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Future lunar exploration will be based on in-situ resource utilization (ISRU) techniques. The most abundant raw material on the Moon is lunar regolith, which, however, is very scarce on Earth, making the study of simulants a necessity. The objective of this study is to characterize and investigate the sintering behavior of EAC-1A lunar regolith simulant. The characterization of the simulant included the determination of the phase assemblage, characteristic temperatures determination and water content analysis. The results are discussed in the context of sintering experiments of EAC-1A simulant, which showed that the material can be sintered to a relative density close to 90%, but only within a very narrow range of temperatures (20–30 °C). Sintering experiments were performed for sieved and unsieved, as well as for dried and non-dried specimens of EAC-1A. In addition, an analysis of the densification and mechanical properties of the sintered specimens was done. The sintering experiments at different temperatures showed that the finest fraction of sieved simulant can reach a higher maximum sintering temperature, and consequently a higher densification and biaxial strength. The non-dried powder exhibited higher densification and biaxial strength after sintering compared to the dried specimen. This difference was explained with a higher green density of the non-dried powder during pressing, rather than due to an actual influence on the sintering mechanism. Nevertheless, drying the powder prior to sintering is important to avoid the overestimation of the strength of specimens to be fabricated on the Moon.
Refractory chemically complex alloys with bcc-based microstructures show great potential for high-temperature applications but most of them exhibit limited room-temperature ductility, which remains a challenge. One such example is the AlMo0.5NbTa0.5TiZr alloy, mainly consisting of a nano-scaled structure with an ordered B2 matrix and a high-volume fraction of aligned cuboidal and coherently embedded A2 precipitates. This work aims to investigate how the cooling rate after hot isostatic pressing of the AlMo0.5NbTa0.5TiZr alloy affects its microstructure and its resulting hardness and fracture toughness at room temperature. A slow cooling rate of 5 °C/min leads to a coarse microstructure consisting of aligned slabs (mean A2 precipitate ≈ 25 nm) with a nanohardness of about 8 GPa. In contrast, after the fastest cooling rate (30 °C/min), the A2 precipitates become more cubic with an edge length of ≈ 16 nm, resulting in an increase in nanohardness by 10 %. The fracture toughness is roughly independent of the cooling rate and its mean value (≈ 4.2 MPa∙m1/2) resembles that of some B2 intermetallics and other A2/B2 alloys. As the lattice misfit between the A2 and B2 phases is known to play a key role in microstructure formation and evolution, its temperature dependence between 20 and 900 °C was investigated. These findings offer insights into the evolution of the microstructure and room-temperature mechanical properties of the AlMo0.5NbTa0.5TiZr alloy, which could help the development of advanced chemically complex alloys.
Understanding the mechanical behavior of silicon nanowires is essential for the implementation of advanced nanoscale devices. Although bending tests are predominantly used for this purpose, their findings should be properly interpreted through modeling. Various modeling approaches tend to ignore parts of the effective parameter set involved in the rather complex bending response. This oversimplification is the main reason behind the spread of the modulus of elasticity and strength data in the literature. Addressing this challenge, a surface-based nanomechanical model is introduced in this study. The proposed model considers two important factors that have so far remained neglected despite their significance: (i) intrinsic stresses composed of the initial residual stress and surface-induced residual stress and (ii) anisotropic implementation of surface stress and elasticity. The modeling study is consolidated with molecular dynamics-based study of the native oxide surface through reactive force fields and a series of nanoscale characterization work through in situ threepoint bending test and Raman spectroscopy. The treatment of the test data through a series of models with increasing complexity demonstrates a spread of 85 GPa for the modulus of elasticity and points to the origins of ambiguity regarding silicon nanowire properties, which are some of the most commonly employed nanoscale building blocks. A similar conclusion is reached for strength with variations of up to 3 GPa estimated by the aforementioned nanomechanical models. Precise consideration of the nanowire surface state is thus critical to comprehending the mechanical behavior of silicon nanowires accurately. Overall, this study highlights the need for a multiscale theoretical framework to fully understand the size-dependent mechanical behavior of silicon nanowires, with fortifying effects on the design and reliability assessment of future nanoelectromechanical systems.
Die klassische Metallographie basiert auf Abbildungen einzelner Schliffebenen und kann auf räumliche Formen und Anordnungen des Gefüges nur bedingt schließen. Die Idee, aus metallographischen Serienschliffen dreidimensionale Gefügestrukturen zu rekonstruieren, ist daher naheliegend und nicht neu. Allerdings ist der Aufwand, in Handarbeit viele Einzel-Schliffe zu präparieren und zu Bildstapeln zusammenzusetzen, sehr hoch und steht einer häufigen Anwendung entgegen.
Deshalb wird an der BAM ein Roboter-gestütztes 3D-Metallographie-System entwickelt, das an einer Schliffprobe die Schritte Präparation und Bildeinzug vollautomatisch mit vielen Wiederholungen ausführt. Die Präparation umfasst Schleifen, Polieren und optional Ätzen der Schlifffläche, der Bildeinzug autofokussierte lichtmikroskopische Aufnahmen bei mehreren Vergrößerungsstufen. Der erhaltene Bildstapel wird anschließend vorverarbeitet, segmentiert und in ein 3D-Modell umgesetzt, das einer mikrotomographischen Aufnahme ähnelt, allerdings mit besserer lateraler Auflösung bei großem Volumen. Im Gegensatz zu tomographischen Verfahren besteht die Möglichkeit der Kontrastierung durch klassische chemische Ätzung. Die Integration eines REMs ist geplant. Bislang durchgeführte Arbeiten verdeutlichen die Möglichkeiten der Darstellung von Heißgas-Korrosionsschichten, Grauguss-Werkstoffen und Keramik-basierten mikroelektronischen Strukturen (Vias).
A pseudosymmetric description of the crystal lattice derived from a single wideangle Kikuchi pattern can have several causes. The small size (<15%) of the sector covered by an electron backscatter diffraction pattern, the limited precision of the projection centre position and the Kikuchi band definition are crucial. Inherent pseudosymmetries of the crystal lattice and/or structure also pose a challenge in the analysis of Kikuchi patterns. To eliminate experimental errors as much as possible, simulated Kikuchi patterns of 350 phases have been analysed using the software CALM [Nolze et al. (2021). J. Appl. Cryst. 54, 1012–1022] in order to estimate the frequency of and reasons for pseudosymmetric crystal lattice descriptions. Misinterpretations occur in particular when the atomic scattering factors of non-equivalent positions are too similar and reciprocal-lattice points are systematically missing. As an example, a pseudosymmetry prediction depending on the elements involved is discussed for binary AB compounds with B1 and B2 structure types. However, since this is impossible for more complicated phases, this approach cannot be directly applied to compounds of arbitrary composition and structure.
To visualize the varying tetragonal distortions in high carbon martensitic steels by EBSD, two different approaches have been applied on backscattered Kikuchi diffraction (BKD) patterns. A band-edge refinement technique called Refined Accuracy (RA) (Oxford Instruments) is compared with a technique called Pattern Matching (PM), which optimizes the fit to a simulated BKD signal. RA distinguishes between hypothetical phases of different fixed 𝑐∕𝑎, while PM determines a best fitting continuous 𝑐∕𝑎 by projective transformation of a master pattern. Both techniques require stored BKD patterns.
The sensitivity of the 𝑐∕𝑎-determination was tested by investigating the microstructure of a ferritic steel with an expected 𝑐∕𝑎 = 1. The influence of the Kikuchi pattern noise on 𝑐∕𝑎 was compared for a single or 40 averaged frames per measuring point, and turned out to be not significant. The application of RA and PM on the martensitic microstructure delivered qualitatively similar maps of 𝑐∕𝑎. The comparison of RA and PM shows that RA is suitably fast and precise during mapping the martensite 𝑐∕𝑎 ratio in analyses of high carbon martensite, especially for fast initial surveys. As RA leads quantitatively to higher noise in 𝑐∕𝑎, the PM analysis can be used for higher precision results.
Fatigue tests were performed on the forged aluminum alloy EN AW-2618A in the T61 state. Different stress ratios (R = -1, R = 0.1) were selected to study the influence of mean stress on fatigue life. Two overaged states (10 h/230 ◦C, 1000 h/230 ◦C) were also tested to investigate the influence of overaging on fatigue life. Transmission electron microscopy (TEM) was used to characterize the precipitates (S-phase), which are mainly responsible for the strength of the alloy. A fractographic analysis was also performed to determine the failure mode. Overaging reduces the fatigue life compared to the T61 state. The longer the aging time, the lower the fatigue resistance. The reason is the decrease in (yield) strength, which correlates with the radius of the S-phase: the precipitate radius increases by a factor of approximately two for the overaged states compared to the initial state. The analysis of the fracture surfaces showed crack initiation occurs predominantly on the outer surface and is
associated with the primary phases.
The derivation of a crystal structure and its phase-specific parameters from a single wide-angle backscattered Kikuchi diffraction pattern requires reliable extraction of the Bragg angles. By means of the first derivative of the lattice profile, an attempt is made to determine fully automatically and reproducibly the band widths in simulated Kikuchi patterns. Even under such ideal conditions (projection centre, wavelength and lattice plane traces are perfectly known), this leads to a lattice parameter distribution whose mean shows a linear offset that correlates with the mean atomic number Z of the pattern-forming phase. The consideration of as many Kikuchi bands as possible reduces the errors that typically occur if only a single band is analysed. On the other hand, the width of the resulting distribution is such that higher image resolution of diffraction patterns, employing longer wavelengths to produce wider bands or the use of higher interference orders is less advantageous than commonly assumed.
High energy X-ray synchrotron diffraction is used to investigate the elastic anisotropy of the nickel-based superalloy IN718 produced by laser powder bed fusion (PBF-LB). This material is characterized by a columnar grain morphology with some crystallographic texture. The material is subjected to elastic loading to determine the diffraction elastic constants (DECs). Furthermore, the single-crystal elastic constants (SCEC) are refined from these experiments using different micromechanical models. The results show that each micromechanical model predicts a specific set of SCEC that well describes the elastic anisotropy of PBF-LB/IN718.
A band width determination using the first derivative of the band profile systematically underestimates the true Bragg angle. Corrections are proposed to compensate for the resulting offset Δa/a of the mean lattice parameters derived from as many Kikuchi band widths as possible. For dynamically simulated Kikuchi patterns, Δa/a can reach up to 8% for phases with a high mean atomic number Z, whereas for much more common low-Z materials the offset decreases linearly. A predicted offset Δa/a = f(Z) is therefore proposed, which also includes the unit-cell volume and thus takes into account the packing density of the scatterers in the material. Since Z is not always available for unknown phases, its substitution by Zmax, i.e. the atomic number of the heaviest element in the compound, is still acceptable for an approximate correction. For simulated Kikuchi patterns the offset-corrected lattice parameter deviation is Δa/a < 1.5%. The lattice parameter ratios, and the angles α, β and γ between the basis vectors, are not affected at all.1.5%. The lattice parameter ratios, and the angles , and between the basis vectors, are not affected at all.
(1) Background: The desire to avoid autograft harvesting in implant dentistry has prompted an ever-increasing quest for bioceramic bone substitutes, which stimulate osteogenesis while resorbing in a timely fashion. Consequently, a highly bioactive silicon containing calcium alkali orthophosphate (Si-CAP) material was created, which previously was shown to induce greater bone cell maturation and bone neo-formation than β-tricalcium phosphate (β-TCP) in vivo as well as in vitro. Our study tested the hypothesis that the enhanced effect on bone cell function in vitro and in sheep in vivo would lead to more copious bone neoformation in patients following sinus floor augmentation (SFA) employing Si-CAP when compared to β-TCP. (2) Methods: The effects of Si-CAP on osteogenesis and Si-CAP resorbability were evaluated in biopsies harvested from 38 patients six months after SFA in comparison to β-TCP employing undecalcified histology, histomorphometry, and immunohistochemical analysis of osteogenic marker expression. (3) Results: Si-CAP as well as β-TCP supported matrix mineralization and bone formation. Apically furthest away from the original bone tissue, Si-CAP induced significantly higher bone formation, bone-bonding (bone-bioceramic contact), and granule resorption than β-TCP. This was in conjunction with a higher expression of osteogenic markers. (4) Conclusions: Si-CAP induced higher and more advanced bone formation and resorbability than β-TCP, while β-TCP’s remarkable osteoconductivity has been widely demonstrated. Hence, Si-CAP constitutes a well-suited bioactive graft choice for SFA in the clinical arena.
To accelerate the growth of Industry 4.0 technologies, the digitalization of mechanical testing laboratories as one of the main data-driven units of materials processing industries is introduced in this paper. The digital lab infrastructure consists of highly detailed and standard-compliant materials testing knowledge graphs for a wide range of mechanical testing processes, as well as some tools that enable the efficient ontology development and conversion of heterogeneous materials’ mechanical testing data to the machine-readable data of uniform and standardized structures. As a basis for designing such a digital lab, the mechanical testing ontology (MTO) was developed based on the ISO 23718 and ISO/IEC 21838-2 standards for the semantic representation of the mechanical testing experiments, quantities, artifacts, and report data. The trial digitalization of materials mechanical testing lab was successfully performed by utilizing the developed tools and knowledge graph of processes for converting the various experimental test data of heterogeneous structures, languages, and formats to standardized Resource Description Framework (RDF) data formats. The concepts of data storage and data sharing in data spaces were also introduced and SPARQL queries were utilized to evaluate how the introduced approach can result in the data retrieval and response to the competency questions. The proposed digital materials mechanical testing lab approach allows the industries to access lots of trustworthy and traceable mechanical testing data of other academic and industrial organizations, and subsequently organize various data-driven research for their faster and cheaper product development leading to a higher performance of products in engineering and ecological aspects.
This contribution contains the raw data used to compare experimental results with thermodynamic calculations using the CALPHAD method, which is related to the research article “The AlMo0.5NbTa0.5TiZr refractory high entropy superalloy: experimental findings and comparison with calculations using the CALPHAD method” [1] , and therefore this article can be used as a basis for interpreting the data contained therein. The AlMo0.5NbTa0.5TiZr refractory superalloy was characterized in the cast and annealed condition (1400 °C for 24 h) in order to measure grain size and to identify and measure the size and area fraction of the phases present. The raw data of this article include X-ray diffraction (XRD) measurements, microstructural characterization by scanning and transmission electron microscopy (SEM and TEM), and elemental analysis by energy dispersive X-ray spectroscopy (EDX). XRD includes the determination of phases and the lattice parameters (A2, B2, and hexagonal structure). Microstructural analysis by scanning and transmission electron microscopy includes (1) identification of composition, size, and volume fraction of the present phases and (2) determination of grain size. Based on these experimental data, it is possible to identify similarities and discrepancies with the data calculated using the CALPHAD method for the alloy under study in Ref. [1] , which provides the basis for better and more efficient development of reliable databases.
Une transition mondiale vers des systèmes énergétiques plus durables, abordables et fiables a été initiée par l’accord de Paris et l’Agenda 2030 des Nations unies pour un développement durable. Il s’agit là d’un défi industriel majeur car les systèmes et infrastructures énergétiques résilients au changement climatique exigent de se positionner pour le long terme. Se pencher sur le comportement dans la durée des matériaux structurels - principalement des métaux et des alliages - s’impose alors comme une nécessité. Dans cette optique, « La corrosion : un défi pour une société durable »présente une série de cas montrant l’importance de la tenue à la corrosion et de la protection anticorrosion des métaux et des alliages pour le développement de systèmes durables, économiques et fiables de production d’énergie.
Although layer-based additive manufacturing methods such as laser powder bed fusion (PBF-LB) offer an immense geometrical freedom in design, they are typically subject to a build-up of internal stress (i.e. thermal stress) during manufacturing. As a consequence, significant residual stress (RS) is retained in the final part as a footprint of these internal stresses. Furthermore, localized melting and solidification inherently induce columnar-type grain growth accompanied by crystallographic texture. Although diffraction-based methods are commonly used to determine the RS distribution in PBF-LB parts, such features pose metrological challenges in their application. In theory, preferred grain orientation invalidates the hypothesis of isotropic material behavior underlying the common methods to determine RS. In this work, more refined methods are employed to determine RS in PBF-LB/M/IN718 prisms, based on crystallographic texture data. In fact, the employment of direction-dependent elastic constants (i.e. stress factors) for the calculation of RS results in insignificant differences from conventional approaches based on the hypothesis of isotropic mechanical properties. It can be concluded that this result is directly linked to the fact that the {311} lattice planes typically used for RS analysis in nickel-based alloys have high multiplicity and less strong texture intensities compared with other lattice planes. It is also found that the length of the laser scan vectors determines the surface RS distribution in prisms prior to their removal from the baseplate. On removal from the baseplate the surface RS considerably relaxes and/or redistributes; a combination of the geometry and the scanning strategy dictates the sub-surface RS distribution.
In failure analysis, micro-fractographic analysis of fracture surfaces is usually performed based on practical knowledge which is gained from available studies, own comparative tests, from the literature, as well as online databases. Based on comparisons with already existing images, fracture mechanisms are determined qualitatively. These images are mostly two-dimensional and obtained by light optical and scanning electron imaging techniques. So far, quantitative assessments have been limited to macrocopically determined percentages of fracture types or to the manual measurement of fatigue striations, for example. Recently, more and more approaches relying on computer algorithms have been taken, with algorithms capable of finding and classifying differently structured fracture characteristics. For the Industrial Collective Research (Industrielle Gemeinschaftsforschung, IGF) project “iFrakto” presented in this paper, electron-optical images are obtained, from which topographic information is calculated. This topographic information is analyzed together with the conventional 2D images. Analytical algorithms and deep learning are used to analyze and evaluate fracture characteristics and are linked to information from a fractography database. The most important aim is to provide software aiding in the application of fractography for failure analysis. This paper will present some first results of the project.
Since the TEM has the capacity to observe the atomic structure of materials, in-situ TEM synthesis methods are uniquely suited to advance our fundamental understanding of the bottom-up dynamics that drive the formation of nanostructures. E-beam induced fragmentation (potentially identified as a manifestation of Coulomb explosion) and electron stimulated desorption (ESD) are phenomena that have received attention because they trigger chemical and physical reactions that can lead to the production of various nanostructures. Here we report a simple TEM protocol implemented on WO2.9 microparticles supported on thin amorphous carbon substrates. The method produces various nanostructures such as WC nanoparticles, WC supported films and others. Nevertheless, we focus on the gradual graphitization and gasification of the C substrate as it interacts with the material expelled from the WO2.9 microparticles. The progressive gasification transforms the substrate from amorphous C down to hybrid graphitic nanoribbons incorporating W nanoparticles. We think these observations open interesting possibilities for the synthesis of 2D nanomaterials in the TEM.
Irradiation assisted stress corrosion cracking (IASCC) is known to be a combination of applied stress, and a corrosive environment in irradiated materials, but an appropriate understanding of how each of these components affects cracking is not yet clear. In this work, we isolate the role of grain boundary (GB) oxidation in IASCC. For this purpose, solution-annealed 304L stainless steel irradiated in reactor to 5.4 or 69 dpa was studied using a miniaturized four-point bend technique. Two modes of bend tests were conducted; straining in simulated pressurized water reactor primary water (PW) at 320 ◦C in an incremental manner, and pre-oxidation in PW at 320 ◦C without application of stress followed by dynamic straining in purified Ar at the same temperature until crack initiation. Exposure of the 5.4 dpa sample for 210 h in high temperature water initiated cracks in Ar at 60% of the yield stress (0.6YS), whereas the companion sample of the same dose exposed for 1010 h cracked in Ar at 0.5YS. The long-term exposure in water led to GB oxidation that ultimately lowered the crack initiation stress. Dynamic straining in water resulted in larger crack lengths and greater crack depths indicating stress accelerated oxidation and cracking. Dislocation pile-ups at dislocation channel-grain boundary sites provide an amplification of the applied stress to a level consistent with the fracture stress of the grain boundary oxide, providing an explanation for IASCC that occurs at applied stresses well below the irradiated yield stress of the alloy. There was no evidence of cracking upon straining of an unoxidized 69 dpa sample in Ar to well above yield, confirming that the irradiated state is not inherently susceptible to intergranular (IG) cracking and that oxidized GBs are responsible for initiation of IG cracking.
Die AG Fraktographie im DVM/DGM-Gemeinschaftsgremium „Elektronenmikroskopie in der Materialforschung“ betreibt seit 2013 eine fraktographische online-Datenbank („FractoDB“), die für das interessierte Fachpublikum kostenfrei zur Verfügung steht. Die Analyse und Bewertung von Bruchflächen und der darauf befindlichen Bruchmerkmale ist ein wichtiger Teilaspekt der Schadensanalyse bei der Suche nach Schadensmechanismen und Schadensursachen. Risse und Brüche an realen Bauteilen können nur dann bewertet werden, wenn gut dokumentierte Vergleichsbrüche aus Laborversuchen zur Verfügung stehen, sei es an Proben oder an Vergleichs-Bauteilen. Daher trägt die AG Fraktographie Bildmaterial zusammen, führt systematisch Laborversuche und Ringversuche durch und analysiert Brüche aus Schadensfällen. Die gewonnenen Daten werden zu Datensätzen zusammengestellt und über die Datenbank zugänglich gemacht. Derzeit ist ein Bestand von über 400 Datensätzen mit insgesamt über 4.500 Bildern verfügbar, welcher durchsucht werden kann und in Anlehnung an die VDI 3822 organisiert ist. Weitere Aktivitäten der AG Fraktographie, die in der FractoDB abgebildet werden, sind u.a. die Entwicklung einer fraktographischen Symbolik und die Analyse von Bruchmerkmalen mittels Machine Learning. Über die aktuellen Ergebnisse und Planungen wird berichtet.
Using the method of directional solidification, single crystals of experimental nickel-based superalloys with negative, zero, and positive γ/γ' misfits are obtained. The γ' solvus, solidus, and liquidus temperatures of the alloys are determined, and the microstructures of the alloys after directional solidification, heat treatment, and creep tests are investigated. Creep tests are performed at temperatures of 800 and 1000°C. It is found that single crystals of the alloy with a negative γ/γ' misfit have the highest creep resistance and lifetime (the crystal lattice period of the γ' phase is smaller than that of the γ matrix).
The damage mechanisms of metallic components produced by process laser powder bed fusion differ significantly from those typically observed in conventionally manufactured variants of the same alloy. This is due to the unique microstructures of additively manufactured materials. Herein, the focus is on the study of the evolution of creep damage in stainless steel 316L specimens produced by laser powder bed fusion. X-ray computed tomography is used to unravel the influence of the process-specific microstructure from the influence of the initial void distribution on creep damage mechanisms. The void distribution of two specimens tested at 600 °C and 650 °C is analyzed before a creep test, after an interruption, and after fracture. The results indicate that the formation of damage is not connected to the initial void distribution. Instead, damage accumulation at grain boundaries resulting from intergranular cracking is observed.
Fractography plays a critical role in failure analysis of engineering components and has a considerable importance for safety investigations. Usually, the interpretation of fracture surfaces is done by experts with the help of literature and experimental data, that requires a lot of experience. The use of deep learning (DL) with neural networks in failure analysis becomes more and more relevant with the rapidly developing possibilities. Especially, the modern network architectures can assist fractographers in determining various fracture features on SEM images of the fracture surfaces. The basis for the best possible evaluation is the understanding of the influence of the input data used for training deep neural networks (DNN). Therefore, this study discusses the influence of the selection of the input data used for the prediction quality of these networks in order to take this into account for future data acquisition. Specimens of various metallic materials were subjected to fatigue cracking experiment under laboratory conditions. The fractured surfaces were then imaged using various modes or detectors (such as SE, BSE and topography) in SEM, and those captured images were used to create a training data set. The relevance of the individual data for the quality of the prediction is determined by a specific combination of the different detector data. For the training, the well-established architecture of a UNet-ResNet34 with a fixed set of hyperparameters is used. It has been found in this present study that the combination of all input data significantly increases the prediction accuracy, whereby even the combination of SE and BSE data provides considerable advantages over the exclusive use of SE images.
This article reports temperature-dependent elastic properties (Young’s modulus, shear modulus) of three alloys measured by the dynamic resonance method. The alloys Ti-6Al-4V, Inconel IN718, and AISI 316 L were each investigated in a variant produced by an additive manufacturing processing route and by a conventional manufacturing processing route. The datasets include information on processing routes and parameters, heat treatments, grain size, specimen dimensions, and weight, as well as Young’s and shear modulus along with their measurement uncertainty. The process routes and methods are described in detail. The datasets were generated in an accredited testing lab, audited as BAM reference data, and are hosted in the open data repository Zenodo. Possible data usages include the verification of the correctness of the test setup via Young’s modulus comparison in low-cycle fatigue (LCF) or thermo-mechanical fatigue (TMF) testing campaigns, the design auf VHCF specimens and the use as input data for simulation purposes.
In this work, we employed glow discharge optical emission spectrometry (GD-OES) depth profiling as a fast and semi-quantitative method to investigate the aluminum (Al) current collector degradation in commercial lithium cobalt oxide (LCO) pouch cells with no Al2O3 pretreatment. After battery aging, a heterogeneous deposit was found on the surface of the cathode. Gray hotspot areas within an extensive pale white region were formed. Consistent with energy dispersive X-ray (EDX) analysis of micro-cross sections milled via targeted focused ion beam (FIB), an Al-containing layer of approximately 3 µm can be observed using GD-OES. We attribute one main cause of this layer is the degradation of the Al current collector. The nonuniform growth of this layer was investigated by performing GD-OES depth profiling at different in-plane positions. We found that the gray area has a higher mass concentration of Al, probably in metallic form, whereas the white area was probably covered more homogeneously with Al2O3, resulting from the inhomogeneous distribution of the pitting positions on the current collector. Compared to FIB-EDX, GD-OES enables a faster and more convenient depth profile analysis, which allows the more productive characterization of lithium-ion batteries (LIBs), and consequently benefits the development of preferable battery materials.
A systematic study on a face‐centered cubic‐based compositionally complex alloy system Al–Co–Cr–Cu–Fe–Ni in its single‐phase state is carried out, where a mother senary compound Al₈Co₁₇Cr₁₇Cu₈Fe₁₇Ni₃₃ and five of its suballoys, obtained by removing one element at a time, are investigated and exhaustively analyzed determining the contribution of each alloying element in the solid solution. The senary and the quinaries are compared using experimental techniques including X‐ray absorption spectroscopy, X‐ray diffraction, transmission electron microscopy, and first principles hybrid Monte Carlo/molecular dynamics simulations. Chemical short‐range order and bond length distances have been determined both at the experimental and computational level. Electronic structure and local atomic distortions up to 5.2 Å have been correlated to the microhardness values. A linear regression model connecting hardness with local lattice distortions is presented.
A giant Zn segregation transition is revealed using CALPHAD-integrated density-based modeling of segregation into Fe grain boundaries (GBs). The results show that above a threshold of only a few atomic percent Zn in the alloy, a substantial amount of up to 60 at.% Zn can segregate to the GB. We found that the amount of segregation abruptly increases with decreasing temperature, while the Zn content in the alloy required for triggering the segregation transition decreases. Direct evidence of the Zn segregation transition is obtained using high-resolution scanning transmission electron microscopy. Base on the model, we trace the origin of the segregation transition back to the low cohesive energy of Zn and a miscibility gap in Fe-Zn GB, arising from the magnetic ordering effect, which is confirmed by ab-initio calculations. We also show that the massive Zn segregation resulting from the segregation transition greatly assists with liquid wetting and reduces the work of separation along the GB. The current predictions suggest that control over Zn segregation, by both alloy design and optimizing the galvanization and welding processes, may offer preventive strategies against liquid metal embrittlement.
In the past two decades, numerous relaxation or physical aging experiments of metallic glasses have revealed signatures of intermittent atomic-scale processes. Revealed via intensity cross-correlations from coherent scattering using X-ray photon correlation spectroscopy (XPCS), the observed abrupt changes in the time-domain of atomic motion does not fit the picture of gradual slowing down of relaxation times and their origin continues to remain unclear. Using a binary Lennard-Jones model glass subjected to microsecond-long isotherms, we show here that temporally and spatially heterogeneous atomic-cluster activity at different length-scales drive the emergence of highly non-monotonous intensity cross-correlations. The simulated XPCS experiments reveal a variety of time-dependent intensity-cross correlations that, depending on both the structural evolution and the 𝑞-space sampling, give detailed insights into the possible structural origins of intermittent aging measured with XPCS.
Mean-field modeling and Phase-field simulation of Grain Growth under Directional driving forces
(2024)
Directional grain growth is a common phenomenon in the synthetic and natural evolution of various polycrystals. It occurs in the presence of an external driving force, such as a temperature gradient, along which grains show a preferred, yet competitive, growth. Novel additive manufacturing processes, with intense, localized energy deposition, are prominent examples of when directional grain growth can occur, beneath the melting pool. In this work, we derive a phenomenological mean-field model and perform 3D phase-field simulations to investigate the directional grain growth and its underlying physical mechanisms. The effect of the intensity of driving force is simulated and systematically analyzed at the evolving growth front as well as various cross-sections perpendicular to the direction of the driving force. We found that although the directional growth significantly deviates from normal grain growth, it is still governed by a power law relation <R> \propto t^n with an exponent n ~ 0.6–0.7. The exponent
exhibits a nontrivial dependence on the magnitude of the directional driving force, such that the lowest growth exponent is observed for intermediate driving forces. We elaborate that this can originate from the fact that the forces at grain boundary junctions evolve out of balance under the influence of the directional driving force. With increasing the driving forces, the growth exponent asymptotically approaches a value of n~0.63, imposed by the largest possible grain aspect ratio for given grain boundary energies. The current combined mean-field and phase-field framework pave the way for future exploration in broader contexts such as the evolution of complex additively manufactured microstructures.
Reliable measurement of the size of polydisperse, complex-shaped commercial nanopowders is a difficult but necessary task, e.g., for regulatory requirements and toxicity risk assessment. Suitable methods exist for the accurate characterization of the size of non-aggregated, stabilized, spherical and monodisperse nanoparticles. In contrast, industrial nanoscale powders usually require dedicated sample preparation procedures developed for the analysis method of choice. These nano-powders tend to agglomerate and/or aggregate, a behavior which in combination with an innate broad particle size distribution and irregular shape often significantly alters the achievable accuracy of the measured size parameters. The present study systematically tests two commercially available nanoscale powders using different sample preparation methods for correlative analysis by scanning electron microscopy, dynamic light scattering, Brunauer–Emmet–Teller method and differential mobility analysis. One focus was set on the sample preparation by embedding nanoparticles in carbon-based hot-mounting resin. Literature on this topic is scarce and the accuracy of the data extracted from cross sections of these particles is unclearly stated. In this paper systematic simulations on the deviation of the size parameters of well-defined series of nanoparticles with different shapes from the nominal value were carried out and the contributing factors are discussed.
AbstractHigh-strength aluminum alloys used in aerospace and automotive applications obtain their strength through precipitation hardening. Achieving the desired mechanical properties requires precise control over the nanometer-sized precipitates. However, the microstructure of these alloys changes over time due to aging, leading to a deterioration in strength. Typically, the size, number, and distribution of precipitates for a quantitative assessment of microstructural changes are determined by manual analysis, which is subjective and time-consuming. In our work, we introduce a progressive and automatable approach that enables a more efficient, objective, and reproducible analysis of precipitates. The method involves several sequential steps using an image repository containing dark-field transmission electron microscopy (DF-TEM) images depicting various aging states of an aluminum alloy. During the process, precipitation contours are generated and quantitatively evaluated, and the results are comprehensibly transferred into semantic data structures. The use and deployment of Jupyter Notebooks, along with the beneficial implementation of Semantic Web technologies, significantly enhances the reproducibility and comparability of the findings. This work serves as an exemplar of FAIR image and research data management.
A density-based phase field model is developed where the free energy functional is explicitly linked with molecular dynamics and is referred to as the Molecular Phase Field Method (MoPF). MoPF simulations involve expressing interatomic potentials in terms of density to form a density based free energy functional. Inputs to this functional are taken from atomistics such that the phase field density profile matches the corresponding density profile from atomistic simulations. We analyze our results by comparing the MoPF calculated excess interfacial energies with excess interfacial energies calculated using molecular dynamics associated with several nickel grain boundaries. Additionally, a comparison is made between our results and the interfacial energies of a \Sigma7 boundary across a variety of FCC systems simulated using density functional theory. The MoPF method is able to successfully predict grain boundary free energy trends between grain boundary and material types offering an atomistically informed mesoscale formulation for studying grain boundary physics.
Knowledge representation in the Materials Science and Engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant (consistent) and variant (context-specific) knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific. In this paper, an approach how to maintain a comprehensive MSE-centric terminology composing a mid-level ontology–the Platform MaterialDigital Core Ontology (PMDco)–via MSE community-based curation procedures is presented. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics. Additionally, it demonstrates how the PMDco lowers development and integration thresholds. Moreover, the research highlights how to fuel it with real-world data sources ranging from manually conducted experiments and simulations with continuously automated industrial applications.
This study investigates the sintering and crystallization behavior and kinetic of the bioactive glass (BG) 13–93 with nominal composition (in mol%): 54.6 SiO2 - 1.7 P2O3 - 22.1 CaO - 6.0 Na2O - 7.9 K2O - 7.7 MgO. Sintering and crystallization were investigated non-isothermally for various particle size fractions smaller than 315 μm as well as for bulk samples. Densification was not hindered by the presence of crystalline phases across all particle size fractions. Afterwards, wollastonite was found as the dominant crystal phase at higher temperature which resorb primary surface precipitation-like quartz crystallites. The growth direction shifts into volume when the sample surface is nearly covered. The crystal growth rate of wollastonite was calculated from the crystalline surface layer thickness measured during heating. The findings of this study are relevant for the high temperature processing of BG 13–93.
The unusual behavior observed in the coefficient of thermal expansion and specific heat capacity of CrFeNi, CoCrNi, and CoCrFeNi medium/high-entropy alloys is commonly referred to as the K-state effect. It is shown to be independent of the Curie temperature, as demonstrated by temperature-dependent magnetic moment measurements. CoCrFeNi alloy is chosen for detailed characterization; potential reasons for the K-state effect such as texture, recrystallization, and second-phase precipitation are ruled out. An examination of the electronic structure indicates the formation of a pseudo-gap in the Density of States, which suggests a specific chemical interaction between Ni and Cr atoms upon alloying. Hybrid Monte Carlo/Molecular Dynamic (MC/MD) simulations indicate the presence of non-negligible chemical short-range order (CSRO). Local lattice distortions are shown to be negligible, although deviations around Cr and Ni elements from those expected in a fully disordered structure are experimentally observed by X-ray absorption spectroscopy. The determined bonding distances are in good agreement with MC/MD calculations. A mechanism is proposed to explain the anomalies and calorimetric experiments and their results are used to validate the mechanism.
Irradiation assisted stress corrosion cracking (IASCC) is a form of intergranular stress corrosion cracking that occurs in irradiated austenitic alloys. It requires an irradiated microstructure along with high temperature water and stress. The process is ubiquitous in that it occurs in a wide range of austenitic alloys and water chemistries, but only when the alloy is irradiated. Despite evidence of this degradation mode that dates back to the 1960s, the mechanism by which it occurs has remained elusive. Here, using high resolution electron backscattering detection to analyze local stress-strain states, high resolution transmission electron microscopy to identify grain boundary phases at crack tips, and decoupling the roles of stress and grain boundary oxidation, we are able to unfold the complexities of the phenomenon to reveal the mechanism by which IASCC occurs. The significance of the findings impacts the mechanical integrity of core components of both current and advanced nuclear reactor designs worldwide.
AbstractThe high-temperature corrosion behaviors of the equimolar CrCoNi medium-entropy alloy and CrMnFeCoNi high-entropy alloy were studied in a gas atmosphere consisting of a volumetric mixture of 10% H2O, 2% O2, 0.5% SO2, and 87.5% Ar at 800 °C for up to 96 h. Both alloys were initially single-phase fcc with a mean grain size of ~ 50 μm and a homogeneous chemical composition. The oxide layer thickness of CrMnFeCoNi increased linearly with exposure time while it remained constant at ~ 1 μm for CrCoNi. A Cr2O3 layer and minor amounts of (Co,Ni)Cr2O4 developed on the latter while three oxide layers were detected on the former, i.e., a thin and continuous chromium rich oxide layer at the oxide/alloy interface, a dense (Mn,Cr)3O4 layer in the center and a thick and porous layer of Mn3O4 and MnSO4 at the gas/oxide interface. Additionally, a few metal sulfides were observed in the CrMnFeCoNi matrix. These results were found to be in reasonable agreement with thermodynamic calculations.
Processing and cytocompatibility of Cu-doped and undoped fluoride-containing bioactive glasses
(2024)
Sintered or additive-manufactured bioactive glass (BG) scaffolds are highly interesting for bone replacement applications. However, crystallization often limits the high-temperature processability of bioactive glasses (BGs). Thus, the BG composition must combine high bioactivity and processability. In this study, three BGs with nominal molar (%) compositions 54.6SiO2-1.7P2O3-22.1CaO-6.0Na2O-7.9K2O-7.7MgO (13–93), 44.8SiO2-2.5P2O3-36.5CaO-6.6Na2O-6.6K2O-3.0CaF2 (F3) and 44.8SiO2-2.5P2O3-35.5CaO-6.6Na2O-6.6K2O-3.0CaF2-1.0CuO (F3–Cu) were investigated. The dissolution and ion release kinetics were investigated on milled glass powder and crystallized particles (500–600 μm). All glasses showed the precipitation of hydroxyapatite (HAp) crystals after 7 days of immersion in simulated body fluid. No significant differences in ion release from glass and crystalline samples were detected. The influence of surface roughness on cytocompatibility and growth of preosteoblast cells (MC3T3-E1) was investigated on sintered and polished BG pellets. Results showed that sintered BG pellets were cytocompatible, and cells were seen to be well attached and spread on the surface after 5 days of incubation. The results showed an inverse relation of cell viability with the surface roughness of pellets, and cells were seen to attach and spread along the direction of scratches.
Extended X-ray absorption fine structure (EXAFS) conducted on an equiatomic MoNbTaW bcc medium-entropy alloy that was annealed at 2273 K reveals unexpectedly small 1st and 2nd shell element-specific lattice distortions. An experimental size-mismatch parameter, δexp, is determined to be ca. 50% lower than the corresponding calculated value. Around W, short-range order (SRO) preferring 4d elements in the 1st and 2nd shells persists. A Nb-W ordering is found, which is reminiscent of ordering emerging at lower temperatures in the B2(Mo,W;Ta,Nb)- and B32(Nb,W)-phases. With high-temperature ordering preferences in fcc also foreshadowing low-temperature phase, these findings suggest a general feature of high-temperature SRO.
The digitalization of materials science and engineering (MSE) is currently leading to remarkable advancements in materials research, design, and optimization, fueled by computer‐driven simulations, artificial intelligence, and machine learning. While these developments promise to accelerate materials innovation, challenges in quality assurance, data interoperability, and data management have to be addressed. In response, the adoption of semantic web technologies has emerged as a powerful solution in MSE. Ontologies provide structured and machine‐actionable knowledge representations that enable data integration, harmonization, and improved research collaboration. This study focuses on the tensile test ontology (TTO), which semantically represents the mechanical tensile test method and is developed within the project Plattform MaterialDigital (PMD) in connection with the PMD Core Ontology. Based on ISO 6892‐1, the test standard‐compliant TTO offers a structured vocabulary for tensile test data, ensuring data interoperability, transparency, and reproducibility. By categorizing measurement data and metadata, it facilitates comprehensive data analysis, interpretation, and systematic search in databases. The path from developing an ontology in accordance with an associated test standard, converting selected tensile test data into the interoperable resource description framework format, up to connecting the ontology and data is presented. Such a semantic connection using a data mapping procedure leads to an enhanced ability of querying. The TTO provides a valuable resource for materials researchers and engineers, promoting data and metadata standardization and sharing. Its usage ensures the generation of finable, accessible, interoperable, and reusable data while maintaining both human and machine actionability.