat and fast ionic conduction. It is found that upon increasing the temperature, the ionic conductivity increases significantly in Cu7PSe6, whereas the thermal conductivity remains nearly constant, revealing no direct correlation between ionic and thermal transport. This absence of direct influence suggests innovative design strategies in thermoelectric applications to enhance stability by diminishing ionic conduction, while maintaining low thermal conductivity, thereby linking the domains of solid‐state ionics and thermoelectrics. Thus, this study attempts to clarify the fundamental principles governing thermal and ionic transport in Cu+‐superionic conductors, similar to recent findings in Ag+ argyrodites.
Mechanochemistry is drawing attention from the pharmaceutical industry given its potential for sustainable material synthesis and manufacture. Scaling mechanochemical processes to industrial level remains a challenge due to an incomplete understanding of their underlying mechanisms. We here show how time-resolved in situ powder X-ray diffraction data, coupled with analytical kinetic modelling, provides a powerful approach to gain mechanistic insight into mechanochemical reactions. By using the ibuprofen–nicotinamide co-crystal mechanosynthesis as a benchmark system, we investigate the behaviour of the solids involved and identify the factors that promote the reaction. As mechanochemical mechanisms become increasingly clear, it promises to become a breakthrough in the industrial preparation of advanced pharmaceuticals.
AbstractTwo‐photon polymerization (2PP) additive manufacturing (AM) utilizes feedstocks of ceramic nanoparticles of a few nanometers in diameter, enabling the fabrication of highly accurate technical ceramic design with structural details as small as 500 nm. The performance of these materials is expected to differ from conventional AM ceramics, as nanoparticles and three‐dimensional printing at high resolution introduce new microstructural aspects. This study applies 2PP‐AM of yttria‐stabilized zirconia to investigate the mechanical response behavior under compressive load, probing the influence of smallest structural units induced by the line packing during the printing process, design of sintered microblocks, and sintering temperature and thereby microstructure. We find a dissipative mechanical response enhanced by sintering at lower temperatures than conventional. The pursued 2PP‐AM approach yields a microstructured material with an increased number of grain boundaries that proposedly play a major role in facilitating energy dissipation within the here printed ceramic material. This microplastic response is further triggered by the filigree structures induced by hollow line packing at the order of the critical defect size of ceramics. Together, these unique aspects made accessible by the 2PP‐AM approach contribute to a heterogeneous nano‐ and microstructure, and hint toward opportunities for tailoring the mechanical response in future ceramic applications.
In this work, the thermoelectric material calcium cobaltite Ca3Co4O9 (CCO), a promising p-type conducting thermoelectric oxide with anisotropic properties, was processed by the powder aerosol deposition method (PAD) to form a dense ceramic CCO film with a thickness in the µm range. The prepared films were characterized regarding their microstructure and thermoelectric properties between room temperature and 900 °C. After heat treatment at 900 °C, the CCO PAD film in-plane shows excellent properties in terms of electrical conductivity (280 S/cm at 900 °C) and Seebeck coefficient (220 µV/K at 900 °C). The calculated power factor in-plane (ab) reaches with 1125 µW/(m K2) 40 % of the single crystal value, surpassing the known-properties of CCO bulk ceramics. Examination of the microstructure shows a strong fiber texture of the film as well as a strong coarsening of the grains during the first heat treatment up to 900 °C.
A widespread recovery of waste heat requires a cost‐effective production of thermoelectric generators. Thermoelectric oxides are predestined for use at high temperatures. For manufacturing reasons, a multilayer generator design will be easily scalable and cost‐effective. To evaluate the potential of ceramic multilayer technology for that purpose, a multilayer of the promising thermoelectric oxides calcium cobaltite (Ca3Co4O9), calcium manganate (CMO, CaMnO3), and glass–ceramic insulation layers is fabricated. Cracks and reaction layers at the interfaces are observed in the microstructure. The compositions of these reaction layers are identified by energy‐dispersive X‐ray spectroscopy and X‐ray diffraction. Mechanical and thermal properties of all layers are compiled from literature or determined by purposeful sample preparation and testing. Based on this data set, the internal stresses in the multilayer after co‐firing are calculated numerically. It is shown that tensile stresses in the range of 50 MPa occur in the CMO layers. The reaction layers have only a minor influence on the level of these residual stresses. Herein, it is proven that the material system is basically suitable for multilayer generator production, but that the co‐firing process and the layer structure must be adapted to improve densification and reduce the tensile stresses in the CMO.
Modern dry pressing of ceramic powders using spray‐dried granulates cannot avoid the occurrence of defects related to persisting inter‐ and intra‐granulate interstitial voids. These constitute the parent defect size population limiting the application of polycrystalline ceramics in high‐stress conditions. The mitigation of such defects could widen the range of application in technical and biomedical engineering, reduce the safety range for design, and extend the lifetime of components. Herein, the Weibull size‐effect on strength in size‐partitioned Yttria‐stabilized zirconias (YSZ) feedstocks is used to explore the viability of changing the density distribution of granulate sizes as an effective strategy to obtain a denser particle packing that could reduce the size distribution of strength‐limiting pressing defects. In a direct assessment of critical defect size using multiscale strength testing with a dataset of ≈1300 values, the success of such an approach in increasing the strength reliability for small volume components is demonstrated, along with its ultimate failure in altering the defect size distribution in sintered YSZ ceramics across several length scales. Finally, it is shown that granule morphology (spherical or dimpled) fails to affect the defect density and size distribution in YSZ ceramics.
Automated computational workflows are a powerful concept that can improve the usability and reproducibility of simulation and data processing approaches. Although used very successfully in bioinformatics, workflow environments in materials science are currently commonly applied in the field of atomistic simulations. This work showcases the integration of a discrete element method (DEM) simulation of powder pressing in the convenient SimStack workflow environment. For this purpose, a Workflow active Node (WaNo) was developed to generate input scripts for the DEM solver using LIGGGHTS Open Source Discrete Element Method Particle Simulation code. Combining different WaNos in the SimStack framework makes it possible to build workflows and loop over different simulation or evaluation conditions. The functionality of the workflows is explained, and the added user value is discussed. The procedure presented here is an example and template for many other simulation methods and issues in materials science and engineering.
A key aspect in the development of multilayer inductors is the magnetic permeability of the ferrite layers. Here, the effects of different processing steps on the permeability of a NiCuZn ferrite is investigated. Dry pressed, tape cast, and co‐fired multilayer samples are analyzed. An automated data pipeline is applied to structure the acquired experimental data according to a domain ontology based on PMDco (Platform MaterialDigital core ontology). Example queries to the ontology show how the determined process‐property correlations are accessible to non‐experts and thus how suitable data for component design can be identified. It is demonstrated how the inductance of co‐fired multilayer inductors is reliably predicted by simulations if the appropriate input data corresponding to the manufacturing process is used.This article is protected by copyright. All rights reserved.
The gravimetric isotope mixture method is the primary method to determine absolute isotope ratios. This method, however, depends on the existence of suitable spike materials and knowledge of their purities. Determining the purity of the spikes can be tedious and labour-intensive. In this publication, an advancement of the gravimetric isotope mixture method, rendering the determination of the purity of the spike materials unnecessary, is presented. The advancement combines mass spectrometry and ion chromatography leading to an approach being independent of the purity of the spike materials. In the manuscript the mathematical background and the basic idea of the novel approach are described using a two-isotope system like copper or lithium.
Glycolide was polymerized in bulk by means of four different ROPPOC catalysts: tin(II) 2-ethylhexanoate (SnOct2), dibutyltin bis(pentafluoro-phenoxide) (BuSnOPF),zinc biscaproate (ZnCap), and zinc bis(pentafluoro-phenyl sulfide) (ZnSPF). The temperature was varied between 110 and 180°C and the time between 3 h and 7 days. For the few polyglycolides (PGAs) that were soluble extremely high molecular masses were obtained. The MALDI TOF mass spectra had all a low signal-to-noise ration and displayed the peaks of cyclic PGAs with a“saw-tooth pattern ”indicating formation of extended-ring crystallites in the mass range below m/z 2500. The shape of DSC curves varied considerably with catalyst and reaction conditions, whereas the long-distance values measured by SAXS were small and varied little with the polymeriza-tion conditions.
We report an analytical methodology for the quantification of sulfur in biological molecules via a speciesunspecific postcolumn isotope dilution (online ID) approach using capillary electrophoresis (CE) coupled online with inductively coupled plasma−mass spectrometry (online ID CE/ICP−MS).
The method was optimized using a mixture of standard compounds including sulfate, methionine, cysteine, cystine, and albumin, yielding compound recoveries between 98 and 105%. The quantity of sulfur is further converted to the quantity of the compounds owing to the prior knowledge of the sulfur content in the molecules. The limit of detection and limit of quantification of sulfur in the compounds were 1.3−2.6 and 4.1−8.4 mg L−1, respectively, with a correlation coefficient of 0.99 within the concentration range of sulfur of 5−100 mg L−1. The capability of the method was extended to quantify albumin in its native matrix (i.e., in serum) using experimentally prepared serum spiked with a pure albumin standard for validation. The relative expanded uncertainty of the method for the quantification of albumin was 6.7% (k = 2). Finally, we tested the applicability of the method on real samples by the analysis of albumin in bovine and human sera. For automated data assessment, a software application (IsoCor) which was developed by us in a previous work was developed further for handling of online ID data. The method has several improvements compared to previously published setups: (i) reduced adsorption of proteins onto the capillary wall owing to a special capillary-coating procedure, (ii) baseline separation of the compounds in less than 30 min via CE, (iii) quantification of several sulfur species within one run by means of the online setup, (iv) SI traceability of the quantification results through online ID, and (v) facilitated data processing of the transient signals using the IsoCor application. Our method can be used as an accurate approach for quantification of proteins and other biological molecules via sulfur analysis in complex matrices for various fields, such as environmental, biological, and pharmaceutical studies as well as clinical diagnosis.
Sulfur is an essential element in living organisms, where it plays important roles in various biological processes, such as protein synthesis, enzyme activity, and antioxidant defense. However, the biological effects of different sulfur species can vary widely, and imbalances in sulfur speciation have been observed in a range of diseases, including cancer, Alzheimer’s disease, and diabetes.1−3 The accurate quantification of sulfur and its species in biological samples requires sensitive and selective analytical techniques. In recent years, separation techniques coupled online with inductively coupled plasma−mass spectrometry (ICP−MS) have emerged as powerful online analytical tools complementary to molecular spectrometric methods for speciation analysis of biological compounds.
External calibration4−9 and isotope dilution (ID)10−15 are common calibration approaches applied for online quantification of sulfur species in complex samples. The ID analysis is advantageous over.