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Paper des Monats
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Although the use of noble metal catalysts can increase the efficiency of hydrogen evolution reaction, the process is still limited by the characteristics of the metal-hydrogen (M−H) bond, which can be too strong or too weak, depending on the metal employed. Studies revealed that the hydrogen affinity for the metal surface (i.e. H absorption/desorption) is regulated also by the potential at the metal nanoparticles. Through controlled periodic illumination (CPI) of a series of metal/TiO2 suspensions, here we demonstrated that an increase of the HER efficiency is possible for those photodeposited metals which have a Tafel slope below 125 mV. Two possible explanations are here reported, in both of them the M−H interaction and the metal covering level play a prominent role, which also depend on the prevailing HER mechanism (Volmer-Heyrovsky or Volmer-Tafel).
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.
Die Integration von Automation und Robotik in die Prüfprozesse ermöglicht die
Untersuchung komplexer Bauteile. Diese Studie präsentiert die robotergestützte
Laserthermografie, um Risse in solchen Bauteilen zu identifizieren und analysieren. Diese Technik ermöglicht die automatisierte Rissprüfung welche im Vergleich zur Farbeindringprüfung auf viele, meist manuelle, Arbeitsschritte sowie die notwendigen Chemikalien verzichtet.
Zusätzlich wird ein automatisiertes Einscannen der Bauteile mithilfe eines
Linienscanners vorgestellt. Dieser Schritt ermöglicht eine detaillierte 3D-Rekonstruktion der Bauteilgeometrie und ermöglicht eine einfache Korrektur von Abweichungen in der Bauteilaufnahme und eröffnet Möglichkeiten zur adaptiven Bahnplanung bei Bauteilverformungen.
Die Rückprojektion der gefundenen Risse auf die Oberfläche des Bauteils kann
automatisiert erfolgen. Dieser Schritt erlaubt nicht nur die Identifikation der Risse, sondern auch eine genauere Analyse ihrer Geometrie und Lage am Bauteil.
Die Kombination von robotergestützter Laserthermografie, automatisiertem 3DScanning und Rückprojektion der Risse auf die Bauteiloberfläche eröffnet neue
Möglichkeiten in der zerstörungsfreien Prüfung von komplexen Bauteilen und erweitert damit mögliche Anwendungsfelder.
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.
It is an essential requirement for all building products to ensure durability of their fire safety. Throughout the working life of products, intumescent coatings are aged by certain climatic factors. To predict a lifetime of several years, generally the behaviour of the intumescent coating is extrapolated based on accelerated artificial ageing. The established German and European procedures to assess the durability assume a working life of at least 10 years. For a longer period, additional evidence is required; yet the procedure and the specifications to justify this are not described. In addition to addressing this formal lack, from a scientific point of view it is necessary to investigate the degradation of intumescent coatings in detail and to propose a reliable test concept to assess durability for more than 10 years. This paper summarises the existing knowledge about the ageing of intumescent coatings. The results of various demanding weathering approaches are presented for two intumescent coatings tested in a joint research project. Moreover, formulations with a reduced amount of functionally relevant components were analysed to gain insight into the associated effects. Derived from these research results and knowledge, recommendations are proposed to assess the durability of intumescent coatings for more than 10 years based on a combination of verifications.
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.