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The large surface-to-volume ratio of nanoparticles is understood to be the source of many interesting phenomena. The melting temperature of nanoparticles is shown to dramatically reduce compared to bulk material. Yet, at temperatures below this reduced melting point, a liquid-like atomic arrangement on the surface of nanoparticles is still anticipated to influence its properties. To understand such surface effects, here, we study the coalescence of Au nanoparticles of various sizes using molecular dynamics simulations. Analysis of the potential energy and Lindemann index distribution across the nanoparticles reveals that high-energy, high-mobility surface atoms can enable the coalescence of nanoparticles at temperatures much lower than their corresponding melting point. The smaller the nanoparticles, the larger the difference between their melting and coalescence temperatures. For small enough particles and/or elevated enough temperatures, we found that the coalescence leads to a melting transition of the two nominally solid nanoparticles, here discussed in relation to the heat released due to the surface reduction upon the coalescence and the size dependence of latent heat. Such discontinuous melting transitions can lead to abrupt changes in the properties of nanoparticles, important for their applications at intermediate temperatures.
The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples.
In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge.
Fully-reversed fatigue behavior of scarf joint repairs for wind turbine blade shell applications
(2022)
To enable a quick and cost-effective return to service for wind turbine blades, localized repairs can be executed by technicians in the field. Scarf repairs, shown to be highly efficient with a smooth load transition across angled joint walls and a restored aerodynamic profile, are the focus of this work. The failure mechanisms of these structures were examined under quasi-static tensile and fully-reversed cyclic loading. While the scarf ratio was held constant at 1:50, the repair layup was varied between large-to-small and small-to-large. The effect of the presence of resin pockets and the fiber orientation mismatch between parent and repair material on the restored strength of BIAX ±45° glass fiber reinforced polymer scarf joint structures was studied.
A new patented dynamic mechanical analysis (DMA) is presented, where the tensile, bending- or torsional stiffness of a media can be characterized in-situ during the phase transition from liquid to solid. An epoxy system, e.g. Hexion L285/H287, is filled into an elastomer container, such as a silicone tube. This can be mounted into a conventional OMA and, based on a linear viscoelastic approach, the storage modulus (E';G'), the loss modulus (E'';G'') and the loss angle tan(δ) can be measured at constant temperature as a function of time in order to investigate the liquid to sol-gel to solid transition. With this new method, the stiffness increase as a result of the cure process can be directly measured more precisely than with a rheometer in a shear plate set-up, because using an elastomer container gives a defined cross section for calculating the Young's modulus.
The interest in repair technologies for polymer composites has increased significantly over the last decades, due to the growing use of these materials in structural applications. In this study, poly (ethylene-co-methacrylic acid) (EMAA) was used as self-healing agent to glass fiber/epoxy composite. Materials with EMAA contents of 2 wt% and 5 wt% were manufactured using Resin Transfer Molding (RTM) and the effects of the healing agent on the properties were investigated using tensile tests and Dynamic Mechanical Analysis (DMA). Results show slight variation of properties, which was more pronounced as the content of EMAA increased. In addition, the healing efficiency was investigated through fatigue tests and the addition of higher content of EMAA increased the number of cycles to failure after the healing activation cycle.
Due to combined cyclic mechanical and thermal loading during operation, the material of exhaust gas conducting components of combustion engines is exposed to thermomechanical fatigue (TMF). This leads to formation and growth of cracks, especially at the most highly stressed points of these components. In order to better predict the service life of cracked components before failure, it is necessary to identify a crack propagation law for the material used. Isothermal crack propagation tests have been carried out at several temperatures with a typical cast iron to identify such a law. The crack length is measured by the potential drop method. The compliance method, fractography and thermographic camera measurements have been used to validate and calibrate the potential drop measurements. Each of the isothermal tests has been simulated using a specially developed FEM-algorithm based on remeshing and remapping. This algorithm has been implemented in python and ABAQUS. Thereby, the crack tip region is modeled by collapsed Quad8 elements. From the individual simulations, the cyclic crack tip opening displacement (ΔCTOD) is extracted and regarded as a potential fracture mechanics parameter which controls the crack growth rate. By combining the data from the experiments and the simulations, the crack propagation law has been identified. Finally, anisothermal crack propagation tests have been performed for validation of the crack growth law.
In diesem Artikel werden die verschiedenen additiven Fertigungsverfahren und ihre Anwendungsmöglichkeiten vorgestellt. Der Fokus liegt hierbei auf Silikatkeramik. Für jedes 3D Druckverfahren werden die Möglichkeiten mit Silikatkeramik, Hochleistungskeramik und Dentalkeramik aufgezeigt. Auf den Nutzen der verschiedenen 3D Druckverfahren für industrielle Anwendungen, den privaten Bereich, sowie die Verwendung für Kunst und Design wird eingegangen. Das Potenzial der Additiven Fertigung wird auch für den Bereich der Keramik in der dentalen Anwendung bewertet.
Das hochaktuelle Thema der Integration und Wiederverwendung von Wissen und Daten aus Herstellung, Bearbeitung und Charakterisierung von Materialien ('Digitalisierung von Materialien') wird in den Projekten Innovationsplattform MaterialDigital (PMD, materialdigital.de) und Materials-open-Lab (Mat-o-Lab, matolab.org) adressiert. In diesem Beitrag werden die Weiterentwicklungen in diesen Projekten hinsichtlich der Speicherung von Zugversuchsdaten gemäß einer normenkonformen (DIN EN ISO 6892-1:2019-11) ontologischen Repräsentation vorgestellt. Das umfasst den Weg von der Entwicklung einer Ontologie nach Norm, der Konvertierung von Daten aus Standardtests in das interoperable RDF-Format bis hin zur Verknüpfung von Ontologie und Daten. Letztendlich können die entsprechenden Daten in einem Triple Store abgelegt und abgefragt werden.
Seit Beginn der Luftfahrt Anfang des letzten Jahrhunderts ist die Menschheit auf der Suche nach neuen Materialien, die das Abenteuer Fliegen sicherer, angenehmer, schneller und rentabler gestalten. Hochentropielegierungen sind solche vielversprechenden Materialien. Die richtige Analytik hilft dabei, besser zu verstehen, wie deren Zusammensetzung und atomare Anordnung die makroskopischen Eigenschaften beeinflusst.
To reveal the corrosion resistance of casing steel/mortar interface in CO2 injection condition, sandwich samples were prepared and exposed up to 20 weeks in aquifer fluid under 10 MPa and 60 °C. Cross section analysis revealed the crevice corrosion as main mechanism instead of pitting corrosion, which would be expected to happen in the extremely high Chloride concentration. Detailed analysis using EDS line scan shown the slow diffusion of Chloride, suggesting why pitting did not happen after 20 weeks. To mimic the passivated steel surface, the steel coupon was passivated in simulated pore solution having pH 13.5 for 42 days. The passivated coupon was further exposed to NGB solution for 28 days. Electrochemical characterization was performed along the exposure processes to reveal the change in impedance, indicating the corrosion resistance of steel casing/mortar interface.
Interpreting high-temperature corrosion induced by mixed-gas atmospheres is challenging due to the different contributions of oxidizing gases. Here, a comprehensive study on the combined oxidation/sulfidation using label molecules is presented. Fe-Cr model alloys with 2 wt% and 9 wt% Cr were isothermally exposed using a volumetric mixture of 0.5%S16O2/27%H218O and 0.5%S16O2/7%H218O at 650 ◦C for 5 h and then characterized by secondary ion mass spectroscopy (SIMS). Additionally, the reactions were followed in-situ utilizing energy dispersive X-ray diffraction. The study showed that both S16O2 and H218O contribute to the oxidation of the alloys but to different extents depending on the Cr-content.
Self-healing agents have the potential to restore mechanical properties and extend service life of composite materials. Thermoplastic healing agents have been extensively investigated for this purpose in epoxy matrix composites due to their strong adhesion to epoxy and their ability to fill in microcracks. One of the most
investigated thermoplastic additives for this purpose is poly(ethylene-co-methacrylic acid) (EMAA). Despite the ability of thermoplastic healing agents to restore mechanical properties, it is important to assess how the addition of thermoplastic healing agents affect properties of the original epoxy material. In this work, EMAA was added to epoxy resin and the effect of the additive on fracture toughness of epoxy was evaluated. Results indicate that although added in low concentrations, EMAA can affect fracture toughness.
Der Beitrag beinhaltet Themen vom H2Safety@BAM-Kompetenzfeld Sensorik, Analytik und zertifizierte Referenzmaterialien (SensRef) mit Fokus auf Mess- und Prüfverfahren mit verschiedenen Sensortechnologien und Ultraschallwellen:
Metrologie zur Wasserstoffspeicherung - Euramet-Vorhaben "MefHySto",
Erkennung von freigesetztem Wasserstoff sowie die Bestimmung des Wasserstoff-Luftverhälntisses mit Gassensoren, zerstörungsfreie Fehlstellenerkennung mit integriertem Zustandsüberwachungssystem basierend auf geführten Ultraschallwellen zur Lebensdauerüberwachung von Composite-Behältern (Wasserstoffspeicher) sowie faseroptische Sensorik zur Schadenfrüherkennung von Wasserstoffspeichern aufgrund erkennbarer Dehnungsänderungen an Druckbehältern.
The field of materials science is defined as “the study of the properties of solid materials and how those properties are determined by a material’s composition and structure.”. Many –if not most– of the materials that are produced nowadays owe their properties to structures engineered down to the nanoscopic level. This need has been partly realized thanks to the understanding of materials’ building blocks via characterization techniques that reach this level of resolution. Transmission electron microscopy, since its first implementation in the early 1930s (in Berlin), has been implemented to achieve imaging –and spectral– analysis at lateral resolutions down to the atomic level.
In this contribution, a series of practical examples will be presented, where applied materials are characterized by a range of transmission electron microscopy techniques to understand structural and functional properties of a wide range of materials. Among these materials examples will be presented on structural conventionally and additively manufactured metallic alloys, high entropy alloys, dissimilar aluminum-to-steel welds, magnetic nanoparticles, ceramic coatings, high temperature oxidation products. Addressed will be either the effect of processing route or that of the exposure to experimental conditions similar to those found in the respective intended applications.
The aim of a fractographic investigation is the evaluation of macroscopic and microscopic fracture surface characteristics and, as a result, the determination of the fracture mechanism of a component from a failure case. The basis for such evaluations of fracture characteristics comes from actual comparative mechanical testing and from the literature. A fractographic analysis can be very complex and, in any case, requires considerable experience. In the IGF project "iFrakto", software is being developed that quantitatively determines fracture characteristics and fracture mechanisms utilizing digitized expert knowledge, machine learning, and standard 2D and topographical data from SEM imaging. Topographical data are obtained from 4QBSE detector using shape-from-shading technology. In the medium term, a software tool should provide knowledge-based suggestions for the evaluation of fracture surfaces in real time during SEM work or at subsequent evaluation. As a basis for this, round robins were carried out among fractographers in order to create a knowledge base, to query the practice-relevant requirements for such tools and to carry out first practical tests. Actual results are presented and the relevance of the evaluation strategy is evaluated.
The aim of a fractographic investigation is the evaluation of macroscopic and microscopic fracture surface characteristics and, as a result, the determination of the fracture mechanism of a component from a failure case. The basis for such evaluations of fracture characteristics comes from actual comparative mechanical testing and from the literature. A fractographic analysis can be very complex and, in any case, requires considerable experience.
Machine learning methods enables the quantitative determination of fracture characteristics and fracture mechanisms utilizing digitized expert knowledge [1]. Although the application of SE images provides promising results, additional information is required to obtain reliable solutions. As expected, BSE and 3D information helps to improve the classification (Fig. 1). But only a fast, widely integrated, and automated topography measurement can provide the required amount of referenced surface data for the application of machine learning methods.
To fulfil these requirements, topographical data are obtained from a BSE detector with four symmetric segments (4Q-BSE) using shape-from-shading technology [2]. Surface height calculation is performed live during image acquisition and provides immediate feedback in three dimensions. All available signals (SE, BSE and more if applicable) are recorded simultaneously together with the surface topography and stored in a multichannel data file. This guaranties the same geometrical reference for all data, which is required for further analysis (Fig. 2).
When applying machine learning methods to topographic data together with SEM images, topographic information must be provided as depth image. Consequently, a unique height scale is required for all applied data with different magnifications. This requires a calibrated height measurement, which is ensured with the integrated 3D calibration of the topographic acquisition and a dedicated calibration sample. Thus, a large number of data sets from different fracture samples was generated and used as training data for machine learning.
The interest to additively manufacture Nickel-based superalloys has substantially grown within the past decade both academically and industrially. More specifically, additive manufacturing processes such as laser powder bed fusion (LPBF) offer the ability to produce dense parts within a single manufacturing step. In fact, the exceptional freedom in design associated with the layer-based nature of the processes is of particular interest for the complex shapes typically required in turbine applications. In certain cases, the overall part performance can be achieved by tailoring the microstructure and the crystallographic texture to the specific application. However, these advantages must be paid at a price: the large local temperature gradients associated with the rapid melting and solidification produce parts that inherently contain large residual stress in the as-manufactured state. In addition, the presence of pores in the final part may further affect the in-service part failure. As among Nickel-based alloys Inconel 718 exhibits excellent weldability, this alloy has been widely studied in open research in the domain of LPBF. However, significant microsegregation of the heavier alloying elements such as Niobium and Molybdenum accompanied by dislocation entanglements may preclude the application of conventional heat treatment schedules. Therefore, different post processing heat treatments are required for laser powder bed fused Inconel 718 as compared to conventional variants of the same alloy.
In this study, we investigated two different heat treatment routes for LPBF Inconel 718. In a first routine, the samples were stress relieved and subsequently subjected to hot isostatic pressing (HIP) followed by a solution heat treatment and a two-step age (referred to as FHT). In a second routine, the samples were subjected to a single-step direct age post stress relieving heat treatment (referred to DA). We investigated the consequences of such heat treatment schedules on the microstructure, texture, and mechanical behavior. We show that by applying a DA heat treatment the typical columnar microstructure possessing a crystallographic texture is retained, while an equiaxed untextured microstructure prevails in case of an FHT heat treatment. We further evaluate how these heat treatments affect the mechanical behaviour on the macroscopic and microscopic scale.
Additive manufacturing (AM) of metallic alloys has gained momentum in the past decade for industrial applications. The microstructures of AM metallic alloys are complex and hierarchical from the macroscopic to the nanometer scale. When using laser-based powder bed fusion (L-PBF) process, two main microstructural features emerge at the nanoscale: the melt pool boundaries (MPB) and the solidification cellular substructure.
Here, details of the MPB are revealed to clearly show the three-dimensional nature of MPBs with changes of cell growth of direction and their relation to their surrounding cellular substructure, as investigated by transmission electron microscopy (TEM) for L-PBF 316L austenitic stainless steel (cf. Figure 1). A hitherto unknown modulated substructure with a period of 21 nm is further discovered within cells as the result of a partial Ga+-focused ion beam-induced ferritic transformation of the austenite. Cell cores and cell boundaries differ notably regarding the modulated substructure.
Ziel von fraktographischen Untersuchungen ist die Auswertung von makroskopischen und mikroskopischen Bruchflächenmerkmalen und daraus resultierend die Bestimmung des Bruchmechanismus eines Bauteils aus einem Schadensfall. Die Grundlage für die Bewertung von Bruchmerkmalen stammt dabei aus zuvor durchgeführten eigenen Vergleichsversuchen und aus der Literatur. Eine fraktographische Analyse kann sehr aufwändig sein und setzt in jedem Fall erhebliches Erfahrungswissen voraus. Im IGF-Vorhaben „iFrakto“ wird Software entwickelt, die auf Basis von digitalisiertem Expertenwissen, Machine Learning und unter Zuhilfenahme von Topographie-Daten anhand von REM-Aufnahmen Bruchmerkmale und Bruchmechanismen quantitativ bestimmt, s. Abbildung. Solche Software soll mittelfristig direkt am REM oder bei der nachfolgenden Auswertung wissensbasierte Vorschläge für die Bewertung von Bruchflächen liefern. Als Grundlage hierfür wurden Ringversuche unter Fraktograph/inn/en durchgeführt, um die Wissensbasis zu schaffen, die praxisrelevanten Anforderungen an solche Software abzufragen und erste Praxistests durchzuführen. Die bisherigen Ergebnisse werden vorgestellt und die Relevanz der Auswertestrategie und unterschiedlicher Sensordaten bewertet.