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Es wird eine Vorrichtung zum thermischen Trennen eines metallischen Werkstücks offenbart. Die Vorrichtung weist einen Schneidkopf zur Erzeugung eines thermischen Schneidstrahls auf, mit dem das metallische Werkstück thermisch schneidbar ist, wobei durch den Schneidstrahl im metallischen Werkstück eine Trennfuge mit Schmelzbad erzeugbar ist. Ferner weist die Vorrichtung eine Einrichtung zur Erzeugung externer magnetischer Felder auf, dazu eingerichtet, das mittels des thermischen Schneidstrahls hergestellte Schmelzbad aus der Trennfuge des metallischen Werkstücks zu treiben, wobei die Einrichtung aufweist: eine Steuereinheit, und mindestens einen durch die Steuereinheit steuerbaren Magneten, wobei der Magnet in einer Richtung quer zu einer Werkstückoberfläche des Werkstücks in Bezug zu einer Richtung der Gravitationskraft oberhalb des Werkstücks und zwischen dem metallischen Werkstück und dem Schneidkopf angeordnet ist, wobei die Steuereinheit derart eingerichtet ist, dass der Magnet ein oszillierendes Magnetfeld am Schmelzbad erzeugt, so dass dadurch ein Wirbelstrom in dem Schmelzbad erzeugt wird. Ferner wird ein thermisches Trennverfahren offenbart.
Die Erfindung betrifft ein Verfahren zum Fügen zweier Fügepartner mittels Metallschweißens, umfassend: Bereitstellen zweier Fügepartner, die jeweils mindestens eine Kontaktfläche aufweisen, über die die Fügepartner gefügt werden sollen; Bereitstellen eines aufzutragenden Auftragmittels, wobei das Auftragmittel ein Schichtmaterial beinhaltet, das mindestens ein Metall oder Halbmetall und/oder mindestens ein Oxid eines Metalls oder Halbmetalls enthält; Auftragen des Auftragmittels zur Bildung einer haftenden Schicht auf mindestens einer der Kontaktflächen mit einer vorgegebenen Menge an Schichtmaterial pro Fläche, wobei die Schicht entweder durch Auftragen des Auftragmittels, welches als Dispersion vorliegt, oder durch ein thermisches Spritzverfahren zum Auftragen des Auftragmittels gebildet wird; Fügen der Fügepartner über die mit der haftenden Schicht beschichtete mindestens eine Kontaktflächen unter der Verwendung eines Strahlschweißverfahrens oder Schutzgasschweißverfahrens, vorzugsweise mittels Laser- oder Elektronenschweißens, oder mittels Plasmastichlochschweißens.
Glasses are a non-equilibrium, non-crystalline condensed state of matter that exhibits a glass transition, where their structure is like that of their parent supercooled liquid. The non-crystalline nature of glasses provides them with several advantages over crystalline materials, including superior mechanical behavior and defiance of stoichiometry rules. However, this comes with drawbacks as well, as it is nontrivial to analyze the glass structure at a level larger than the short range (> 5 ), thus resulting in a lack of proper structure–property relationship. Here, we use atomistic simulations and persistent homology (PH) to analyze the medium-range structure of the archetypal oxide glass (Silica) at ambient temperatures and with varying pressures. PH offers a robust, scale-invariant method to identify loops and cavities, enabling the unbiased detection of topological features that are not captured by conventional structural metrics. This provides an advantage over other methods for studying the structure and topology of complex materials, such as glasses, across multiple length scales. We captured subtle topological transitions in medium-range order and cavity distributions, providing
insights into glass structure and topology. Our work provides a robust method for extracting the medium-range structure and void distribution of oxide glasses based on persistent homology, thereby advancing the interpretation of glass structure beyond pair correlations.
Microstructure-Specific Mechanisms Define multistage Relaxation Dynamics in a Metallic Model-Glass
(2025)
Glasses are non‐equilibrium materials that continuously relax toward an equilibrium state. On a macroscopic length scale, glasses exhibit a steady, continuous relaxation over time, as evidenced by changes in volume, viscosity, and enthalpy—aging. However, at the microscopic scale, using high‐resolution techniques such as X-ray photon correlation spectroscopy (XPCS), the dynamics have been reported to occur in stages, where relaxation proceeds via avalanches interspersed with long periods of little to no change3,4. This discontinuous aging of metallic glasses reflects the existence of a heterogeneous microstructure and the complexity of the sampled energy landscape at the atomic level, making the understanding of such relaxation behavior far from trivial. Here, using computational XPCS to analyze microsecond molecular-dynamics simulation trajectories of model glasses and supercooled liquids around Tg, we find that their relaxation dynamics occur in multiple stages with different, growing timescales. These relaxation stages can be traced back to spatially correlated structural dynamics governed by the existence and growth of a percolative network of mobile and immobile domains. The mobile network is responsible for the β-relaxation, while the slow domains, which relax on a much slower timescale, give rise to the long-time relaxation plateau. The percolated domains of immobile atoms are found to have an energetically stable, structurally more ordered configuration, similar to that of the C15 Laves phase. Thus, we present a unified picture that maps dynamical and spatial heterogeneities onto each other and links them to the relaxation behavior of glasses and supercooled liquids, reflecting their heterogeneous microstructure.
The discovery and optimization of solvent-resistant nanofiltration (SRNF) membranes remain limited by the complexity of polymeric material systems and the scarcity of harmonized experimental data. Here, we demonstrate how the open membrane database - a preexisting, diverse Findable, Accessible, Interoperable and Reusable (FAIR), open-access membrane database - can be transformed into a robust platform for data-driven materials understanding. Using 5600+ curated SRNF filtration experiments comprising up to 154 descriptors, we construct interpretable machine-learning models that predict two key crucial performance metrics—solvent permeance and molecular-weight cut-off (MWCO). After systematic data cleaning and feature engineering, ensemble treebased models outperform linear and distance-based methods, achieving test-set R2 values of 0.76 for permeance and 0.70 for MWCO. Model explainability via permutation importance and SHapley Additive exPlanations (SHAP) analysis reveals that selective-layer chemistry, deposition method, and nanocomposite components dominate membrane performance, whereas solution conditions influence permeance but not MWCO. External validation of four previously unreported membranes and three literature experiments not in the database confirms the approach's predictive capability, while systematic overestimation of some data points suggests publication bias in the underlying literature. Our results provide mechanistic insight into structure–property relationships in SRNF membranes and establish a possible modeling pipeline for leveraging open experimental data to accelerate the rational design of complex material systems.
Hierarchical nanoporous metals infiltrated with polymers offer enhanced tensile stability while retaining functional porosity, yet their micromechanical deformation mechanisms remain insufficiently understood. Here, a micromechanics-based finite element framework is developed for epoxy-filled hierarchical nanoporous copper (HNPCu) based on experimentally derived structural parameters. The hierarchical ligament architecture across two structural levels as well as selective epoxy infiltration are explicitly resolved, enabling phase-specific analysis of local stress and strain evolution. The predicted tensile response is validated against experiments for different Cu solid fractions (0.1 ≤ 𝜑 ≤ 0.2), and the experimentally observed trends are well reproduced using idealized microstructures. Epoxy infiltration markedly reduces plastic strain localization within the Cu network, leading to a more homogeneous deformation state compared to epoxy-free HNPCu. At the macroscopic level, the tensile response remains largely unaffected by epoxy infiltration at small strains, with differences emerging only at larger deformation. Strain localization is predicted both within Cu ligaments and near Cu–epoxy interfaces, consistent with experimentally observed microcrack formation along phase boundaries and inside the Cu network. These findings provide micromechanical insight into hierarchy-assisted deformation in polymer-infiltrated nanoporous metals and establish a basis for microstructure-guided design of mechanically robust hierarchical materials.
Atomistic simulations are integral to the knowledge and design of glasses, but are nonetheless challenging due to slow structural dynamics, complex workflows, and issues of data management. With advances in high-throughput modeling and machine-learned interatomic potentials, it is worth increasing the Findability, Accessibility, Interoperability, and Reusability (FAIR) of these simulations. Here we present a Python package for the automated setup, execution, and analysis of atomistic simulations of glasses. The software package has semi-to-fully automated modules for the setup of molecular dynamics simulations, preparation of glassy systems, calculation of properties (elastic moduli, viscosity), and structural analysis of the resulting atomic configurations across short- and medium-range order. The computational and workflow management capability is based on the pyiron framework. Showcases of the automated glass preparation, property calculation, and analysis will be presented. The package includes a dedicated web application programming interface for use by large language models. We therefore provide an extensible platform for standardized, FAIR, AI-assisted atomistic simulation of glasses.
This is the first-ever report of igniting a combustive process that we tentatively denote as a mixing-induced self-propagating reaction (MXSR) in an inorganic system by a simple intensive mixing of the educts. The occurrence of MXSR is proven by observing a spike during in situ temperature monitoring. We demonstrate this on the example of agitating copper and sulfur powders in a ball-free planetary mill jar, igniting a MXSR without the external heating or the mechanical impact. Intensive powder agitation yields a mixture of nanocrystalline covellite (CuS) and digenite (Cu1.8S) in under 2 min. MXSR ignition thresholds are precisely determined (jar filling ≥40%, mixing speed ≥700 rpm, Cu:S molar ratio of 0.625–1.00). If these thresholds are not respected, a gradual reaction partly proceeds and an unstable mixture of digenite and non-reacted sulfur is formed, which is transformed into covellite with time. In specific cases, MXSR can be ignited within a few minutes after the termination of mixing. In the end, scalability to 40 and 62.5 g scales in planetary and mixer mills, respectively, is demonstrated and the products' thermoelectric utility for waste heat conversion is showcased. The proposed MXSR pathway overcomes state-of-the-art limitations in mechanochemistry, including product contamination from milling media abrasion and energy-intensive activation, while achieving decent alignment with green chemistry (100% atom economy, 88% and 91% reaction mass efficiency for the experiments performed on a larger scale in a mixer and planetary mill, respectively).
Repair welding of cast iron components is widely employed to restore structural integrity in large-scale systems such as wind turbine hubs. However the brittleness and susceptibility of cast iron components to crack initiation and combined effect of weld bead geometry and Residual Stresses (RSs) on Fatigue Crack Growth (FCG) highlights the need for a thorough understanding and potential optimisation of the process. This study develops an integrated experimental–numerical framework to elucidate the FCG behaviour of repair-welded ductile cast iron, explicitly accounting for RS and geometric effects. FCG tests were conducted on welded specimens extracted from three different areas, namely Weld Metal (WM), Heat-Affected Zone (HAZ), and Base Metal (BM) to determine material-specific crack growth parameters. A coupled thermo-mechanical finite element model is used to predict the RS fields induced during single- and multi-pass repair welding, followed by three-dimensional FCG simulations incorporating semi-elliptical surface defects and elliptical embedded cracks under the influence of RS. Parametric analyses are performed to evaluate the effects of weld bead removal, number of passes, and inter-pass temperature on the RS evolution, Stress Intensity Factors (SIFs), and synthetic S–N curves. The experimental results show the WM exhibits the lowest threshold SIF range, while the BM shows the highest. The numerical results indicate that multi-pass welding with controlled inter-pass temperature reduces RS magnitudes by up to 25%, whereas weld bead removal improves the fatigue life by mitigating local stress concentration. The developed numerical framework is applied to a large-scale wind turbine hub to demonstrate its predictive capability, with the results showing that RS can entail a twofold reduction of the fatigue life. The proposed methodology provides a robust basis and highly cost efficient means for optimising repair welding parameters to enhance fatigue performance in service-critical cast iron structures.