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Thermal decomposition in blended cement systems and its effect on fire-induced concrete spalling: Insights from XRD and TGA
No full textBlended cements are gaining increasing popularity due to their lower CO2-footprint in comparison to ordinary Portland cement (OPC). However, this growing use raises the potential risk of buildings made with blended cement concrete being exposed to fire, which can lead to heavy damages caused by explosive concrete spalling. It has already been shown that the cement type strongly influences the fire-induced concrete spalling and the thermally induced moisture transport, however, to understand the mechanisms behind these findings the thermal decomposition behavior of the cementitious matrix must be investigated more systematically. Therefore, the phase content of three blended cement pastes (CEM II/A-LL, CEM III/A and CEM II/B-Q) was studied in comparison with a Portland cement paste (CEM I) after temperature exposure to 20 °C, 105 °C, 300 °C and 500 °C. Clear differences in the initial phase composition and their dehydration behavior between the individual cement types were recognized. In conclusion, blended cements showed lower amounts of AFt and AFm phases and additionally lower amounts of portlandite and C-(A)-S-H were found in CEM III/A and CEM II/B-Q pastes. The results suggest that higher AFt and AFm contents in CEM I, which are associated with greater water release at relatively low temperatures may ultimately reduce the spalling risk. Furthermore, C-(A)-S-H in CEM III/A and CEM II/B-Q showed increased thermal stability and large amounts of non-hydrated phases were found in every blended cement paste. Both of those aspects might contribute to thermomechanical spalling and the overall increased spalling susceptibility observed in blended cement concrete
Micro‐ and Macroscopic Analysis of Agglomerate‐Driven Oil Immobilization in Nut‐Based Pastes
No full textOil mobility is a key determinant of stability in hazelnut-based pastes, as it promotes oil separation, which in turn causes a greasy texture and increased susceptibility to oxidation. It is hypothesized that (1) grinding leads to the formation of agglomerates that immobilize oil and thus prevent oil separation and that (2) mixing disrupts these structures, resulting in destabilization and increased oil mobility. The understanding of the formation, process dependency, and functional relevance of agglomerates is limited by the lack of analytical methods for their detection. This study employed a multiscale analytical approach combining microscopic techniques (light microscopy and NMR diffusometry) for direct detection of agglomerates with macroscopic measurements (oil binding capacity, rheology, and oil separation during 4 weeks of storage) to reveal their function in nut pastes of increasing complexity: pure hazelnut pastes (100% w/w nuts), hazelnut–sugar pastes (70% w/w nuts and 30% w/w sugar), and nougat formulations. Grinding technologies (cutter, ball mill, and roller refiner) at two intensities were compared during the production of pure hazelnut and hazelnut–sugar pastes. Based on these results, nougat pastes were produced at laboratory and industrial scales using roller refining. Mixing conditions of nougat pastes were varied to evaluate the stability of agglomerates and its impact on oil mobility. Agglomerate structures were detected using microscopic techniques, depending on processing technology, intensity, and composition of hazelnut-based pastes. In macroscopic tests, their presence was associated with enhanced oil immobilization and improved product stability. These findings demonstrate that oil mobility in hazelnut-based pastes is strongly influenced by grinding and mixing conditions and highlight the relevance of a multiscale analytical approach to optimize processing for stable fat-based products
On a T-structure in geometrically linearized elasticity: Qualitative and quantitative analysis and numerical simulations
No full textWe study the rigidity properties of the T-structure for the symmetrized gradient from the work of Bhattacharya, Firoozye, James and Kohn [Restrictions on microstructure, Proc. Roy. Soc. Edinburgh Sect. A124 (1994) 843–878; BFJK] qualitatively, quantitatively and numerically. More precisely, we complement the flexibility result for approximate solutions of the associated differential inclusion which was deduced in BFJK by a rigidity result on the level of exact solutions and by a quantitative rigidity estimate and scaling result. The T3-structure for the symmetrized gradient can hence be regarded as a symmetrized gradient analogue of the Tartar square for the gradient. As such a structure cannot exist in R the example from BFJK is in this sense minimal. We complement our theoretical findings with numerical simulations of the resulting microstructure
A Data‐Driven Quest for Room‐Temperature Bulk Plastically Deformable Ceramics
No full textThe growing number of ceramics exhibiting bulk plasticity at room temperature has renewed interest in revisiting plastic deformation and dislocation-mediated mechanical and functional properties in these materials. In this work, a data-driven approach is employed to identify the key parameters governing room-temperature bulk plasticity in ceramics. The model integrates an existing dataset of 55 ceramic materials, including 38 plastically deformable and 17 brittle, and achieves accurate classification of bulk plasticity. The analysis reveals several key parameters essential for predicting bulk plasticity: (i) Poisson\u27s ratio and Pugh\u27s ratio as macroscopic indicators reflecting the balance between shear and volumetric deformation resistance, and (ii) Burgers vector, crystal structure and melting temperature as crystallographic descriptors associated with lattice geometry, slip resistance and thermal stability, and iii) Bader charge as a microscopic measure of bonding character. Together, these parameters define a multiscale descriptor space linking intrinsic materials properties to bulk room-temperature plasticity in ceramics, bridging the gap between empirical ductility criteria and atomistic mechanisms of dislocation-mediated plasticity. While preliminary, this study provides the first systematic, data-driven mapping of the governing factors of ceramic plasticity. The resulting framework establishes a foundation for unifying experimental and computational studies through shared datasets and descriptors, fostering collective progress toward understanding and designing intrinsically ductile ceramics
Novel approaches for quantitative assessments of wetting development in membrane distillation based on optical coherence tomography
No full textOptical coherence tomography (OCT) has been considered as a non-invasive imaging tool to provide real-time, local information of wetting in membrane distillation (MD). However, the follow-up research question is how to quantitatively assess the localized wetting development in order to prevent system failure. This study aims to develop a quantification method based on the changes in the intensity distribution within OCT three-dimensional datasets (volume scan, C-scans). The achieved maps elucidate the wetting depth (e.g., wetting progress) across the membrane area in various cases. Severe wetting with homogeneous and heterogeneous distribution, and even subtle wetting have been quantified successfully. Results indicate that an increase in the volume of wetted membrane (expressed as the wetting ratio) does not necessarily correspond to an increase in the membrane area that is fully wetted (expressed as fully-wetted fraction), revealing the limiting parameter for deterioration in condensate quality. Additionally, the underlying mechanism governing the wetting behavior was also discussed based on the quantified wetting parameters. This OCT-based method would be helpful to investigate wetting not only for MD but also potentially for other membrane processes involving two-phase flow such as gas–liquid membrane contactors and membrane biofilm reactors
Oxidation and degradation of Cr-coated Zr-based alloy up to 1500°C: Effect of Cr thickness
No full textThis study systematically investigates the influence of chromium coating thickness (5–25 μm) on the oxidation and degradation behavior of Cr-coated Zircaloy-4 under high-temperature steam conditions up to 1500 ◦C. Using thermogravimetry, hydrogen release monitoring, and extensive post-test microstructural analyses, the results show that thicker Cr coatings significantly extend the protective effect below the Zr–Cr eutectic temperature (~1330 ◦C). The degradation processes are governed by different diffusion mechanisms that gradually lead to a loss of coating protectiveness, with transition times strongly dependent on coating thickness and temperature. Above the eutectic point, however, all coatings fail almost instantaneously, regardless of thickness, with the oxidation kinetics switching from chromia to zirconia formation. The findings confirm the effectiveness of Cr coatings under normal operation, transients, and design-basis accidents, but demonstrate their intrinsic limita-
tions in beyond-design-basis accident scenarios exceeding the eutectic temperature
Analyzing the acceleration time and reflectance of light sails made from homogeneous and core-shell spheres
No full textDeciding on appropriate materials and designs for use in light sails, like the one proposed in the Breakthrough Starshot Initiative, is a topic that requires much care and forethought. Here, we offer a feasible option in the form of metasurfaces made of periodically arranged homogeneous and core-shell spheres. Using the re-normalized T-matrix from Mie theory, we explore the reflectance, absorptance, and acceleration time of such metasurfaces. We focus on spheres made from aluminum, silicon, silicon dioxide, and combinations thereof. Since the light sails are foreseen to be accelerated using Earth-based laser arrays to 20% of the speed of light, one needs to account for relativistic effects. As a result, a high broadband reflectance is essential for effective propulsion. We identify metasurfaces that offer such properties combined with a low absorptance to reduce heating and deformation. We highlight a promising extension to the case of a metasurface made from homogeneous silicon spheres, as already discussed in the literature, by adding a layer of silicon dioxide. The high broadband reflectance of the silicon and silicon dioxide combination is explained by the favorable interference of the multipolar contributions of the outgoing field up to quadrupolar order. We also consider the impact of an embedding material characterized by different refractive indices. Refractive indices up to 1.13 maintain over 90% reflectance without re-optimizing the light sail
Engineering Digital Engineering : A methodology for model-based and subject-oriented design
No full textDigitale Ecosysteme stellen ein neuartiges Paradigma für industrielle Zusammenarbeit dar, das Coopetition, Resilienz und Anpassungsfähigkeit zwischen vielfältigen Akteuren betont. Ihre inhärente Komplexität – bedingt durch Heterogenität, Emergenz und Föderation – erschwert jedoch eine effektive Gestaltung erheblich. Diese Studie begegnet diesen Herausforderungen mit der Einführung der Engineering Digital Ecosystems (EDE) Methodologie, einem modellbasierten und subjektorientierten Gestaltungsrahmen, der auf die Bedürfnisse sozio-technischer Digitaler Ecosysteme zugeschnitten ist, insbesondere im Kontext kleiner und mittelständischer Unternehmen (KMU). Geleitet vom Paradigma der Design Science Research (DSR) untersucht die Arbeit zwei zentrale Forschungsfragen: (1) Wie kann der Gestaltungsprozess Digitaler Ecosysteme durch eine modellbasierte Methodologie unterstützt werden? und (2) Welche Art von subjektorientiertem Modell eignet sich zur Beschreibung solcher Ecosysteme? Die resultierende EDE-Methodologie integriert einen Vorgehensmodell basierend auf dem Double-Diamond mit einem mehrschichtigen Synthesis Model, das strukturelle, funktionale, interaktive und verhaltensbezogene Aspekte Digitaler Ecosysteme abbildet. Der Rahmen wurde iterativ im industriellen Anwendungskontext (IntWertL) entwickelt und evaluiert, wodurch validierte Artefakte und praxisnahe Erkenntnisse gewonnen wurden. Diese Arbeit liefert die erste zufriedenstellende Methodologie zur Gestaltung Digitaler Ecosysteme und bietet einen systematischen, nutzerorientierten Ansatz, der Klarheit, Kommunikation, und Abstimmung entlang des gesamten Designprozesses verbessert
Tailoring Patient-Specific Cranial Implants for Bone Reconstruction via End-to-End Deep Learning Image-to-Print Approach
No full textCalculation of the Ionisation-Cluster Size Distribution for LEEs in Nanometric Volumes Using A Principle Relevant for Generative Artificial Intelligence
No full textDas Problem bei der Bestimmung der Ionisations-Cluster-Größe wird erklärt. Anschließend wird ein statistisches Modell zur Berechnung der Verteilung der Ionisations-Cluster-Größe vorgestellt. Das Modell basiert auf einem Prinzip, das dem Prinzip der maximalen Entropie entspricht