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Paper des Monats
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Additive manufacturing of concrete structures is a novel and emerging technology. Freecontouring in civil engineering, which allows for entirely new designs, is a significant advantage. Inthe future, lower construction costs are expected with increased construction speeds and decreasingrequired materials and workers. However, architects and civil engineers rely on a certain quality ofexecution to fulfil construction standards. Although several techniques and approaches demonstratethe advantages, quality control during printing is highly challenging and rarely applied. Due to thecontinuous mixing process commonly used in 3D concrete printing, it is impossible to exclude varia-tions in the dry mixture or water content, and a test sample cannot be taken as a representative samplefor the whole structure. Although mortar properties vary only locally, a defect in one layer duringprinting could affect the entire integrity of the whole structure . Therefore, real-time process monitor-ing is required to record and document the printing process.At the Bundesanstalt für Materialforschung und -prüfung (BAM) a new test rig for the additive man-ufacturing of concrete is built. The primary purpose is measuring and monitoring the properties of amortar during the printing process.The following study investigates an approach for calculating yield stress and plastic viscosity based onexperimentally recorded pressure data. The calculations assume that fresh mortar behaves as a Bing-ham fluid and that the Buckingham-Reiner-equation is applicable. A test setup consisting of rigid pipeswith integrated pressure sensors at different positions is utilized.Monitoring the printing process with different sensors is crucial for the quality control of an ongoingprocess.
Homochirality is an obvious feature of life on Earth. On the other hand, extraterrestrial samples contain largely racemic compounds. The same is true for any common organic synthesis. Therefore, it has been a perplexing puzzle for decades how these racemates could have formed enantiomerically enriched fractions as a basis for the origin of homochiral life forms. Numerous hypotheses have been put forward as to how preferentially homochiral molecules could have formed and accumulated on Earth. In this article, it is shown that homochirality of the abiotic organic pool at the time of formation of the first self-replicating molecules is not necessary and not even probable. It is proposed to abandon the notion of a molecular ensemble and to focus on the level of individual molecules. Although the formation of the first self-replicating, most likely homochiral molecule, is a seemingly improbable event, on a closer look, it is almost inevitable that some homochiral molecules have formed simply on a statistical basis. In this case, the non-selective leap to homochirality would be one of the first steps in chemical evolution directly out of a racemic “ocean”. Moreover, most studies focus on the chirality of the primordial monomers with respect to an asymmetric carbon atom. However, any polymer with a minimal size that allows folding to a secondary structure would spontaneously lead to asymmetric higher structures (conformations). Most of the functions of these polymers would be influenced by this inherently asymmetric folding. Furthermore, a concept of physical compartmentalization based on rock nanopores in analogy to nanocavities of digital immunoassays is introduced to suggest that complex cell walls or membranes were also not required for the first steps of chemical evolution. To summarize, simple and universal mechanisms may have led to homochiral self-replicating systems in the context of chemical evolution. A homochiral monomer pool is deemed unnecessary and probably never existed on primordial Earth.
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.
In materials science, traditional techniques for analyzing layered structures are essential for obtaining information about local structure, electronic properties and chemical states. While valuable, these methods often require high vacuum environments and have limited depth profiling capabilities. The grazing exit x-ray absorption near-edge structure (GE-XANES) technique addresses these limitations by providing depth-resolved insight at ambient conditions, facilitating in situ material analysis without special sample preparation. However, GE-XANES is limited by long data acquisition times, which hinders its practicality for various applications. To overcome this, we have incorporated Bayesian optimization (BO) into the GE-XANES data acquisition process. This innovative approach potentially reduces measurement time by a factor of 50. We have used a standard GE-XANES experiment, which serve as reference, to validate the effectiveness and accuracy of the BO-informed experimental setup. Our results show that this optimized approach maintains data quality while significantly improving efficiency, making GE-XANES more accessible to a wider range of materials science applications.
Quantitative microstructural analysis of XCT 3D images is key for quality assurance of materials and components. In this paper we implement a Graph Convolutional Neural Network (GCNN) architecture to segment a complex Al-Si Metal Matrix composite XCT volume (3D image). We train the model on a synthetic dataset and we assess its performance on both synthetic and experimental, manually-labeled, datasets. Our simple GCNN shows a comparable performance, measured via the Dice score, to more standard machine learning methods, but uses a greatly reduced number of parameters (less than 1/10 of parameters), features low training time, and needs little hardware resources. Our GCNN thus achieves a cost-effective reliable segmentation.
Silicon isotope fractionation during silicification is poorly understood and impedes our ability to decipher paleoenvironmental conditions from Si isotopes in ancient cherts. To investigate isotope fractionation during silica-for-carbonate replacement we analyzed the microscale Si and O isotope composition in different silica phases in a silicified zebra dolostone as well as their bulk δ18O and Δ’17O compositions. The subsequent replacement of carbonate layers is mimicked by decreasing δ18O and δ30Si. The textural relationship and magnitude of Si and O isotope fractionation is best explained by near-quantitative silica precipitation in an open system with finite Si. A Rayleigh model for silicification suggests positive Ɛ30/28Si during silicification, conforming with predictions for isotope distribution at chemical equilibrium from ab-initio models. Application of the modelled Ɛ30Si-T relationship yields silicification temperatures of approx. 50°C. To reconcile the δ18Ochert composition with these temperatures, the δ18O of the fluid must have been between -2.5 and -4 ‰, compositions for which the quartz phases fall close to the oxygen equilibrium fractionation line in three-isotope space. Diagenetic silica replacement appears to occur in O and Si isotopic equilibrium allowing reconstructions of temperatures of silicification from Si isotopes and derive the δ18O composition of the fluid – a highly desired value needed for accurate reconstructions of the temperature- and δ18O histories of the oceans.
The European Commission has recently announced two guiding principles for EU product policy: First, product policy shall ensure that the performance of front-runner products in terms of sustainability becomes the norm, and second, the effectiveness of the current Ecodesign legislative framework is going to be significantly improved. Within this paper, already existing front-runner approaches and recent and ongoing product policy-making processes were reviewed. Based on the results, an EU front-runner approach is outlined. The presented approach (i) refers to performance levels of the best products already available on the market, (ii) aggregates information in existing databases, and (iii) works semi-automated. Together, all three attributes have a high potential to facilitate and accelerate the specification of appropriate minimum requirements for products at the EU level. This way, EU policymakers can deliver on the core objectives of the Ecodesign legislative framework much better. The basic mechanism and its legal entrenchment of the approach are illustrated for the energy efficiency of energy-related products. In addition, the Front-Runner Approach can be applied to any product group in the scope of the upcoming Ecodesign for Sustainable Products Regulation and to a wide range of product-related minimum requirements, such as durability, reparability, or recycled content. The study’s objective is to suggest a tailor-made and dynamic approach to keep the EU product legislation up to date using innovative technology based on the investigation of current regulations and identify the gap. Experiences from three international case studies suggest that a front-runner approach to setting energy-performance standards can drive innovation and reduce energy consumption via promoting energy-efficient products; transparency about available products is one of the key factors and can be established by a database. The EU front-runner approach comprises extending the existing energy label database (or making use of the digital product passport) and introducing a legislative procedure that triggers changes in the energy efficiency requirements in the specific EU regulations if the database shows that a certain threshold value is reached. Challenges such as limited EU staff capacities and opportunities such as increased dynamic are discussed.
The LOBSTER (Deringer et al., 2011;Maintz et al., 2013 ,2016 ;Nelson et al., 2020 ) software aids in extracting quantum-chemical bonding information from materials by projecting the plane-wave based wave functions from density functional theory (DFT) onto an atomic orbital basis. LobsterEnv, a module implemented in pymatgen (Ong et al., 2013) by some of the authors of this package, facilitates the use of quantum-chemical bonding information obtained from LOBSTER calculations to identify neighbors and coordination environments. LobsterPy is a Python package that offers a set of convenient tools to further analyze and summarize the LobsterEnv outputs in the form of JSONs that are easy to interpret and process. These tools enable the estimation of (anti) bonding contributions, generation of textual descriptions, and visualization of LOBSTER computation results. Since its first release, both LobsterPy and LobsterEnv capabilities have been extended significantly. Unlike earlier versions, which could only automatically analyze Crystal Orbital Hamilton Populations (COHPs) (Dronskowski & Blöchl, 1993), both can now also analyze Crystal Orbital Overlap Populations (COOP) (Hughbanks & Hoffmann, 1983) and Crystal Orbital Bond Index (COBI) (Müller et al., 2021). Extracting the information about the most important orbitals contributing to the bonds is optional, and users can enable it as needed. Additionally, bonding-based features for machinelearning (ML) studies can be engineered via the sub-packages “featurize” and “structuregraphs”. Alongside its Python interface, it also provides an easy-to-use command line interface (CLI) that runs automatic analysis of the computations and generates a summary of results and publication-ready figures. LobsterPy has been used to produce the results in Ngo et al. (2023), Chen et al. (2024), Naik et al. (2023), and it is also part of Atomate2 (2023) bonding analysis workflow for generating bonding analysis data in a format compatible with the Materials Project (Jain et al., 2013) API.
We present Jobflow, a domain-agnostic Python package for writing computational workflows tailored for high-throughput computing applications. With its simple decorator-based approach, functions and class methods can be transformed into compute jobs that can be stitched together into complex workflows. Jobflow fully supports dynamic workflows where the full acyclic graph of compute jobs is not known until runtime, such as compute jobs that launch
other jobs based on the results of previous steps in the workflow. The results of all Jobflow compute jobs can be easily stored in a variety of filesystem- and cloud-based databases without the data storage process being part of the underlying workflow logic itself. Jobflow has been intentionally designed to be fully independent of the choice of workflow manager used to dispatch the calculations on remote computing resources. At the time of writing, Jobflow
workflows can be executed either locally or across distributed compute environments via an adapter to the FireWorks package, and Jobflow fully supports the integration of additional workflow execution adapters in the future.
The transition toward a hydrogen-based economy requires a widespread transport and distribution network, and repurposed natural gas pipelines are a viable option. An assessment of the hydrogen-induced degradation of pipeline steels is needed to inject H2 gas into the existing infrastructure safely. The conservative and standardized method consists of in-situ tensile tests in an autoclave filled with high-pressure hydrogen gas. A proposed alternative method involves
using a hollow specimen as containment volume and applying the gas pressure in the inner cavity.
This technique has lower costs and shorter test preparation time but is not standardized yet. This study aims to evaluate and compare the tensile properties of API 5L X65 pipeline steel in two states: vintage and modern. The influence of the surface roughness is investigated through parallel tests with drilled and reamed specimens. Hydrogen tests are compared with reference tests in an inert environment. A significant hydrogen-induced decrease in tensile properties is observed, and no significant difference between vintage and modern X65 can be drawn. The reduction in tensile properties is more significant in specimens with higher inner surface roughness. The evaluation of surface conditions appears crucial when assessing the HE susceptibility of hydrogen transport and storage equipment.
EPDM, HNBR and FKM materials were exposed at 150 ◦C to air under atmospheric pressure and to hydrogen at 50 bar for different ageing times. All measurements after hydrogen exposure were conducted on samples in degassed condition to assess irreversible effects resulting from that exposure and to compare them to those after ageing in air. Density, hardness, tensile properties, compression set, and hydrogen permeability of all samples were analysed. In both ageing environments, HNBR exhibited the most significant changes of material properties.
However, for both EPDM and HNBR, considerably less severe ageing effects were observed under hydrogen in comparison to ageing in air. On the other hand, FKM showed about the same low level of deterioration in both ageing environments but exhibited poor resistance against damage due to rapid gas decompression in hydrogen environment that can lead to seal failure. The obtained results may serve as a guidance toward a better understanding for design and utilisation of elastomeric materials in future hydrogen infrastructure components.
AbstractLithium‐ion batteries, essential for electronics and electric vehicles, predominantly use cathodes made from critical materials like cobalt. Sulfur‐based cathodes, offering a high theoretical capacity of 1675 mAh g−1 and environmental advantages due to sulfur's abundance and lower toxicity, present a more sustainable alternative. However, state‐of‐the‐art sulfur‐based electrodes do not reach the theoretical capacities, mainly because conventional electrode production relies on mixing of components into weakly coordinated slurries. Consequently, sulfur‘s mobility leads to battery degradation—an effect known as the “sulfur‐shuttle”. This study introduces a solution by developing a microporous, covalently‐bonded, imine‐based polymer network grown in situ around sulfur particles on the current collector. The polymer network (i) enables selective transport of electrolyte and Li‐ions through pores of defined size, and (ii) acts as a robust host to retain the active component of the electrode (sulfur species). The resulting cathode has superior rate performance from 0.1 C (1360 mAh g−1) to 3 C (807 mAh g−1). Demonstrating a high‐performance, sustainable sulfur cathode produced via a simple one‐pot process, our research underlines the potential of microporous polymers in addressing sulfur diffusion issues, paving the way for sulfur electrodes as viable alternatives to traditional metal‐based cathodes.
Transparent conductive oxides such as indium tin oxide (ITO) are standards for thin film electrodes, providing a synergy of high optical transparency and electrical conductivity. In an electrolytic environment, the determination of an inert electrochemical potential window is crucial to maintain a stable material performance during device operation. We introduce operando ellipsometry, combining cyclic voltammetry (CV) with spectroscopic ellipsometry, as a versatile tool to monitor the evolution of both complete optical (i.e., complex refractive index) and electrical properties under wet electrochemical operational conditions. In particular, we trace the degradation of ITO electrodes caused by electrochemical reduction in a pH-neutral, water-based electrolyte environment during electrochemical cycling. With the onset of hydrogen evolution at negative bias voltages, indium and tin are irreversibly reduced to the metallic state, causing an advancing darkening, i.e., a gradual loss of transparency, with every CV cycle, while the conductivity is mostly conserved over multiple CV cycles. Post-operando analysis reveals the reductive (loss of oxygen) formation of metallic nanodroplets on the surface. The reductive disruption of the ITO electrode happens at the solid–liquid interface and proceeds gradually from the surface to the bottom of the layer, which is evidenced by cross-sectional transmission electron microscopy imaging and complemented by energy-dispersive X-ray spectroscopy mapping. As long as a continuous part of the ITO layer remains at the bottom, the conductivity is largely retained, allowing repeated CV cycling. We consider operando ellipsometry a sensitive and nondestructive tool to monitor early stage material and property changes, either by tracing failure points, controlling intentional processes, or for sensing purposes, making it suitable for various research fields involving solid–liquid interfaces and electrochemical activity.
Abstract. In power electronics, compound semiconductors with large bandgaps, like silicon carbide (SiC), are increasingly being used as material instead of silicon. They have a lot of advantages over silicon but are also intolerant of nanoscale material defects, so that a defect inspection with high accuracy is needed. The different defect types on SiC samples are measured with various measurement methods, including optical and tactile methods. The defect types investigated include carrots, particles, polytype inclusions and threading dislocations, and they are analysed with imaging ellipsometry, coherent Fourier scatterometry (CFS), white light interference microscopy (WLIM) and atomic force microscopy (AFM). These different measurement methods are used to investigate which method is most sensitive for which type of defect to be able to use the measurement methods more effectively. It is important to be able to identify the defects to classify them as critical or non-critical for the functionality of the end product. Once these investigations have been completed, the measurement systems can be optimally distributed to the relevant defects in further work to realize a hybrid analysis of the defects. In addition to the identification and classification of defects, such a future hybrid analysis could also include characterizations, e.g. further evaluation of ellipsometric data by using numerical simulations.
Heterogeneous sandwich immunoassays are widely used for biomarker detection in bioanalysis and medical diagnostics. The high analyte sensitivity of the current “gold standard” enzyme-linked immunosorbent assay (ELISA) originates from the signal-generating enzymatic amplification step, yielding a high number of optically detectable reporter molecules. For future point-of-care testing (POCT) and point-of-need applications, there is an increasing interest in more simple detection strategies that circumvent time-consuming and temperature-dependent enzymatic reactions. A common concept to aim for detection limits comparable to those of enzymatic amplification reactions is the usage of polymer nanoparticles (NP) stained with a large number of chromophores. We explored different simple NP-based signal amplification strategies for heterogeneous sandwich immunoassays
that rely on an extraction-triggered release step of different types of optically detectable reporters. Therefore, streptavidinfunctionalized polystyrene particles (PSP) are utilized as carriers for (i) the fluorescent dye coumarin 153 (C153) and (ii) hemin (hem) molecules catalyzing the luminol reaction enabling chemiluminescence (CL) detection. Additionally, (iii) NP labeling with hemin-based microperoxidase MP11 was assessed. For each amplification approach, the PSP was first systematically optimized regarding size, loading concentration, and surface chemistry. Then, for an immunoassay for the inflammation marker C- eactive protein (CRP), the analyte sensitivity achievable with optimized PSP
ystems was compared with the established ELISA concept for photometric and CL detection. Careful optimization led to a limit of detection (LOD) of 0.1 ng/mL for MP11-labeled PSP and CL detection, performing similarly well to a photometric ELISA (0.13 ng/mL), which demonstrates the huge potential of our novel assay concept.
Irradiation of solid surfaces with high intensity, ultrashort laser pulses triggers a variety of secondary processes that can lead to the formation of transient and permanent structures over a large range of length scales from mm down to the nano‐range. One of the most prominent examples are LIPSS – Laser‐Induced Periodic Surface Structures. While LIPSS have been a scientific evergreen for of almost 60 years, experimental methods that combine ultrafast temporal with the required nm spatial resolution have become available only recently with the advent of short pulse, short wavelength free electron lasers. Here, the current status and future perspectives in this field are discussed by exploiting the unique possibilities of these 4th‐generation light sources to address by time‐domain experimental techniques the fundamental LIPSS‐question, namely why and how laser irradiation can initiate the transition of a “chaotic” (rough) surface from an aperiodic into a periodic structure.
Cellulose nanofibrils (CNFs) with different charge densities were prepared and investigated by a combination of different complementary techniques sensitive to the structure and molecular dynamics of the system. The morphology of the materials was investigated by scanning electron microscopy (SEM) and X-ray scattering (SAXS/WAXS). The latter measurements were quantitatively analyzed yielding to molecular parameters in dependence of the charge density like the diameter of the fibrils, the distance between the fibrils, and the dimension of bundles of nanofibrils, including pores. The influence of water on the properties and the charge density is studied by thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and broadband dielectric spectroscopy. The TGA measurements reveal two mass loss processes. The one at lower temperatures was related to the loss of water, and the second process at higher temperatures was related to the chemical decomposition. The resulting char yield could be correlated to the distance between the microfibrils. The DSC investigation for hydrated CNFs revealed three glass transitions due to the cellulose segments surrounded by water molecules in different states. In the second heating scan, only one broad glass transition is observed. The dielectric spectra reveal two relaxation processes. At low temperatures or higher frequencies, the β-relaxation is observed, which is assigned to localized fluctuation of the glycosidic linkage. At higher temperatures and lower frequencies, the α-relaxation takes places. This relaxation is due to cooperative fluctuations in the cellulose segments. Both processes were quantitatively analyzed. The obtained parameters such as the relaxation rates were related to both the morphological data, the charge density, and the content of water for the first time.
Multiphoton lithography (MPL), an emerging truly 3D microfabrication technique, exhibits substantial potential in biomedical applications, including drug delivery and tissue engineering. Fabricated micro-objects are often expected to undergo shape morphing or bending of the entire structure or its parts. Furthermore, ensuring precise property tuning is detrimental to the realization of the functionality of MPL microstructures. Herein, novel MPL materials based on interpenetrating polymer networks (IPNs) are presented that effectively combine the advantages of acrylate and epoxy systems. IPNs with varying component ratios are investigated for their microfabrication performance and structural integrity with respect to thermal and micromechanical properties. A variety of high-resolution techniques is applied to comprehensively evaluate IPN properties at the bulk, micron, and segmental levels. This study shows that the MPL laser scanning velocity and power, photoinitiator content, and multi-step exposure can be used to tune the morphology and properties of the IPN. As a result, a library of 3D MPL IPN microstructures with high 3D structural stability and tailored thermal and micromechanical properties is achieved. New IPN microstructures with Young’s moduli of 3–4 MPa demonstrate high-to-fully elastic responses to deformations, making them promising for applications in morphable microsystems, soft micro-robotics, and cell engineering.
Recent publications indicate that the order of electrochemical anodization (before or after the laser processing step) plays an important role for the response of bone-forming osteoblasts—an effect that can be utilized for improving permanent dental or removable bone implants. For exploring these different surface functionalities, multimethod morphological, structural, and chemical characterizations are performed in combination with electrochemical pre- and postanodization for two different characteristic microspikes covered by nanometric laser-induced periodic surface structures on Ti–6Al–4V upon irradiation with near-infrared ps-laser pulses (1030 nm wavelength, ≈1 ps pulse duration, 67 and 80 kHz pulse repetition frequency) at two distinct sets of laser fluence and beam scanning parameters. This work involves morphological and topographical investigations by scanning electron microscopy and white light interference microscopy, structural material examinations via X-ray diffraction, and micro-Raman spectroscopy, as well as near-surface chemical analyses by X-ray photoelectron spectroscopy and hard X-ray photoelectron spectroscopy. The results allow to qualify the mean laser ablation depth, assess the spike geometry and surface roughness parameters, and provide new detailed insights into the near-surface oxidation that may affect the different cell growth behavior for pre- or postanodized medical implants.
Two-dimensional covalent organic frameworks (COFs) based on phosphinine and thiophene building blocks have been synthesized with two different side groups. The materials are denoted as CPSF-MeO and CPSF-EtO where CxxF correspond to the covalent framework, whereas P and S are related to heteroatoms phosphorous and sulfur. MeO and EtO indicate the substituents, i.e. methoxy and ethoxy.
Their morphologies were studied by scanning electron microcopy and X-ray scattering. The absence of crystalline reflexes in the X-ray pattern reveal that both materials are amorphous and can be considered as glasses. Furthermore, N2 adsorption measurements indicate substantial Brunauer–Emmett–Teller (BET) surface area values pointing to the formation of three-dimensional pores by stacking of the aromatic 2D layer. An analysis of the porosity of both COFs showed a mean radius of the pores to be of ca. 4 nm, consistent with their chemical structure. The COFs form nanoparticles with a radius of around 100 nm. The thermal behavior of the COFs was further investigated by fast scanning calorimetry. These investigations showed that both COFs undergo a glass transition. The glass transition temperature of CPSF-EtO is found to be ca. 100 K higher than that for CPSF-MeO. This large difference in the glass transition is discussed to be due to a change in the interaction of the COF sheets induced by the longer ethoxy group. It might be assumed that for CPSF-EtO more individual COF sheets assemble to larger stacks than for CPSF-MeO. This agrees with the much larger surface area value found for CPSF-EtO compared to CPSF-MeO. To corroborate the results obtained be fast scanning calorimetry dielectric measurements were conducted which confirm the occurrence of a dynamic glass transition. The estimated temperature dependence of the relaxation rates of the dielectric relaxation and their absolute values agrees well with the data obtained by fast scanning calorimetry. Considering the fragility approach to the glass transition, it was further found that CPSF-MeO is a fragile glass former whereas CPSF-EtO behaves as a strong glass forming material. This difference in the fragility points also to distinct differences in the interaction between the 2D COF molecules in both materials.