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Paper des Monats
- ja (71)
Advanced ceramics printed with photon-based additive manufacturing deals with anisotropic mechanical properties from the layer-by-layer manufacturing. Motivated by the success in using highly filled transparent slurries containing nanoparticles for powder-based two-photon-polymerization (2PP) for advanced ceramic printing, this works approach is the transfer to Xolography, a volumetric additive manufacturing technology based on linear two-photon excitation and without recoating steps. This paper reports the results of a preliminary investigation optimizing the photocurable slurry to the requirements of Xolography in terms of transparency, over a significantly larger mean free path, compared to 2PP. A feedstock filled with 70 % weight fraction of ceramic particles (∼30 vol%) exhibiting an exceptionally high degree of transparency in the relevant wavelength range of 400–800 nm was prepared from 5 nm zirconia nanoparticles. The high transparency of the photocurable slurry is attributed to the near-monomodal particle size distribution of the zirconia nanoparticles used.
AbstractTwo‐photon polymerization (2PP) additive manufacturing (AM) utilizes feedstocks of ceramic nanoparticles of a few nanometers in diameter, enabling the fabrication of highly accurate technical ceramic design with structural details as small as 500 nm. The performance of these materials is expected to differ from conventional AM ceramics, as nanoparticles and three‐dimensional printing at high resolution introduce new microstructural aspects. This study applies 2PP‐AM of yttria‐stabilized zirconia to investigate the mechanical response behavior under compressive load, probing the influence of smallest structural units induced by the line packing during the printing process, design of sintered microblocks, and sintering temperature and thereby microstructure. We find a dissipative mechanical response enhanced by sintering at lower temperatures than conventional. The pursued 2PP‐AM approach yields a microstructured material with an increased number of grain boundaries that proposedly play a major role in facilitating energy dissipation within the here printed ceramic material. This microplastic response is further triggered by the filigree structures induced by hollow line packing at the order of the critical defect size of ceramics. Together, these unique aspects made accessible by the 2PP‐AM approach contribute to a heterogeneous nano‐ and microstructure, and hint toward opportunities for tailoring the mechanical response in future ceramic applications.
A long-term study was conducted on double-lap spruce wood-concrete joints to investigate their shear strength and stiffness over a 12-month period. These joints were manufactured using both wet and dry processes, each incorporating two adhesive types for bonding the wood to the concrete: a brittle epoxy and a ductile polyurethane (PUR). The experimental design exposed the joints to three specific long-term environments: (1) outdoor exposure, (2) indoor conditions with applied load, and (3) outdoor conditions with applied load. The wood concrete joints exposed to outdoor conditions were subjected to destructive shear testing at intervals of 0 (serving as the reference sample), 2, 4, 6, and 12 months, respectively. For joints subjected to both indoor and outdoor conditions with shear loading, the shear deformation of joints was monitored continuously over the 12 months before performing the destructive tests. A gradual reduction in the shear stiffness and strength of dry joints (produced using the dry bond method) exposed to outdoor conditions was observed over a 12-month period, primarily due to bond failure at the concrete-adhesive interface. The wet joints exhibited no degradation in shear stiffness and strength across long-term conditions over the same period. The bond failure observed in dry joints was predominantly associated with stresses arising from dimensional changes in the wood. No degradation was found in the cross-linking density of the adhesive or in the concrete’s compressive stiffness and strength.
AbstractUnderstanding the origin of low thermal conductivities in ionic conductors is essential for improving their thermoelectric efficiency, although accompanying high ionic conduction may present challenges for maintaining thermoelectric device integrity. This study investigates the thermal and ionic transport in Cu7PSe6, aiming to elucidate their fundamental origins and correlation with the structural and dynamic properties. Through a comprehensive approach including various characterization techniques and computational analyses, it is demonstrated that the low thermal conductivity in Cu7PSe6 arises from structural complexity, variations in bond strengths, and high lattice anharmonicity, leading to pronounced diffuson transport of heat and fast ionic conduction. It is found that upon increasing the temperature, the ionic conductivity increases significantly in Cu7PSe6, whereas the thermal conductivity remains nearly constant, revealing no direct correlation between ionic and thermal transport. This absence of direct influence suggests innovative design strategies in thermoelectric applications to enhance stability by diminishing ionic conduction, while maintaining low thermal conductivity, thereby linking the domains of solid‐state ionics and thermoelectrics. Thus, this study attempts to clarify the fundamental principles governing thermal and ionic transport in Cu+‐superionic conductors, similar to recent findings in Ag+ argyrodites.
Mechanochemistry is drawing attention from the pharmaceutical industry given its potential for sustainable material synthesis and manufacture. Scaling mechanochemical processes to industrial level remains a challenge due to an incomplete understanding of their underlying mechanisms. We here show how time-resolved in situ powder X-ray diffraction data, coupled with analytical kinetic modelling, provides a powerful approach to gain mechanistic insight into mechanochemical reactions. By using the ibuprofen–nicotinamide co-crystal mechanosynthesis as a benchmark system, we investigate the behaviour of the solids involved and identify the factors that promote the reaction. As mechanochemical mechanisms become increasingly clear, it promises to become a breakthrough in the industrial preparation of advanced pharmaceuticals.
The ultrasonic echo technique is broadly applied in non‐destructive testing (NDT) of concrete structures involving tasks such as measuring thickness, determining geometry and locating built‐in elements. To address the challenge of enhancing ultrasonic imaging for complex concrete constructions, we adapted a seismic imaging algorithm – reverse time migration (RTM) – for NDT in civil engineering. Unlike the traditionally applied synthetic aperture focusing technique (SAFT), RTM takes into account the full wavefield including primary and reflected arrivals as well as multiples. This capability enables RTM to effectively handle all wave phenomena, unlimited by changes in velocity and reflector inclinations. This paper concentrates on applying and evaluating a two‐dimensional elastic RTM algorithm that specifically addresses horizontally polarized shear (SH) waves only, as these are predominantly used in ultrasonic NDT of concrete structures. The elastic SH RTM algorithm was deployed for imaging real ultrasonic echo SH‐wave data obtained at a concrete specimen exhibiting a complex back wall geometry and containing four tendon ducts. As these features are frequently encountered in practical NDT scenarios, their precise imaging holds significant importance. By applying the elastic SH RTM algorithm, we successfully reproduced nearly all reflectors within the concrete specimen. In particular, we were capable of accurately reconstructing all vertically oriented reflectors as well as the circular cross sections of three tendon ducts, which was not achievable with traditional SAFT imaging. These findings demonstrate that elastic SH RTM holds the ability to considerably improve the imaging of complex concrete geometries, marking a crucial advancement for accurate, high‐quality ultrasonic NDT in civil engineering.
Non‐targeted screenings (NTS) are essential tools in different fields, such as forensics, health and environmental sciences. NTSs often employ mass spectrometry (MS) methods due to their high throughput and sensitivity in comparison to, for example, nuclear magnetic resonance–based methods. As the identification of mass spectral signals, called annotation, is labour intensive, it has been used for developing supporting tools based on machine learning (ML). However, both the diversity of mass spectral signals and the sheer quantity of different ML tools developed for compound annotation present a challenge for researchers in maintaining a comprehensive overview of the field.In this work, we illustrate which ML‐based methods are available for compound annotation in non‐targeted MS experiments and provide a nuanced comparison of the ML models used in MS data analysis, unravelling their unique features and performance metrics. Through this overview we support researchers to judiciously apply these tools in their daily research. This review also offers a detailed exploration of methods and datasets to show gaps in current methods, and promising target areas, offering a starting point for developers intending to improve existing methodologies.
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.
A combination of neutron time-of-flight and neutron backscattering spectroscopy was used to investigate the molecular dynamics of Janus polynorbornenes (Janus poly(tricyclononenes)) on a microscopic level.
These Janus polynorbornenes, denoted as PTCNSiOR, have a semirigid backbone with −Si(OR)3 side groups attached to it. R represents the length of the alkyl side chain. Here side chain lengths of R = 3 (propyl) and R = 8 (octyl) were considered. It is worth mentioning that these polymers have some potential as active layers in gas separation membranes, especially for the separation of higher hydrocarbons. The combination of time-of-flight and backscattering will ensure a reasonably broad time window for analysis where the incoherent intermediate scattering function SInc(q,t) is considered. Previously, it was shown by X-ray investigations that the system undergoes a nanophase separation into alkyl side chain-rich domains surrounded by a backbone-rich matrix. For PTCNSiOPr (R = 3), the alkyl side-chain-rich domains are truly isolated in the backbone-rich matrix, whereas for PTCNSiOOc (R = 8) these domains percolate through the matrix. Further, it was also previously shown that the alkyl side-chain-rich domains undergo a glass transition. The advantage of neutron scattering experiments discussed here is that besides temporal also spatial information is obtained which will allow conclusions to be drawn about the type of molecular fluctuations. At the lowest measured temperature, the decay in Sinc(q,t) is due to the methyl group rotation. The methyl group dynamics is analyzed in terms of a modified jump-diffusion in a 3-fold potential and yields to a reasonable fraction of hydrogens which contribute to the methyl group rotation. At higher temperatures, the decay in SInc(q,t) is due to both the methyl group rotation and the segmental dynamics in the alkyl side-chain-rich domains. The segmental diffusion is modeled by a sublinear diffusion. For the analysis of the scattering function SInc(q,t) of PTCNSiOPr an elastic scattering due to the immobilized backbone-rich matrix must be taken into account. The analysis reveals that the segmental dynamics is confined by the finite size of alkyl chain-rich domains and that it is intrinsically heterogeneous in nature. Both effects are more pronounced for PTCNSiOPr in comparison to those of PTCNSiOOc.
Fenton-like processes using persulfate for oxidative water treatment and contaminant removal can be enhanced by the addition of redox-active biochar, which accelerates the reduction of Fe(III) to Fe(II) and increases the yield of reactive species that react with organic contaminants. However, available data on the formation of non-radical or radical species in the biochar/Fe(III)/persulfate system are inconsistent, which limits the evaluation of treatment efficiency and applicability in different water matrices. Based on competition kinetics calculations, we employed different scavengers and probe compounds to systematically evaluate the effect of chloride in presence of organic matter on the formation of major reactive species in the biochar/Fe(III)/persulfate system for the transformation of the model compound N,N‑diethyl-m-toluamide (DEET) at pH 2.5. We show that the transformation of methyl phenyl sulfoxide (PMSO) to methyl phenyl sulfone (PMSO2) cannot serve as a reliable indicator for Fe(IV), as previously suggested, because sulfate radicals also induce PMSO2 formation. Although the formation of Fe(IV) cannot be completely excluded, sulfate radicals were identified as the major reactive species in the biochar/Fe(III)/persulfate system in pure water. In the presence of dissolved organic matter, low chloride concentrations (0.1 mM) shifted the major reactive species likely to hydroxyl radicals. Higher chloride concentrations (1 mM), as present in a mining-impacted acidic surface water, resulted in the formation of another reactive species, possibly Cl2•−, and efficient DEET degradation. To tailor the application of this oxidation process, the water matrix must be considered as a decisive factor for reactive species formation and contaminant removal.
Group 1 metal molecular chemistry is dominated by a +1 oxidation state, while a 0 oxidation state is widespread in the metals. A more exotic, yet still available, oxidation state of group 1 metal is −1, i.e., alkalide. Reported as early as the 1970s, the alkalides appear in every modern inorganic chemistry textbook as an iconic chemical curiosity, yet their reactivity remains unexplored. This is due to their synthetic hurdles. In this work, we report the first facile synthesis of the archetypical alkalide complex, [Na+(2,2,2-cryptand)Na–], which allows us to unveil a versatile reactivity profile of this once exotic species.
Characteristics of environmental stress cracking of PE-HD induced by biodiesel and diesel fuels
(2024)
In the context of the increasing effect of carbon dioxide emissions on the global climate biodiesel produced from renewable sources has emerged as a promising contender replacing fossil fuels, especially in long-range transport vehicles, using existing engines and infrastructure.
High-density polyethylene is one of the prevailing materials for pipe and container applications for storage and transport of such fuels, both, from fossil and renewable resources. The contact with the respective fuels raises questions concerning material compatibility as biodiesel exhibits significant differences compared to conventional diesel fuel affecting its sorption and plasticization behavior in polyethylene. In this study, its behavior with respect to environmental stress cracking, considered one of the most frequent damage mechanisms leading to failure of polymer parts and packaging, was evaluated using the well-established Full Notch Creep Test. This
approach allows for a detailed fracture surface analysis using imaging techniques, such as optical and laser scanning microscopy, as well as infrared spectroscopy. Comparing the environmental stress cracking behavior in standard surfactant solutions with that in biodiesel and diesel, respective crack propagation rates, showing different levels of acceleration, were determined and details of the underlying mechanisms could be revealed.
Furthermore, the specific infrared absorption of the biodiesel’s ester functionality allows its semi-quantitative determination on the fracture surface of the tested specimens after failure. Thus, a preferred uptake of sorptive fluids in the fracture zone due to local morphological changes of the polyethylene could be directly evidenced by infrared spectroscopy.
Microalloying elements such as Nb and Ti are essential to increase the strength of quenched and tempered high-strength low alloy (HSLA) structural steels with nominal yield strength ≥ 690 MPa and their welded joints. Standards such as EN 10025–6 only specify limits or ranges for chemical composition, which leads to variations in specific compositions between steel manufacturers. These standards do not address the mechanical properties of the material, and even small variations in alloy content can significantly affect these properties. This makes it difficult to predict the weldability and integrity of welded joints, with potential problems such as softening or excessive hardening of the heat-affected zone (HAZ). To understand these metallurgical effects, previous studies have investigated different microalloying routes with varying Ti and Nb contents using test alloys. The high-strength quenched and tempered fine-grained structural steel S690QL is the basic grade regarding chemical composition and heat treatment. To evaluate weldability, three-layer welds were made using high-performance MAG welding. HAZ formation was investigated, and critical microstructural areas were identified, focusing on phase transformations during cooling and metallurgical precipitation behavior. Isothermal thermodynamic calculations for different precipitations were also carried out. Mechanical properties, especially Charpy notch impact toughness, were evaluated to understand the influence of different microalloys on the microstructure of the HAZ and mechanical properties.
Safety and reliability are the major challenges to face for the development and acceptance of hydrogen technology. It is therefore crucial to deeply study material compatibility, in particular for tribological components that are directly in contact with hydrogen. Some of the most critical parts are sealing materials that need increased safety requirements. In this study, the fretting behavior of several elastomer materials were evaluated against 316L stainless steel in an air and hydrogen environment up to 10 MPa. Several grades of cross-linked hydrogenated acrylonitrile butadiene (HNBR), acrylonitrile butadiene (NBR) and ethylene propylene diene monomer rubbers (EPDM) were investigated. Furthermore, aging experiments were conducted for 7 days under static contions in 100 MPa of hydrogen followed by rapid gas decompression. Fretting tests revealed that the wear of these compounds is significantly affected by the hydrogen environment compared to air, especially with NBR grades. After the aging experiment, the friction response of the HBNR grades is characterized by increased adhesion due to elastic deformation, leading to partial slip.
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.
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.
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.
Glassy solids evolve towards lower-energy structural states by physical aging. This can be characterized by structural relaxation times, the assessment of which is essential for understanding the glass’ time-dependent property changes. Conducted over short times, a continuous increase of relaxation times with time is seen, suggesting a time-dependent dissipative transport mechanism. By focusing on micro-structural rearrangements at the atomic-scale, we demonstrate the emergence of sub-diffusive anomalous transport and therefore temporal fractional diffusion in a metallic glass, which we track via coherent x-ray scattering conducted over more than 300,000 s. At the longest probed decorrelation times, a transition from classical stretched exponential to a power-law behavior occurs, which in concert with atomistic simulations reveals collective and intermittent atomic motion. Our observations give a physical basis for classical stretched exponential relaxation behavior, uncover a new power-law governed collective transport regime for metallic glasses at long and practically relevant time-scales, and demonstrate a rich and highly non-monotonous aging response in a glassy solid, thereby challenging the common framework of homogeneous aging and atomic scale diffusion.
The development of multi‐principal‐element alloys (MPEAs) with unique characteristics such as high work hardening capacity similar to well‐known alloy systems like Hadfield steel X120Mn12 (ASTM A128) is a promising approach. Hence, by exploiting the core effects of MPEAs, the application range of conventional alloy systems can be extended. In the present study, work‐hardening MPEAs based on the equimolar composition CoFeNi are developed. Mn and C are alloyed in the same ratio as for X120Mn12. The production route consists of cast manufacturing by an electric arc furnace and surface functionalization via mechanical finishing using ultrasonic‐assisted milling (USAM) to initiate work hardening. The microstructure evolution, the hardness as well as the resulting oscillating wear resistance are detected. A pronounced lattice strain and grain refinement due to the plastic deformation during the USAM is recorded for the MPEA CoFeNi‐Mn12C1.2. Consequently, hardness increases by ≈380 HV0.025 in combination with a higher oscillating wear resistance compared to the X120Mn12. This shows the promising approach for developing work‐hardening alloys based on novel alloy concepts such as MPEAs.
Machine learning in non-destructive testing (NDT) offers significant potential for efficient daily data analysis and uncovering previously unknown relationships in persistent problems. However, its successful application heavily depends on the availability of a diverse and well-labeled training dataset, which is often lacking, raising questions about the transferability of trained algorithms to new datasets. To examine this issue closely, the authors applied classifiers trained with laboratory Ground Penetrating Radar (GPR) data to categorize on-site moisture damage in layered building floors. The investigations were conducted at five different locations in Germany. For reference, cores were taken at each measurement point and labeled as (i) dry, (ii) with insulation damage, or (iii) with screed damage. Compared to the accuracies of 84 % to 90 % within the laboratory training data (504 B-Scans), the classifiers achieved a lower overall accuracy of 53 % for on-site data (72 B-Scans). This discrepancy is mainly attributable to a significantly higher dynamic of all signal features extracted from on-site measurements compared to laboratory training data. Nevertheless, this study highlights the promising sensitivity of GPR for identifying individual damage cases. In particular the results showing insulation damage, which cannot be detected by any other non-destructive method, revealed characteristic patterns. The accurate interpretation of such results still depends on trained personnel, whereby fully automated approaches would require a larger and diverse on-site data set. Until then, the findings of this work contribute to a more reliable analysis of moisture damage in building floors using GPR and offer practical insights into applying machine learning to non-destructive testing for civil engineering (NDT-CE).
Introduction
Glacier ice algae, mainly Ancylonema alaskanum and Ancylonema nordenskiöldi, bloom on Greenland Ice Sheet bare ice surfaces. They significantly decrease surface albedo due to their purple-brown pigmentation, thus increasing melt. Little is known about their metabolic adaptation and factors controlling algal growth dynamics and pigment formation. A challenge in obtaining such data is the necessity of melting samples, which delays preservation and introduces bias to metabolomic analysis. There is a need to evaluate the physiological response of algae to melting and establish consistent sample processing strategies for metabolomics of ice microbial communities.
Objectives
To address the impact of sample melting procedure on metabolic characterization and establish a processing and analytical workflow for endometabolic profiling of glacier ice algae.
Methods
We employed untargeted, high-resolution mass spectrometry and tested the effect of sample melt temperature (10, 15, 20 °C) and processing delay (up to 49 h) on the metabolome and lipidome, and complemented this approach with cell counts (FlowCam), photophysiological analysis (PAM) and diversity characterization.
Results and Conclusion
We putatively identified 804 metabolites, with glycerolipids, glycerophospholipids and fatty acyls being the most prominent superclasses ( 50% of identified metabolites). Among the polar metabolome, carbohydrates and amino acid-derivatives were the most abundant. We show that 8% of the metabolome is affected by melt duration, with a pronounced decrease in betaine membrane lipids and pigment precursors, and an increase in phospholipids. Controlled fast melting at 10 °C resulted in the highest consistency, and is our recommendation for future supraglacial metabolomics studies.
Viscous crack healing in soda–lime–magnesium–silicate–ZrO<sub>2</sub> glass matrix composites
(2024)
AbstractThe present study investigates the influence of the crystal volume content on viscous crack healing in glass ceramic glass sealants. To ensure constant microstructure during healing, soda–lime–magnesium silicate glass matrix composites with varied volume fractions of ZrO2 filler particles were used. Crack healing was studied on radial cracks induced by Vickers indentation, which were stepwise annealed to monitor the healing progress by confocal laser scanning microscopy. Confirming previous studies, healing of radial cracks in pure glass was found delayed by global flow phenomena like crack widening and crack edge and tip rounding to minimize the sample surface. With increasing ZrO2 filler content, these global flow phenomena were progressively inhibited whereas local flow phenomena like sharp crack tip healing could still occur. As a result, crack healing was even accelerated by filler particles up to a maximum filler content of 17 vol% whereas crack healing was fully suppressed only at 33 vol% filler content.
Gas Distribution Mapping (GDM) is a valuable tool for monitoring the distribution of gases in a wide range of applications, including environmental monitoring, emergency response, and industrial safety. While GDM is actively researched in the scope of gas-sensitive mobile robots (Mobile Robot Olfaction), there is a potential for broader applications utilizing sensor networks. This study aims to address the lack of deep learning approaches in GDM and explore their potential for improved mapping of gas distributions. In this paper, we introduce Gas Distribution Decoder (GDD), a learning-based GDM method. GDD is a deep neural network for spatial interpolation between sparsely distributed sensor measurements that was trained on an extensive data set of realistic-shaped synthetic gas plumes based on actual airflow measurements. As access to ground truth representations of gas distributions remains a challenge in GDM research, we make our data sets, along with our models, publicly available. We test and compare GDD with state-of-the-art models on synthetic and real-world data. Our findings demonstrate that GDD significantly outperforms existing models, demonstrating a 35% improvement in accuracy on synthetic data when measured using the Root Mean Squared Error over the entire distribution map. Notably, GDD appears to have superior capabilities in reconstructing the edges and characteristic shapes of gas plumes compared to traditional models. These potentials offer new possibilities for more accurate and efficient environmental monitoring, and we hope to inspire other researchers to explore learning-based GDM.
This work studies the influence of the adsorbed layer on the glass transition of thin films of polysulfone. Therefore, the growth kinetics of the irreversibly adsorbed layer of polysulfone on silicon substrates was first investigated using the solvent leaching approach, and the thickness of the remaining layer was measured with atomic force microscopy. Annealing conditions before leaching were varied in temperature and time (0–336 h). The growth kinetics showed three distinct regions: a pre-growth step where it was assumed that phenyl rings align parallel to the substrate at the shortest annealing times, a linear growth region, and a crossover from linear to logarithmic growth observed at higher temperatures for the longest annealing times. No signs of desorption were observed, pointing to the formation of a strongly adsorbed layer.
Second, the glass transition of thin polysulfone films was studied in dependence on the film thickness using spectroscopic ellipsometry. Three annealing conditions were compared: two with only a tightly bound layer formed in the linear growth regime and one with both tightly bound and loosely adsorbed layers formed in the logarithmic growth regime. The onset thickness and increase in the glass transition temperature increases with annealing time and temperature. These differences were attributed to the distinct conformations of the formed adsorbed layers.
Knufia petricola is a black fungus that colonizes sun-exposed surfaces as extreme and oligotrophic environments. As ecologically important heterotrophs and biofilm-formers on human-made surfaces, black fungi form one of the most resistant groups of biodeteriorating organisms. Due to its moderate growth rate in axenic culture and available protocols for its transformation and CRISPR/Cas9-mediated genome editing, K. petricola is used for studying the morpho-physiological adaptations shared by extremophilic and extremotolerant black fungi. In this study, the bacteria-derived tetracycline (TET)-dependent promoter (Tet-on) system was implemented to enable controllable gene expression in K. petricola. The functionality i.e., the dose-dependent inducibility of TET-regulated constructs was investigated by using GFP fluorescence, pigment synthesis(melanin and carotenoids) and restored uracil prototrophy as reporters. The newly generated cloning vectors containing the Tet-on construct, and the validated sites in the K. petricola genome for color-selectable or neutral insertion of expression constructs complete the reverse genetics toolbox. One or multiple genes can be expressed on demand from different genomic loci or from a single construct by using 2A self-cleaving peptides, e.g., for localizing proteins and protein complexes in the K. petricola cell or for using K. petricola as host for the expression of heterologous genes.
AbstractRecently, we have developed an algorithm to quantitatively evaluate the roughness of spherical microparticles using scanning electron microscopy (SEM) images. The algorithm calculates the root-mean-squared profile roughness (RMS-RQ) of a single particle by analyzing the particle’s boundary. The information extracted from a single SEM image yields however only two-dimensional (2D) profile roughness data from the horizontal plane of a particle. The present study offers a practical procedure and the necessary software tools to gain quasi three-dimensional (3D) information from 2D particle contours recorded at different particle inclinations by tilting the sample (stage). This new approach was tested on a set of polystyrene core-iron oxide shell-silica shell particles as few micrometer-sized beads with different (tailored) surface roughness, providing the proof of principle that validates the applicability of the proposed method. SEM images of these particles were analyzed by the latest version of the developed algorithm, which allows to determine the analysis of particles in terms of roughness both within a batch and across the batches as a routine quality control procedure. A separate set of particles has been analyzed by atomic force microscopy (AFM) as a powerful complementary surface analysis technique integrated into SEM, and the roughness results have been compared.
Alcohol-initiated polymerizations of glycolide (GL) catalyzed by tin(II) 2-ethylhexanoate (SnOct2) were carried out in bulk with variation of GA/In ratio, temperature and time. Due to a rather strong competition of cyclization polyglycolide (PGA) free of cycles were never obtained. When the cyclic catalysts 2,2-dibutal-2-stanna − 1,3-dithiolane (DSTL) or 2-stanna 1,3-dioxo-4,5,6,7 bibenzepane (SnBiph) were used in combination with 1,4-butanediol the influence of cyclization was even stronger. Furthermore, the degrees of polymerization were higher than the GA/alcohol ratio due to rapid polycondensation in the solid state. At 160 °C or below, the matrixassisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectra indicated separate crystallization of low molar mass cyclic and linear PGAs from the same reaction mixture (also observed for poly(L-lactide)s).
Pressure-sensitive adhesive tapes are used in a variety of applications such as construction, aircrafts, railway vehicles, and ships, where flame retardancy is essential. Especially in these applications, phosphorus-based flame retardants are often chosen over halogenated ones due to their advantages in terms of toxicity. Although there are pressure-sensitive adhesives with phosphorus flame retardants available on the market, their flame-retardant modes of action and mechanisms are not entirely understood. This research article provides fundamental pyrolysis research of three phosphorus-based flame retardants that exhibit different mechanisms in a pressuresensitive adhesive matrix. The flame-retardants modes of action and mechanisms of a 9,10-dihydro-9-oxa-10-phosphaphenanthrene-10-oxide (DOPO) derivate, an aryl phosphate, and a self-synthesized, covalently bonded DOPO derivate (copolymerized) are investigated. The blended DOPO derivate is volatilized at rather low temperatures while the covalently bonded DOPO derivate decomposes together with the polymer matrix at the same temperature. Both DOPO derivates release PO radicals which are known for their flame inhibition. The aryl phosphate decomposes at higher temperatures, releases small amounts of aryl phosphates into the gas phase, and acts predominantly the condensed phase. The aryl phosphate acts as precursor for phosphoric acid and improves the charring of the pressure sensitive adhesive matrix. All flame retardants enhance the flammability of the adhesives depending on their individual mode of action while the covalently bonded flame retardant additionally improves the mechanical properties at elevated temperatures making it a promising future technology for pressure-sensitive adhesives.
This work provides an investigation of the influence of low temperature heat treatments on the fatigue behavior of a PBF-LB AlSi10Mg alloy. Fatigue specimens are produced in form of round bars on a build platform preheated at 200 ◦C. The specimens have been tested in three different conditions: as-built, and after heat treatments at 265 ◦C for 1 h and 300 ◦C for 2 h. Prior to the fatigue testing, the defect distribution is analyzed by means of micro computed tomography. Subsequently, the peak over threshold method is successfully applied to provide a prediction of the size of killer defect. The defect population was of gas porosity type. No clear improvement of the fatigue performance is observed after the heat treatments. The fatigue strength predicted using fracture mechanics-based approaches is in good agreement with the experimental data. Among the studied approaches, short crack models provided the most conservative predictions.
This article presents a method to use the dispersive behavior of ultrasonic guided waves and neural networks to determine the isotropic elastic constants of plate-like structures through dispersion images. Therefore, two different architectures are compared: one using convolutions and transfer learning based on the EfficientNetB7 and a Vision Transformer-like approach. To accomplish this, simulated and measured dispersion images are generated, where the first is applied to design, train, and validate and the second to test the neural networks. During the training of the neural networks, distinct data augmentation layers are employed to introduce artifacts appearing in measurement data into the simulated data. The neural networks can extrapolate from simulated to measured data using these layers. The trained neural networks are assessed using dispersion images from seven known material samples. Multiple variations of the measured dispersion images are tested to guarantee the prediction stability. The study demonstrates that neural networks can learn to predict the isotropic elastic constants from measured dispersion images using only simulated dispersion images for training and validation without needing an initial guess or manual feature extraction, independent of the measurement setup. Furthermore, the suitability of the different architectures for generating information from dispersion images in general is discussed.
Most high capacity anode materials for lithium-ion batteries (LiB) require a carbonaceous matrix. In this context one promising material is reduced graphene oxide (rGO). Herein, we present the influence of different reduction degrees of rGO on its physico-chemical properties, such as crystallinity, specific surface area, electrical conductivity and electrochemical lithiation/delithiation behavior. It is found that a heat treatment under inert and reducing atmospheres increases the long-range order of rGO up to a temperature of 700 °C. At temperatures around 1000 °C, the crystallinity decreases. With decreasing oxygen content, a linear decrease in irreversible capacity during cycle 1 can be observed, along with a significant increase in electrical conductivity. This decrease in irreversible capacity can be observed despite an increase in specific surface area indicating the more significant influence of the oxygen content on the capacity loss. Consequently, the reversible capacity increases continuously up to a carbon content of 84.4 at% due to the thermal reduction. Contrary to expectations, the capacity decreases with further reduction. This can be explained by the loss of functional groups that will be lithiated reversibly, and a simultaneous reduction of long-range order, as concluded from dq/dU analysis in combination with XRD analysis.
AbstractRecent studies have hypothesized that the reinforcing effects of boehmite nanoparticles (BNPs) in polymer nanocomposites (PNCs) are partly related to the particles themselves and partly to the water released from the BNP during curing. In this work, PNCs made from dried BNP (dBNP) with concentrations up to 15 wt% are investigated to differentiate particle and water related effects. The observed trend of the storage modulus in dynamic mechanical thermal analysis measurements was found to be independent of the drying procedure. Stiffness maps from intermodulation atomic force microscopy showed that dBNP leads to a stiffening of the interphase surrounding the particles compared with the unaffected epoxy matrix, while a softer interphase was reported for PNCs with as received BNP. A slight decrease in the glass transition temperature was observed by broadband dielectric spectroscopy related to a lowered crosslink density due to the particles. A significantly higher decrease was reported for PNCs with BNP, attributed to water influencing the curing process. In conclusion, the stiffening of PNC with BNP is related to the particles themselves, while the release of water causes the formation of a soft interphase in the vicinity of the particles and a significant decrease in crosslink density.
Cryomyces antarcticus, a melanized cryptoendolithic fungus endemic to Antarctica, can tolerate environmental conditions as severe as those in space. Particularly, its ability to withstand ionizing radiation has been attributed to the presence of thick and highly melanized cell walls, which—according to a previous investigation—may contain both 1,8‐dihydroxynaphthalene (DHN) and L‐3,4 dihydroxyphenylalanine (L‐DOPA) melanin. The genes putatively involved in the synthesis of DHN melanin were identified in the genome of C. antarcticus. Most important is capks1 encoding a non‐reducing polyketide synthase (PKS) and being the ortholog of the functionally characterized kppks1 from the rock‐inhabiting fungus Knufia petricola. The co‐expression of CaPKS1 or KpPKS1 with a 4′‐phosphopantetheinyl transferase in Saccharomyces cerevisiae resulted in the formation of a yellowish pigment, suggesting that CaPKS1 is the enzyme providing the precursor for DHN melanin. To dissect the composition and function of the melanin layer in the outer cell wall of C. antarcticus, non‐melanized mutants were generated by CRISPR/Cas9‐mediated genome editing. Notwithstanding its slow growth (up to months), three independent non‐melanized Δcapks1 mutants were obtained. The mutants exhibited growth similar to the wild type and a light pinkish pigmentation, which is presumably due to carotenoids. Interestingly, visible light had an adverse effect on growth of both melanized wild‐type and non‐melanized Δcapks1 strains. Further evidence that light can pass the melanized cell walls derives from a mutant expressing a H2B‐GFP fusion protein, which can be detected by fluorescence microscopy. In conclusion, the study reports on the first genetic manipulation of C. antarcticus, resulting in non‐melanized mutants and demonstrating that the melanin is rather of the DHN type. These mutants will allow to elucidate the relevance of melanization for surviving extreme conditions found in the natural habitat as well as in space.
In this work, the thermoelectric material calcium cobaltite Ca3Co4O9 (CCO), a promising p-type conducting thermoelectric oxide with anisotropic properties, was processed by the powder aerosol deposition method (PAD) to form a dense ceramic CCO film with a thickness in the µm range. The prepared films were characterized regarding their microstructure and thermoelectric properties between room temperature and 900 °C. After heat treatment at 900 °C, the CCO PAD film in-plane shows excellent properties in terms of electrical conductivity (280 S/cm at 900 °C) and Seebeck coefficient (220 µV/K at 900 °C). The calculated power factor in-plane (ab) reaches with 1125 µW/(m K2) 40 % of the single crystal value, surpassing the known-properties of CCO bulk ceramics. Examination of the microstructure shows a strong fiber texture of the film as well as a strong coarsening of the grains during the first heat treatment up to 900 °C.
Development and fundamental understanding of precious-group-metal-free electrocatalysts is hampered by limitations in the quantification of the intrinsic activity of different catalytic sites and understanding the different reaction mechanisms. Comparing isomorphic nitrogen-doped carbons, Zn-N-Cs and Fe-N-Cs with the common tetrapyrrolic motif, a catalyst-independent outer-sphere rate-determining step in the alkaline oxygen reduction reaction is observed. Density functional theory (DFT) simulations on tetrapyrrolic model structures indicate the highest occupied molecular orbital (HOMO) level as a good descriptor for the catalytic activity. Contour plots suggest that the electron transfer occurs directly from the tetrapyrrolic coordination site, rather than from the metal center. Metal-free tetrapyrrolic N4 sites are discovered to be highly active oxygen reduction reaction (ORR) active sites in alkaline that reach turnover frequencies (TOF) of 0.33 and 1.84 s−1 at 0.80 and 0.75 VRHE in the order of magnitude of tetrapyrrolic Fe–N4 sites in the acidic ORR. While Zn-coordination lowers the HOMO level and therefore the catalytic activity, Fe-coordination lifts the HOMO level resulting in TOF values of 0.4 and 4 s−1 for tetrapyrrolic Fe–N4 sites at 0.90 and 0.85 VRHE, respectively. At higher mass activities, the peroxide reduction becomes rate-limiting, where highest peroxide production rates are observed for the nitrogen-doped carbon.
L-Lactide (LA) was polymerized with neat tin(II) 2-ethylhexanoate (SnOct2) in toluene at 115 °C at low concentration with variation of the LA/Cat ratio. Cyclic polylactides (cPLAs) with number average molecular weights (Mn) between 7 000 and 17 000 were obtained. MALDI-TOF mass spectrometry also revealed the formation of a few percent of linear chains. Crystalline cPLAs with Mn around 9 000 and 14 000 were annealed at 140 °C in the presence of ScOct2 or dibutyl-2-stanna-1,3-dithiolane (DSTL). Simultaneously, crystallites of extended linear chains and crystallites of extended cycles were formed regardless of the catalyst, indicating that transesterification reaction proceeded different for linear chains and for cycles, governed by thermodynamic control. The formation of extended chain crystallites with low dispersity indicates the existence of symproportionation of short and long chains. A complementary experiment was carried out with a PLA ethyl ester composed mainly of linear chains with a small fraction of cycles
This research was aimed at comparing the fire characteristics of different types of pepper in the context of explosion prevention. The following characteristics were studied: explosion pressure Pmax and Kst at selected concentrations, ignition temperature of the deposited dust layer from the hot surface, and minimum ignition energy. The comparison of the chemical properties of the used types of pepper was performed using TG/DSC. The results of the measurements suggest that different types of peppers exhibit different explosion characteristics. Each sample reached the maximum value of the explosion pressure and rate of pressure rise at different concentrations. The volume of the explosion chamber used also influenced the explosion characteristics. It is a consequence of the fact that the explosion characteristics strongly depend on the mechanism of action of a particular igniter. The minimum effect on the safety characteristics was observed when measuring the minimum ignition energy and the minimum ignition temperature of the dust layer from the hot surface. The results of the measurements suggest that different types of peppers exhibit different explosion characteristics. This information should then be considered in explosion prevention.
The Great Pacific Garbage Patch, a significant collection of plastic introduced by human activities, provides an ideal environment to study bacterial lifestyles on plastic substrates. We proposed that bacteria colonizing the floating plastic debris would develop strategies to deal with the ultravioletexposed substrate, such as the production of antioxidant pigments. We observed a variety of pigmentation in 67 strains that were directly cultivated from plastic pieces sampled from the Garbage Patch. The genomic analysis of four representative strains, each distinct in taxonomy, revealed multiple pathways for carotenoid production. These pathways include those that produce
less common carotenoids and a cluster of photosynthetic genes. This
cluster appears to originate from a potentially new species of the Rhodobacteraceae family. This represents the first report of an aerobic anoxygenic photoheterotrophic bacterium from plastic biofilms. Spectral analysis showed that the bacteria actively produce carotenoids, such as betacarotene and beta-cryptoxanthin, and bacteriochlorophyll a. Furthermore, we discovered that the genetic ability to synthesize carotenoids is more common in plastic biofilms than in the surrounding water communities. Our findings suggest that plastic biofilms could be an overlooked source of bacteria-produced carotenoids, including rare forms. It also suggests that photoreactive molecules might play a crucial role in bacterial biofilm communities in surface water.
The synergistic behavior of different silicon compounds is investigated in flame retardant biocomposites with aluminum trihydroxide (ATH) as the main flame retardant. The paper shows a new approach towards sustainable biocomposites through the implementation of thermoplastic starch (TPS), leather fibers from industrial waste streams, and non-hazardous flame retardants and synergists. In these multicomponent systems, the different components address different modes of action in the fire scenario. When ATH is partially substituted by glass frits or layered silicates, fire performance is enhanced without changing the total amount of filler in the polymer. In a biocomposite with 25 phr of fiber and 90 phr of ATH, substituting 5 phr of ATH for layered silicates increased the LOI from 31.5 vol % to 34.8 vol %, decreased the peak of heat release by 20%, and increased the UL 94 rating from V-1 to V-0.
The affinity constant, also known as the equilibrium constant, binding constant, equilibrium association constant, or the reciprocal value, the equilibrium dissociation constant (Kd), can be considered as one of the most important characteristics for any antibody–antigen pair. Many methods based on different technologies have been proposed and used to determine this value. However, since a very large number of publications and commercial datasheets do not include this information, significant obstacles in performing such measurements seem to exist. In other cases where such data are reported, the results have often proved to be unreliable. This situation may indicate that most of the technologies available today require a high level of expertise and effort that does not seem to be available in many laboratories. In this paper, we present a simple approach based on standard immunoassay technology that is easy and quick to perform. It relies on the effect that the molar IC50 approaches the Kd value in the case of infinitely small concentrations of the reagents. A two-dimensional dilution of the reagents leads to an asymptotic convergence to Kd. The approach has some similarity to the well-known checkerboard titration used for the optimization of immunoassays. A well-known antibody against the FLAG peptide, clone M2, was used as a model system and the results were compared with other methods. This approach could be used in any case where a competitive assay is available or can be developed. The determination of an affinity constant should belong to the crucial parameters in any quality control of antibody-related products and assays and should be mandatory in papers using immunochemical protocols.
Ceramic additive manufacturing (AM) requires a complex process chain with various post-processing steps that require expensive machines and special expertise. The key to further market penetration is AM that makes it possible to integrate into an already established ceramic process chain. Most successful AM technologies for ceramics are, however, based on processes that initially have been developed for polymeric materials. For ceramics AM, polymers or precursors are loaded with ceramic particles. This strategy facilitates the entry into AM, however the introduction of organic additives into the ceramic process chain represents a considerable technological challenge to ultimately obtain a ceramic component after additive shaping. In the present communication, two technologies based on ceramic suspensions will be introduced, the “layerwise slurry deposition” (LSD) and “laser induced slip casting” (LIS) technology. Both technologies take advantage of the high packing densities reached by conventional slip casting and moreover enable the processing of fines, even nanoparticles.
A key aspect in the development of multilayer inductors is the magnetic permeability of the ferrite layers. Here, the effects of different processing steps on the permeability of a NiCuZn ferrite is investigated. Dry pressed, tape cast, and co‐fired multilayer samples are analyzed. An automated data pipeline is applied to structure the acquired experimental data according to a domain ontology based on PMDco (Platform MaterialDigital core ontology). Example queries to the ontology show how the determined process‐property correlations are accessible to non‐experts and thus how suitable data for component design can be identified. It is demonstrated how the inductance of co‐fired multilayer inductors is reliably predicted by simulations if the appropriate input data corresponding to the manufacturing process is used.This article is protected by copyright. All rights reserved.
The classification of incineration bottom ash (IBA) as hazardous or non-hazardous according to ecotoxic hazard property HP14 is still under debate. In this context, only the compounds of Zn and Cu with the hazard statement code H410 are of relevance. With an approach based on the grouping of substances, it was shown that such substances are either readily water-soluble or slightly and sparingly soluble. The concentrations of readily soluble Cu and Zn compounds in IBA are far below the cut-off value of 0.1%. Slightly and sparingly soluble Zn and Cu compounds could be quantified in the first fraction of a four-step sequential extraction procedure. With the results from the complete sequence, the dimensionless synthesis toxicity index (STI) was calculated and was in the range of 494 to 1218 for the four investigated IBA samples. It was concluded that IBA can usually be classified as non-hazardous.
The Bundesanstalt für Materialforschung und -prüfung (BAM) collaborates with TNO to develop a software framework for automated calibration of structural models based on monitoring data. The ultimate goal is to include such models in the asset management process of engineering structures. As a basis for developing the framework, a multi-span road bridge consisting of ten simply supported steel box girders was selected as a test case. Our group measured output-only vibration data from one box girder under ambient conditions. From the data, we determined eigenfrequencies and mode shapes. In parallel, we developed a preliminary structural model of the box girder for the purpose of predicting its modal properties. In this contribution, we provide an overview of the measurement campaign, the operational modal analysis, the structural modeling and qualitatively compare the identified with the predicted modes. As an outlook, we discuss the further steps in the calibration process and future applications of the calibrated model.
Managing aging engineering structures requires damage identification, capacity reassessment, and prediction of remaining service life. Data from structural health monitoring (SHM) systems can be utilized to detect and characterize potential damage. However, environmental and operational variations impair the identification of damages from SHM data. Motivated by this, we introduce a Bayesian probabilistic framework for building models and identifying damage in monitored structures subject to environmental variability. The novelty of our work lies (a) in explicitly considering the effect of environmental influences and potential structural damages in the modeling to enable more accurate damage identification and (b) in proposing a methodological workflow for model‐based structural health monitoring that leverages model class selection for model building and damage identification. The framework is applied to a progressively damaged reinforced concrete beam subject to temperature variations in a climate chamber. Based on deflections and inclinations measured during diagnostic load tests of the undamaged structure, the most appropriate modeling approach for describing the temperature‐dependent behavior of the undamaged beam is identified. In the damaged state, damage is characterized based on the identified model parameters. The location and extent of the identified damage are consistent with the cracks observed in the laboratory. A numerical study with synthetic data is used to validate the parameter identification. The known true parameters lie within the 90% highest density intervals of the posterior distributions of the model parameters, suggesting that this approach is reliable for parameter identification. Our results indicate that the proposed framework can answer the question of damage identification under environmental variations. These findings show a way forward in integrating SHM data into the management of infrastructures.
This data article presents a set of primary, analyzed, and digitalized mechanical testing datasets for nine copper alloys. The mechanical testing methods including the Brinell and Vickers hardness, tensile, stress relaxation, and low-cycle fatigue (LCF) testing were performed according to the DIN/ISO standards. The obtained primary testing data (84 files) mainly contain the raw measured data along with the testing metadata of the processes, materials, and testing machines. Five secondary datasets were also provided for each testing method by collecting the main meta- and measurement data from the primary data and the outputs of data analyses. These datasets give materials scientists beneficial data for comparative material selection analyses by clarifying the wide range of mechanical properties of copper alloys, including Brinell and Vickers hardness, yield and tensile strengths, elongation, reduction of area, relaxed and residual stresses, and LCF fatigue life. Furthermore, both the primary and secondary datasets were digitalized by the approach introduced in the research article entitled “Toward a digital materials mechanical testing lab” [1]. The resulting open-linked data are the machine-processable semantic descriptions of data and their generation processes and can be easily queried by semantic searches to enable advanced data-driven materials research.
Nowadays geotechnical engineering firms have powerful software tools to extent their consult-ing business also into dynamic soil-structure interaction, which before has been restricted to a rather small community of specialized experts in this field, and they certainly do. This is par-ticularly true with respect to non-seismic sources, that is all kinds of human induced vibrations. Hence, there is a demand from clients as well as from contractors to have guidance on the re-quirements as well as the limits of numerical modelling of soil-structure interaction. From the literature as well as from relevant standards, recommendations for the numerical modelling of soil-structure interaction problems involving seismic actions are well known, e. g. ASCE/SEI 4-16. There are, however, some particularities when dealing with human-induced vibrations, which are absent in seismic analyses. For human-induced excitations very little specific guid-ance has been published in the past. A machine foundation on a homogeneous half space ex-cited by harmonic loads with excitation frequency between 4 Hz and 64 Hz has been ana-lysed by means of several commercially available software packages. Parametric studies have been performed to verify if recommendations for seismic soil-structure analyses are valid for non-seismic analyses as well. This paper provides details on the benchmark example and the most important conclusions from the undertaken parametric studies.
AbstractTwo‐photon polymerization (2PP) additive manufacturing (AM) utilizes feedstocks of ceramic nanoparticles of a few nanometers in diameter, enabling the fabrication of highly accurate technical ceramic design with structural details as small as 500 nm. The performance of these materials is expected to differ from conventional AM ceramics, as nanoparticles and three‐dimensional printing at high resolution introduce new microstructural aspects. This study applies 2PP‐AM of yttria‐stabilized zirconia to investigate the mechanical response behavior under compressive load, probing the influence of smallest structural units induced by the line packing during the printing process, design of sintered microblocks, and sintering temperature and thereby microstructure. We find a dissipative mechanical response enhanced by sintering at lower temperatures than conventional. The pursued 2PP‐AM approach yields a microstructured material with an increased number of grain boundaries that proposedly play a major role in facilitating energy dissipation within the here printed ceramic material. This microplastic response is further triggered by the filigree structures induced by hollow line packing at the order of the critical defect size of ceramics. Together, these unique aspects made accessible by the 2PP‐AM approach contribute to a heterogeneous nano‐ and microstructure, and hint toward opportunities for tailoring the mechanical response in future ceramic applications.